Veri Temizleme-1
Melike Kara Sahin
2026-02-22
Verilerin Temizlenmesi-Analizlerden Önce Verilerin Taranması
Bu dosyada amaç, elde edilen verilerde ortaya çıkan bazı problemlerin çözümleme sürecini ve verilerin genel analizlere hazır hale getirilmesi aşamalarından bazılarını ele almaktadır.
Gerekli paketlerin ve veri setinin yüklenmesi.
library(dplyr)## Warning: package 'dplyr' was built under R version 4.4.3##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(haven)## Warning: package 'haven' was built under R version 4.4.3ogrenci <- read_sav("bsgturm8.sav")
head(ogrenci)## # A tibble: 6 × 19
## BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H
## <dbl+lbl> <dbl+lbl> <dbl+l> <dbl+l> <dbl+l> <dbl+l> <dbl+l> <dbl+l> <dbl+l>
## 1 2 [Boy] 1 [Agree a … 2 [Agr… 2 [Agr… 1 [Agr… 1 [Agr… 1 [Agr… 1 [Agr… 1 [Agr…
## 2 1 [Girl] 2 [Agree a … 1 [Agr… 1 [Agr… 2 [Agr… 4 [Dis… 4 [Dis… 4 [Dis… 4 [Dis…
## 3 2 [Boy] 2 [Agree a … 3 [Dis… 1 [Agr… 2 [Agr… 3 [Dis… 4 [Dis… 2 [Agr… 4 [Dis…
## 4 1 [Girl] 2 [Agree a … 1 [Agr… 1 [Agr… 2 [Agr… 4 [Dis… 4 [Dis… 4 [Dis… 4 [Dis…
## 5 2 [Boy] 1 [Agree a … 2 [Agr… 4 [Dis… 1 [Agr… 1 [Agr… 1 [Agr… 1 [Agr… 2 [Agr…
## 6 1 [Girl] 2 [Agree a … 1 [Agr… 1 [Agr… 3 [Dis… 4 [Dis… 4 [Dis… 4 [Dis… 4 [Dis…
## # ℹ 10 more variables: BSBM19I <dbl+lbl>, BSBM22A <dbl+lbl>, BSBM22B <dbl+lbl>,
## # BSBM22C <dbl+lbl>, BSBM22D <dbl+lbl>, BSBM22E <dbl+lbl>, BSBM22F <dbl+lbl>,
## # BSBM22G <dbl+lbl>, BSBM22H <dbl+lbl>, BSMMAT01 <dbl+lbl>Veri Seti Ön İnceleme
Veri setini incelemek için temel fonksiyonlar kullanılmıştır.
summary(ogrenci)## BSBG01 BSBM19A BSBM19B BSBM19C
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000
## Median :2.000 Median :2.000 Median :2.000 Median :2.000
## Mean :1.506 Mean :2.184 Mean :2.427 Mean :2.449
## 3rd Qu.:2.000 3rd Qu.:3.000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :2.000 Max. :4.000 Max. :4.000 Max. :4.000
## NA's :80 NA's :130 NA's :155 NA's :152
## BSBM19D BSBM19E BSBM19F BSBM19G
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000
## Median :2.000 Median :2.000 Median :2.000 Median :2.000
## Mean :2.071 Mean :2.298 Mean :2.416 Mean :2.421
## 3rd Qu.:3.000 3rd Qu.:3.000 3rd Qu.:3.000 3rd Qu.:4.000
## Max. :4.000 Max. :4.000 Max. :4.000 Max. :4.000
## NA's :167 NA's :190 NA's :168 NA's :160
## BSBM19H BSBM19I BSBM22A BSBM22B
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:2.000 1st Qu.:1.000 1st Qu.:2.000 1st Qu.:1.000
## Median :3.000 Median :3.000 Median :2.000 Median :2.000
## Mean :2.916 Mean :2.671 Mean :2.403 Mean :2.507
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:3.000 3rd Qu.:4.000
## Max. :4.000 Max. :4.000 Max. :4.000 Max. :4.000
## NA's :161 NA's :157 NA's :169 NA's :212
## BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.00 Min. :1.000
## 1st Qu.:1.000 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.00 1st Qu.:1.000
## Median :2.000 Median :3.000 Median :3.000 Median :3.00 Median :2.000
## Mean :2.408 Mean :2.683 Mean :2.844 Mean :2.65 Mean :2.282
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.00 3rd Qu.:4.000
## Max. :4.000 Max. :4.000 Max. :4.000 Max. :4.00 Max. :4.000
## NA's :197 NA's :194 NA's :210 NA's :223 NA's :185
## BSBM22H BSMMAT01
## Min. :1.000 Min. :216.0
## 1st Qu.:1.000 1st Qu.:420.2
## Median :2.000 Median :502.9
## Mean :2.198 Mean :504.2
## 3rd Qu.:3.000 3rd Qu.:587.3
## Max. :4.000 Max. :851.1
## NA's :190#psych
psych paketini kullanarak daha detaylı betimsel istatistikler elde edilmiştir.
library(psych)## Warning: package 'psych' was built under R version 4.4.3describe(ogrenci)## vars n mean sd median trimmed mad min max range
## BSBG01 1 4845 1.51 0.50 2.00 1.51 0.00 1.00 2.0 1.00
## BSBM19A 2 4795 2.18 1.07 2.00 2.10 1.48 1.00 4.0 3.00
## BSBM19B 3 4770 2.43 1.21 2.00 2.41 1.48 1.00 4.0 3.00
## BSBM19C 4 4773 2.45 1.14 2.00 2.44 1.48 1.00 4.0 3.00
## BSBM19D 5 4758 2.07 1.08 2.00 1.96 1.48 1.00 4.0 3.00
## BSBM19E 6 4735 2.30 1.14 2.00 2.25 1.48 1.00 4.0 3.00
## BSBM19F 7 4757 2.42 1.15 2.00 2.40 1.48 1.00 4.0 3.00
## BSBM19G 8 4765 2.42 1.14 2.00 2.40 1.48 1.00 4.0 3.00
## BSBM19H 9 4764 2.92 1.07 3.00 3.02 1.48 1.00 4.0 3.00
## BSBM19I 10 4768 2.67 1.22 3.00 2.71 1.48 1.00 4.0 3.00
## BSBM22A 11 4756 2.40 1.05 2.00 2.38 1.48 1.00 4.0 3.00
## BSBM22B 12 4713 2.51 1.17 2.00 2.51 1.48 1.00 4.0 3.00
## BSBM22C 13 4728 2.41 1.19 2.00 2.38 1.48 1.00 4.0 3.00
## BSBM22D 14 4731 2.68 1.05 3.00 2.73 1.48 1.00 4.0 3.00
## BSBM22E 15 4715 2.84 1.08 3.00 2.93 1.48 1.00 4.0 3.00
## BSBM22F 16 4702 2.65 1.12 3.00 2.69 1.48 1.00 4.0 3.00
## BSBM22G 17 4740 2.28 1.21 2.00 2.23 1.48 1.00 4.0 3.00
## BSBM22H 18 4735 2.20 1.12 2.00 2.12 1.48 1.00 4.0 3.00
## BSMMAT01 19 4925 504.18 110.64 502.87 503.79 123.79 216.03 851.1 635.07
## skew kurtosis se
## BSBG01 -0.02 -2.00 0.01
## BSBM19A 0.48 -1.02 0.02
## BSBM19B 0.11 -1.54 0.02
## BSBM19C 0.10 -1.41 0.02
## BSBM19D 0.59 -0.97 0.02
## BSBM19E 0.33 -1.31 0.02
## BSBM19F 0.12 -1.42 0.02
## BSBM19G 0.16 -1.39 0.02
## BSBM19H -0.47 -1.13 0.02
## BSBM19I -0.19 -1.55 0.02
## BSBM22A 0.20 -1.15 0.02
## BSBM22B 0.02 -1.48 0.02
## BSBM22C 0.13 -1.50 0.02
## BSBM22D -0.12 -1.22 0.02
## BSBM22E -0.36 -1.21 0.02
## BSBM22F -0.14 -1.36 0.02
## BSBM22G 0.30 -1.47 0.02
## BSBM22H 0.43 -1.20 0.02
## BSMMAT01 0.05 -0.62 1.58#gtsummary
gtsummary paketini kullanarak sunuma hazır tablolar oluşturulmuştur.
library(gtsummary)## Warning: package 'gtsummary' was built under R version 4.4.3ogrenci %>%
select(1:5) %>%
tbl_summary(
statistic = all_continuous() ~ c("{min}, {max}"),
missing = "always"
)## ! Column(s) "BSBG01", "BSBM19A", "BSBM19B", "BSBM19C", and "BSBM19D" are class
## "haven_labelled".
## ℹ This is an intermediate data structure not meant for analysis.
## ℹ Convert columns with `haven::as_factor()`, `labelled::to_factor()`,
## `labelled::unlabelled()`, and `unclass()`. Failure to convert may have
## unintended consequences or result in error.
## <https://haven.tidyverse.org/articles/semantics.html>
## <https://larmarange.github.io/labelled/articles/intro_labelled.html#unlabelled>| Characteristic | N = 4,9251 |
|---|---|
| GEN\SEX OF STUDENT | |
| 1 | 2,393 (49%) |
| 2 | 2,452 (51%) |
| Unknown | 80 |
| MAT\AGREE\ENJOY LEARNING MATHEMATICS | |
| 1 | 1,554 (32%) |
| 2 | 1,636 (34%) |
| 3 | 776 (16%) |
| 4 | 829 (17%) |
| Unknown | 130 |
| MAT\AGREE\WISH HAVE NOT TO STUDY MATH | |
| 1 | 1,527 (32%) |
| 2 | 1,044 (22%) |
| 3 | 835 (18%) |
| 4 | 1,364 (29%) |
| Unknown | 155 |
| MAT\AGREE\MATH IS BORING | |
| 1 | 1,294 (27%) |
| 2 | 1,278 (27%) |
| 3 | 965 (20%) |
| 4 | 1,236 (26%) |
| Unknown | 152 |
| MAT\AGREE\LEARN INTERESTING THINGS | |
| 1 | 1,889 (40%) |
| 2 | 1,369 (29%) |
| 3 | 774 (16%) |
| 4 | 726 (15%) |
| Unknown | 167 |
| 1 n (%) | |
#vtable
vtable paketi kullanılarak özet tablolar oluşturulmuştur.
library(vtable)## Warning: package 'vtable' was built under R version 4.4.3## Loading required package: kableExtra## Warning: package 'kableExtra' was built under R version 4.4.3##
## Attaching package: 'kableExtra'## The following object is masked from 'package:dplyr':
##
## group_rowssumtable(ogrenci, summ = c('notNA(x)', 'min(x)','max(x)'))## Warning in sumtable(ogrenci, summ = c("notNA(x)", "min(x)", "max(x)")): Some
## labelled variables have unlabeled values. Treating these as numeric variables
## and ignoring labels.| Variable | NotNA | Min | Max |
|---|---|---|---|
| BSMMAT01 | 4925 | 216 | 851 |
kable
kable fonksiyonu kullanarak markdown formatında tablolar oluşturulmuştur.
kable(describe(ogrenci), format='markdown', caption="Betimsel İstatistikler", digits=2)| vars | n | mean | sd | median | trimmed | mad | min | max | range | skew | kurtosis | se | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| BSBG01 | 1 | 4845 | 1.51 | 0.50 | 2.00 | 1.51 | 0.00 | 1.00 | 2.0 | 1.00 | -0.02 | -2.00 | 0.01 |
| BSBM19A | 2 | 4795 | 2.18 | 1.07 | 2.00 | 2.10 | 1.48 | 1.00 | 4.0 | 3.00 | 0.48 | -1.02 | 0.02 |
| BSBM19B | 3 | 4770 | 2.43 | 1.21 | 2.00 | 2.41 | 1.48 | 1.00 | 4.0 | 3.00 | 0.11 | -1.54 | 0.02 |
| BSBM19C | 4 | 4773 | 2.45 | 1.14 | 2.00 | 2.44 | 1.48 | 1.00 | 4.0 | 3.00 | 0.10 | -1.41 | 0.02 |
| BSBM19D | 5 | 4758 | 2.07 | 1.08 | 2.00 | 1.96 | 1.48 | 1.00 | 4.0 | 3.00 | 0.59 | -0.97 | 0.02 |
| BSBM19E | 6 | 4735 | 2.30 | 1.14 | 2.00 | 2.25 | 1.48 | 1.00 | 4.0 | 3.00 | 0.33 | -1.31 | 0.02 |
| BSBM19F | 7 | 4757 | 2.42 | 1.15 | 2.00 | 2.40 | 1.48 | 1.00 | 4.0 | 3.00 | 0.12 | -1.42 | 0.02 |
| BSBM19G | 8 | 4765 | 2.42 | 1.14 | 2.00 | 2.40 | 1.48 | 1.00 | 4.0 | 3.00 | 0.16 | -1.39 | 0.02 |
| BSBM19H | 9 | 4764 | 2.92 | 1.07 | 3.00 | 3.02 | 1.48 | 1.00 | 4.0 | 3.00 | -0.47 | -1.13 | 0.02 |
| BSBM19I | 10 | 4768 | 2.67 | 1.22 | 3.00 | 2.71 | 1.48 | 1.00 | 4.0 | 3.00 | -0.19 | -1.55 | 0.02 |
| BSBM22A | 11 | 4756 | 2.40 | 1.05 | 2.00 | 2.38 | 1.48 | 1.00 | 4.0 | 3.00 | 0.20 | -1.15 | 0.02 |
| BSBM22B | 12 | 4713 | 2.51 | 1.17 | 2.00 | 2.51 | 1.48 | 1.00 | 4.0 | 3.00 | 0.02 | -1.48 | 0.02 |
| BSBM22C | 13 | 4728 | 2.41 | 1.19 | 2.00 | 2.38 | 1.48 | 1.00 | 4.0 | 3.00 | 0.13 | -1.50 | 0.02 |
| BSBM22D | 14 | 4731 | 2.68 | 1.05 | 3.00 | 2.73 | 1.48 | 1.00 | 4.0 | 3.00 | -0.12 | -1.22 | 0.02 |
| BSBM22E | 15 | 4715 | 2.84 | 1.08 | 3.00 | 2.93 | 1.48 | 1.00 | 4.0 | 3.00 | -0.36 | -1.21 | 0.02 |
| BSBM22F | 16 | 4702 | 2.65 | 1.12 | 3.00 | 2.69 | 1.48 | 1.00 | 4.0 | 3.00 | -0.14 | -1.36 | 0.02 |
| BSBM22G | 17 | 4740 | 2.28 | 1.21 | 2.00 | 2.23 | 1.48 | 1.00 | 4.0 | 3.00 | 0.30 | -1.47 | 0.02 |
| BSBM22H | 18 | 4735 | 2.20 | 1.12 | 2.00 | 2.12 | 1.48 | 1.00 | 4.0 | 3.00 | 0.43 | -1.20 | 0.02 |
| BSMMAT01 | 19 | 4925 | 504.18 | 110.64 | 502.87 | 503.79 | 123.79 | 216.03 | 851.1 | 635.07 | 0.05 | -0.62 | 1.58 |
#skimr
skimr paketini kullanılarak veri setinin detaylı bir özeti alınmıştır.
library(skimr)## Warning: package 'skimr' was built under R version 4.4.3skim(ogrenci)| Name | ogrenci |
| Number of rows | 4925 |
| Number of columns | 19 |
| _______________________ | |
| Column type frequency: | |
| numeric | 19 |
| ________________________ | |
| Group variables | None |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| BSBG01 | 80 | 0.98 | 1.51 | 0.50 | 1.00 | 1.00 | 2.00 | 2.00 | 2.0 | ▇▁▁▁▇ |
| BSBM19A | 130 | 0.97 | 2.18 | 1.07 | 1.00 | 1.00 | 2.00 | 3.00 | 4.0 | ▇▇▁▃▅ |
| BSBM19B | 155 | 0.97 | 2.43 | 1.21 | 1.00 | 1.00 | 2.00 | 4.00 | 4.0 | ▇▆▁▅▇ |
| BSBM19C | 152 | 0.97 | 2.45 | 1.14 | 1.00 | 1.00 | 2.00 | 4.00 | 4.0 | ▇▇▁▆▇ |
| BSBM19D | 167 | 0.97 | 2.07 | 1.08 | 1.00 | 1.00 | 2.00 | 3.00 | 4.0 | ▇▆▁▃▃ |
| BSBM19E | 190 | 0.96 | 2.30 | 1.14 | 1.00 | 1.00 | 2.00 | 3.00 | 4.0 | ▇▇▁▃▆ |
| BSBM19F | 168 | 0.97 | 2.42 | 1.15 | 1.00 | 1.00 | 2.00 | 3.00 | 4.0 | ▇▇▁▆▇ |
| BSBM19G | 160 | 0.97 | 2.42 | 1.14 | 1.00 | 1.00 | 2.00 | 4.00 | 4.0 | ▇▇▁▅▇ |
| BSBM19H | 161 | 0.97 | 2.92 | 1.07 | 1.00 | 2.00 | 3.00 | 4.00 | 4.0 | ▂▅▁▅▇ |
| BSBM19I | 157 | 0.97 | 2.67 | 1.22 | 1.00 | 1.00 | 3.00 | 4.00 | 4.0 | ▅▅▁▃▇ |
| BSBM22A | 169 | 0.97 | 2.40 | 1.05 | 1.00 | 2.00 | 2.00 | 3.00 | 4.0 | ▅▇▁▅▅ |
| BSBM22B | 212 | 0.96 | 2.51 | 1.17 | 1.00 | 1.00 | 2.00 | 4.00 | 4.0 | ▇▆▁▆▇ |
| BSBM22C | 197 | 0.96 | 2.41 | 1.19 | 1.00 | 1.00 | 2.00 | 4.00 | 4.0 | ▇▆▁▅▇ |
| BSBM22D | 194 | 0.96 | 2.68 | 1.05 | 1.00 | 2.00 | 3.00 | 4.00 | 4.0 | ▃▇▁▆▇ |
| BSBM22E | 210 | 0.96 | 2.84 | 1.08 | 1.00 | 2.00 | 3.00 | 4.00 | 4.0 | ▃▆▁▅▇ |
| BSBM22F | 223 | 0.95 | 2.65 | 1.12 | 1.00 | 2.00 | 3.00 | 4.00 | 4.0 | ▅▆▁▆▇ |
| BSBM22G | 185 | 0.96 | 2.28 | 1.21 | 1.00 | 1.00 | 2.00 | 4.00 | 4.0 | ▇▅▁▃▅ |
| BSBM22H | 190 | 0.96 | 2.20 | 1.12 | 1.00 | 1.00 | 2.00 | 3.00 | 4.0 | ▇▆▁▃▅ |
| BSMMAT01 | 0 | 1.00 | 504.18 | 110.64 | 216.03 | 420.19 | 502.87 | 587.31 | 851.1 | ▂▇▇▅▁ |
#DataExplorer
DataExplorer paketi kullanılarak veri seti hakkında otomatik rapor oluşturulmuştur.
library(DataExplorer)## Warning: package 'DataExplorer' was built under R version 4.4.3create_report(ogrenci)##
##
## processing file: report.rmd## | | | 0% | |. | 2% | |.. | 5% [global_options] | |... | 7% | |.... | 10% [introduce] | |.... | 12% | |..... | 14% [plot_intro]## | |...... | 17% | |....... | 19% [data_structure] | |........ | 21% | |......... | 24% [missing_profile]## | |.......... | 26% | |........... | 29% [univariate_distribution_header] | |........... | 31% | |............ | 33% [plot_histogram]## | |............. | 36% | |.............. | 38% [plot_density] | |............... | 40% | |................ | 43% [plot_frequency_bar] | |................. | 45% | |.................. | 48% [plot_response_bar] | |.................. | 50% | |................... | 52% [plot_with_bar] | |.................... | 55% | |..................... | 57% [plot_normal_qq]## | |...................... | 60% | |....................... | 62% [plot_response_qq] | |........................ | 64% | |......................... | 67% [plot_by_qq] | |.......................... | 69% | |.......................... | 71% [correlation_analysis]## | |........................... | 74% | |............................ | 76% [principal_component_analysis]## | |............................. | 79% | |.............................. | 81% [bivariate_distribution_header] | |............................... | 83% | |................................ | 86% [plot_response_boxplot] | |................................. | 88% | |................................. | 90% [plot_by_boxplot] | |.................................. | 93% | |................................... | 95% [plot_response_scatterplot] | |.................................... | 98% | |.....................................| 100% [plot_by_scatterplot] ## output file: C:/Users/HUAWE/Desktop/Doktora 4. Dönem/report.knit.md## "C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/pandoc" +RTS -K512m -RTS "C:\Users\HUAWE\Desktop\DOKTOR~4.DNE\REPORT~1.MD" --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output pandoc4e8830744052.html --lua-filter "C:\Users\HUAWE\AppData\Local\R\win-library\4.4\rmarkdown\rmarkdown\lua\pagebreak.lua" --lua-filter "C:\Users\HUAWE\AppData\Local\R\win-library\4.4\rmarkdown\rmarkdown\lua\latex-div.lua" --lua-filter "C:\Users\HUAWE\AppData\Local\R\win-library\4.4\rmarkdown\rmarkdown\lua\table-classes.lua" --embed-resources --standalone --variable bs3=TRUE --section-divs --table-of-contents --toc-depth 6 --template "C:\Users\HUAWE\AppData\Local\R\win-library\4.4\rmarkdown\rmd\h\default.html" --no-highlight --variable highlightjs=1 --variable theme=yeti --mathjax --variable "mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML" --include-in-header "C:\Users\HUAWE\AppData\Local\Temp\RtmpAN5NfS\rmarkdown-str4e88323277f4.html"##
## Output created: report.html#funModeling
funModeling paketini kullanılarak veri setindeki eksik değerler ve benzersiz değerler özetlenmiştir.
library(funModeling)## Warning: package 'funModeling' was built under R version 4.4.3## Loading required package: Hmisc## Warning: package 'Hmisc' was built under R version 4.4.3##
## Attaching package: 'Hmisc'## The following object is masked from 'package:psych':
##
## describe## The following objects are masked from 'package:dplyr':
##
## src, summarize## The following objects are masked from 'package:base':
##
## format.pval, units## funModeling v.1.9.6 :)
## Examples and tutorials at livebook.datascienceheroes.com
## / Now in Spanish: librovivodecienciadedatos.aidf_status(ogrenci)## variable q_zeros p_zeros q_na p_na q_inf p_inf
## 1 BSBG01 0 0 80 1.62 0 0
## 2 BSBM19A 0 0 130 2.64 0 0
## 3 BSBM19B 0 0 155 3.15 0 0
## 4 BSBM19C 0 0 152 3.09 0 0
## 5 BSBM19D 0 0 167 3.39 0 0
## 6 BSBM19E 0 0 190 3.86 0 0
## 7 BSBM19F 0 0 168 3.41 0 0
## 8 BSBM19G 0 0 160 3.25 0 0
## 9 BSBM19H 0 0 161 3.27 0 0
## 10 BSBM19I 0 0 157 3.19 0 0
## 11 BSBM22A 0 0 169 3.43 0 0
## 12 BSBM22B 0 0 212 4.30 0 0
## 13 BSBM22C 0 0 197 4.00 0 0
## 14 BSBM22D 0 0 194 3.94 0 0
## 15 BSBM22E 0 0 210 4.26 0 0
## 16 BSBM22F 0 0 223 4.53 0 0
## 17 BSBM22G 0 0 185 3.76 0 0
## 18 BSBM22H 0 0 190 3.86 0 0
## 19 BSMMAT01 0 0 0 0.00 0 0
## type unique
## 1 haven_labelled-vctrs_vctr-double 2
## 2 haven_labelled-vctrs_vctr-double 4
## 3 haven_labelled-vctrs_vctr-double 4
## 4 haven_labelled-vctrs_vctr-double 4
## 5 haven_labelled-vctrs_vctr-double 4
## 6 haven_labelled-vctrs_vctr-double 4
## 7 haven_labelled-vctrs_vctr-double 4
## 8 haven_labelled-vctrs_vctr-double 4
## 9 haven_labelled-vctrs_vctr-double 4
## 10 haven_labelled-vctrs_vctr-double 4
## 11 haven_labelled-vctrs_vctr-double 4
## 12 haven_labelled-vctrs_vctr-double 4
## 13 haven_labelled-vctrs_vctr-double 4
## 14 haven_labelled-vctrs_vctr-double 4
## 15 haven_labelled-vctrs_vctr-double 4
## 16 haven_labelled-vctrs_vctr-double 4
## 17 haven_labelled-vctrs_vctr-double 4
## 18 haven_labelled-vctrs_vctr-double 4
## 19 haven_labelled-vctrs_vctr-double 4920Kayıp Veri
ogrenci <- expss::drop_var_labs(ogrenci)## Registered S3 methods overwritten by 'expss':
## method from
## [.labelled Hmisc
## as.data.frame.labelled base
## print.labelled Hmischead(ogrenci)## # A tibble: 6 × 19
## BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 1 2 2 1 1 1 1 1 1
## 2 1 2 1 1 2 4 4 4 4 4
## 3 2 2 3 1 2 3 4 2 4 3
## 4 1 2 1 1 2 4 4 4 4 4
## 5 2 1 2 4 1 1 1 1 2 1
## 6 1 2 1 1 3 4 4 4 4 4
## # ℹ 9 more variables: BSBM22A <dbl>, BSBM22B <dbl>, BSBM22C <dbl>,
## # BSBM22D <dbl>, BSBM22E <dbl>, BSBM22F <dbl>, BSBM22G <dbl>, BSBM22H <dbl>,
## # BSMMAT01 <dbl>#Kayıp Veri Türleri
#Kayıp Veri İnceleme
Veri setinde herhangi bir kayıp değer olup olmadığı kontrol edilmiştir.
library(naniar)## Warning: package 'naniar' was built under R version 4.4.3##
## Attaching package: 'naniar'## The following object is masked from 'package:skimr':
##
## n_completelibrary(ggplot2)## Warning: package 'ggplot2' was built under R version 4.4.3##
## Attaching package: 'ggplot2'## The following objects are masked from 'package:psych':
##
## %+%, alphaany_na(ogrenci)## [1] TRUEVeri setindeki toplam kayıp değer sayısı ve oranı hesaplanmıştır.
n_miss(ogrenci)## [1] 3100prop_miss(ogrenci)## [1] 0.03312851Her bir değişkendeki kayıp değer sayısı hesaplanmıştır.
ogrenci %>% is.na() %>% colSums()## BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G
## 80 130 155 152 167 190 168 160
## BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F
## 161 157 169 212 197 194 210 223
## BSBM22G BSBM22H BSMMAT01
## 185 190 0Değişken ve gözlem bazında kayıp veri özetleri görüntülenmiştir.
miss_var_summary(ogrenci)## # A tibble: 19 × 3
## variable n_miss pct_miss
## <chr> <int> <num>
## 1 BSBM22F 223 4.53
## 2 BSBM22B 212 4.30
## 3 BSBM22E 210 4.26
## 4 BSBM22C 197 4
## 5 BSBM22D 194 3.94
## 6 BSBM19E 190 3.86
## 7 BSBM22H 190 3.86
## 8 BSBM22G 185 3.76
## 9 BSBM22A 169 3.43
## 10 BSBM19F 168 3.41
## 11 BSBM19D 167 3.39
## 12 BSBM19H 161 3.27
## 13 BSBM19G 160 3.25
## 14 BSBM19I 157 3.19
## 15 BSBM19B 155 3.15
## 16 BSBM19C 152 3.09
## 17 BSBM19A 130 2.64
## 18 BSBG01 80 1.62
## 19 BSMMAT01 0 0miss_var_table(ogrenci)## # A tibble: 18 × 3
## n_miss_in_var n_vars pct_vars
## <int> <int> <dbl>
## 1 0 1 5.26
## 2 80 1 5.26
## 3 130 1 5.26
## 4 152 1 5.26
## 5 155 1 5.26
## 6 157 1 5.26
## 7 160 1 5.26
## 8 161 1 5.26
## 9 167 1 5.26
## 10 168 1 5.26
## 11 169 1 5.26
## 12 185 1 5.26
## 13 190 2 10.5
## 14 194 1 5.26
## 15 197 1 5.26
## 16 210 1 5.26
## 17 212 1 5.26
## 18 223 1 5.26miss_case_summary(ogrenci)## # A tibble: 4,925 × 3
## case n_miss pct_miss
## <int> <int> <dbl>
## 1 122 18 94.7
## 2 818 18 94.7
## 3 878 18 94.7
## 4 939 18 94.7
## 5 960 18 94.7
## 6 961 18 94.7
## 7 962 18 94.7
## 8 963 18 94.7
## 9 964 18 94.7
## 10 965 18 94.7
## # ℹ 4,915 more rowsmiss_case_table(ogrenci)## # A tibble: 18 × 3
## n_miss_in_case n_cases pct_cases
## <int> <int> <dbl>
## 1 0 4332 88.0
## 2 1 343 6.96
## 3 2 43 0.873
## 4 3 10 0.203
## 5 4 5 0.102
## 6 5 2 0.0406
## 7 6 3 0.0609
## 8 8 49 0.995
## 9 9 20 0.406
## 10 10 3 0.0609
## 11 11 2 0.0406
## 12 12 1 0.0203
## 13 13 2 0.0406
## 14 14 2 0.0406
## 15 15 6 0.122
## 16 16 1 0.0203
## 17 17 21 0.426
## 18 18 80 1.62Kayıp veriyi görselleştirmek için çeşitli grafikler oluşturulmuştur.
library(rlang)## Warning: package 'rlang' was built under R version 4.4.3##
## Attaching package: 'rlang'## The following object is masked from 'package:data.table':
##
## :=library(ggplot2)
library(UpSetR)## Warning: package 'UpSetR' was built under R version 4.4.3library(naniar)
gg_miss_upset(ogrenci)## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## ℹ The deprecated feature was likely used in the UpSetR package.
## Please report the issue to the authors.
## This warning is displayed once per session.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.## Warning: The `size` argument of `element_line()` is deprecated as of ggplot2 3.4.0.
## ℹ Please use the `linewidth` argument instead.
## ℹ The deprecated feature was likely used in the UpSetR package.
## Please report the issue to the authors.
## This warning is displayed once per session.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
vis_miss(ogrenci) + theme(axis.text.x = element_text(angle=80))
gg_miss_upset(ogrenci)
#MCAR Testi
library(naniar)
mcar_test(data = ogrenci[,c(1,2,3,4,5)])## # A tibble: 1 × 4
## statistic df p.value missing.patterns
## <dbl> <dbl> <dbl> <int>
## 1 36.1 32 0.283 13Kayıp Veriyle Baş Etme Yöntemleri
Veri Silmeye Dayalı Yöntemler Liste Bazında Silme
na.omit(ogrenci)## # A tibble: 4,332 × 19
## BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 1 2 2 1 1 1 1 1
## 2 1 2 1 1 2 4 4 4 4
## 3 2 2 3 1 2 3 4 2 4
## 4 2 1 2 4 1 1 1 1 2
## 5 1 2 1 1 3 4 4 4 4
## 6 2 1 4 4 1 1 1 1 1
## 7 2 1 4 3 1 1 1 2 2
## 8 2 1 4 4 1 1 2 2 2
## 9 2 3 2 3 3 2 4 4 3
## 10 1 3 2 3 2 2 2 2 3
## # ℹ 4,322 more rows
## # ℹ 10 more variables: BSBM19I <dbl>, BSBM22A <dbl>, BSBM22B <dbl>,
## # BSBM22C <dbl>, BSBM22D <dbl>, BSBM22E <dbl>, BSBM22F <dbl>, BSBM22G <dbl>,
## # BSBM22H <dbl>, BSMMAT01 <dbl>Veri Atamaya Dayalı Yöntemler Ortalama İle Atama
ogrenci3 <- ogrenci
ogrenci3$BSBM22F[is.na(ogrenci3$BSBM22F)] <- mean(ogrenci3$BSBM22F, na.rm=TRUE)
summary(ogrenci3$BSBM22F)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.00 2.00 3.00 2.65 4.00 4.00sd(ogrenci$BSBM22F, na.rm=TRUE)## [1] 1.118752sd(ogrenci3$BSBM22F)## [1] 1.093125Döngü ile ortalama atama birden fazla değişken için kayıp değerleri ortalamayla doldurur.
ogrenci4 <- ogrenci[,1:5]
for(i in 1:ncol(ogrenci4)){ogrenci4[,i][is.na(ogrenci4[,i])] <- mean(ogrenci4[,i],na.rm=TRUE)
}
any_na(ogrenci4)## [1] FALSEapply ailesi ile benzer bir ilişki eklendi.
ogrenci9 <- ogrenci[, 1:5]
ogrenci9 <- apply(ogrenci9, 2, function(x) {
x[is.na(x)] <- mean(x, na.rm = TRUE)
return(x)
})
any_na(ogrenci9)## [1] FALSEtransform fonksiyonu ile atama transform fonksiyonunu kullanarak kayıp değerleri ortalamayla dolduruldu.
ogrenci10 <- ogrenci
ogrenci10 <- transform(ogrenci10,
BSBM22F = ifelse(is.na(BSBM22F),
mean(BSBM22F, na.rm = TRUE),
BSBM22F))
summary(ogrenci10)## BSBG01 BSBM19A BSBM19B BSBM19C
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000
## Median :2.000 Median :2.000 Median :2.000 Median :2.000
## Mean :1.506 Mean :2.184 Mean :2.427 Mean :2.449
## 3rd Qu.:2.000 3rd Qu.:3.000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :2.000 Max. :4.000 Max. :4.000 Max. :4.000
## NA's :80 NA's :130 NA's :155 NA's :152
## BSBM19D BSBM19E BSBM19F BSBM19G
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000
## Median :2.000 Median :2.000 Median :2.000 Median :2.000
## Mean :2.071 Mean :2.298 Mean :2.416 Mean :2.421
## 3rd Qu.:3.000 3rd Qu.:3.000 3rd Qu.:3.000 3rd Qu.:4.000
## Max. :4.000 Max. :4.000 Max. :4.000 Max. :4.000
## NA's :167 NA's :190 NA's :168 NA's :160
## BSBM19H BSBM19I BSBM22A BSBM22B
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:2.000 1st Qu.:1.000 1st Qu.:2.000 1st Qu.:1.000
## Median :3.000 Median :3.000 Median :2.000 Median :2.000
## Mean :2.916 Mean :2.671 Mean :2.403 Mean :2.507
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:3.000 3rd Qu.:4.000
## Max. :4.000 Max. :4.000 Max. :4.000 Max. :4.000
## NA's :161 NA's :157 NA's :169 NA's :212
## BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.00 Min. :1.000
## 1st Qu.:1.000 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.00 1st Qu.:1.000
## Median :2.000 Median :3.000 Median :3.000 Median :3.00 Median :2.000
## Mean :2.408 Mean :2.683 Mean :2.844 Mean :2.65 Mean :2.282
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.00 3rd Qu.:4.000
## Max. :4.000 Max. :4.000 Max. :4.000 Max. :4.00 Max. :4.000
## NA's :197 NA's :194 NA's :210 NA's :185
## BSBM22H BSMMAT01
## Min. :1.000 Min. :216.0
## 1st Qu.:1.000 1st Qu.:420.2
## Median :2.000 Median :502.9
## Mean :2.198 Mean :504.2
## 3rd Qu.:3.000 3rd Qu.:587.3
## Max. :4.000 Max. :851.1
## NA's :190Model Tabanlı Yöntemler
EM Algoritması
library(mvdalab)## Warning: package 'mvdalab' was built under R version 4.4.3##
## Attaching package: 'mvdalab'## The following object is masked from 'package:psych':
##
## smcdat <- introNAs(iris, percent=25)
dat_EM <- imputeEM(dat)
dat_EM
## Sepal.Length Sepal.Width Petal.Length Petal.Width Speciessetosa
## 1 5.100000 3.500000 1.520826 0.27670583 1.0000000000
## 2 4.900000 3.000000 1.709335 0.34299654 1.0000000000
## 3 4.700000 3.200000 1.308565 0.15736055 0.8768217413
## 4 4.600000 3.100000 1.405555 0.21480344 1.0000000000
## 5 4.951589 3.600000 1.334307 0.20000000 1.0000000000
## 6 5.400000 3.474823 1.700000 0.37590104 1.0000000000
## 7 4.600000 3.488430 1.262484 0.30000000 1.0000000000
## 8 5.000000 3.294617 1.500000 0.20000000 0.8773023117
## 9 4.400000 3.499385 1.078859 0.20000000 1.0000000000
## 10 4.900000 3.100000 1.500000 0.10000000 1.0000000000
## 11 5.400000 3.700000 1.500000 0.31006888 1.0000000000
## 12 4.800000 3.485112 1.600000 0.20000000 1.0000000000
## 13 4.800000 3.000000 1.400000 0.10000000 1.0000000000
## 14 4.300000 3.000000 1.100000 0.10000000 1.0000000000
## 15 5.800000 4.000000 1.200000 0.31516867 1.0000000000
## 16 5.700000 4.400000 1.474696 0.40000000 1.0000000000
## 17 5.400000 3.470609 1.784498 0.40000000 1.0000000000
## 18 5.100000 3.489664 1.400000 0.26377149 1.0000000000
## 19 5.700000 3.800000 1.716354 0.30000000 1.0000000000
## 20 5.100000 3.800000 1.500000 0.30000000 1.0000000000
## 21 5.400000 3.400000 1.700000 0.20000000 1.0000000000
## 22 5.032647 3.700000 1.500000 0.40000000 1.0000000000
## 23 4.799616 3.236945 1.425246 0.20000000 0.8720782952
## 24 5.100000 3.300000 1.700000 0.50000000 1.0000000000
## 25 4.800000 3.400000 1.900000 0.20000000 1.0000000000
## 26 5.000000 3.486522 1.600000 0.20000000 1.0000000000
## 27 5.000000 3.400000 1.600000 0.28047700 1.0000000000
## 28 5.200000 3.484717 1.500000 0.30114801 1.0000000000
## 29 5.200000 3.390944 1.400000 0.20000000 0.9159399163
## 30 4.700000 3.200000 1.414808 0.22182794 1.0000000000
## 31 4.800000 3.100000 1.600000 0.20000000 1.0000000000
## 32 5.029532 3.400000 1.500000 0.40000000 0.9088594928
## 33 5.200000 4.100000 1.500000 0.10000000 1.3505877259
## 34 5.500000 4.200000 1.400000 0.20000000 1.0000000000
## 35 4.900000 3.100000 1.500000 0.20000000 1.0000000000
## 36 5.000000 3.200000 1.649583 0.32324114 1.0000000000
## 37 5.500000 3.499881 1.300000 0.20000000 1.0000000000
## 38 4.900000 3.600000 1.239817 0.10000000 1.0000000000
## 39 4.400000 3.000000 1.335315 0.20000000 1.0000000000
## 40 5.100000 3.400000 1.500000 0.20000000 1.0000000000
## 41 5.000000 3.494611 1.300000 0.22639498 1.0000000000
## 42 4.500000 2.300000 1.300000 0.24376306 0.3624850302
## 43 4.400000 3.499676 1.300000 0.08011218 1.0000000000
## 44 5.000000 3.461130 1.600000 0.60000000 1.0000000000
## 45 5.100000 3.800000 1.900000 0.26803049 1.0000000000
## 46 4.974130 3.000000 1.400000 0.30000000 1.0000000000
## 47 5.100000 3.491376 1.473645 0.20000000 1.0000000000
## 48 4.600000 3.493884 1.400000 0.14186916 1.0000000000
## 49 5.300000 3.700000 1.500000 0.35526087 1.0666787554
## 50 5.000000 3.300000 1.400000 0.28250265 0.8820524816
## 51 7.000000 3.200000 4.700000 1.40000000 0.0000000000
## 52 6.400000 3.200000 4.500000 1.50000000 0.2445708372
## 53 5.881999 3.100000 4.900000 1.50000000 0.0000000000
## 54 5.500000 2.300000 4.000000 1.32716791 0.0000000000
## 55 6.500000 2.800000 4.605439 1.50000000 0.0000000000
## 56 5.700000 2.800000 4.500000 1.34508498 0.0000000000
## 57 5.891272 3.300000 4.700000 1.60000000 0.0000000000
## 58 4.900000 2.400000 3.300000 1.00000000 0.0000000000
## 59 6.061995 2.999957 4.600000 1.30000000 0.1859905719
## 60 5.200000 2.597233 3.900000 1.40000000 0.0000000000
## 61 5.000000 2.000000 3.500000 1.00000000 0.0000000000
## 62 5.798961 2.581016 4.327985 1.50000000 0.0000000000
## 63 6.000000 2.200000 4.302429 1.00000000 0.0000000000
## 64 6.100000 2.900000 4.493436 1.51538202 0.0948097276
## 65 5.600000 2.619928 3.600000 1.24382140 0.0000000000
## 66 6.700000 3.100000 4.400000 1.52001796 0.0000000000
## 67 5.600000 2.574030 4.500000 1.50000000 0.0000000000
## 68 5.800000 2.700000 3.934101 1.00000000 0.0000000000
## 69 6.200000 2.200000 4.500000 1.57631481 0.0000000000
## 70 5.600000 2.618015 3.931498 1.10000000 0.0000000000
## 71 5.919956 2.553632 4.608681 1.80000000 0.0000000000
## 72 6.100000 2.800000 4.000000 1.38074879 0.0000000000
## 73 6.300000 2.500000 4.900000 1.50000000 0.0000000000
## 74 6.100000 2.800000 4.700000 1.20000000 0.0000000000
## 75 6.400000 3.195078 4.300000 1.30000000 0.2796762885
## 76 6.600000 2.590703 4.400000 1.40000000 0.0000000000
## 77 6.800000 2.560563 4.800000 1.69233960 0.0000000000
## 78 6.700000 3.000000 4.747181 1.70000000 0.0000000000
## 79 6.000000 2.962956 4.500000 1.50000000 0.1479981151
## 80 5.700000 2.623187 3.500000 1.25520582 0.0000000000
## 81 5.500000 2.400000 3.987160 1.10000000 0.0000000000
## 82 5.500000 2.631296 3.700000 1.00000000 0.0000000000
## 83 5.800000 2.700000 3.900000 1.31418423 0.0000000000
## 84 6.000000 2.700000 5.100000 1.60000000 0.0000000000
## 85 5.400000 3.000000 4.500000 1.50000000 0.0000000000
## 86 6.000000 3.400000 4.084785 1.60000000 0.0000000000
## 87 6.700000 3.100000 4.700000 1.50000000 0.0000000000
## 88 6.300000 3.091276 4.400000 1.54653448 0.1854749229
## 89 5.600000 3.000000 4.100000 1.23517318 0.0000000000
## 90 5.500000 2.500000 4.068650 1.30000000 0.0000000000
## 91 5.500000 2.600000 3.950886 1.20000000 0.0000000000
## 92 5.813531 3.000000 4.600000 1.40000000 0.0000000000
## 93 5.613449 2.600000 4.000000 1.20000000 0.0569869579
## 94 5.000000 2.300000 3.300000 1.00000000 0.0264753015
## 95 5.600000 2.700000 4.200000 1.30000000 0.0000000000
## 96 5.700000 3.000000 4.200000 1.27164274 0.0000000000
## 97 5.700000 2.900000 4.200000 1.30000000 0.0000000000
## 98 6.200000 2.900000 4.300000 1.30000000 0.0000000000
## 99 5.100000 2.500000 3.000000 1.10000000 0.1405247016
## 100 5.700000 2.599536 4.129555 1.30000000 0.0000000000
## 101 6.300000 3.204900 5.220146 1.86007167 0.0000000000
## 102 5.800000 2.794197 4.708188 1.90000000 -0.0013968998
## 103 7.100000 3.000000 5.900000 2.10000000 0.0000000000
## 104 6.300000 3.196461 5.600000 1.80000000 0.0000000000
## 105 6.500000 3.000000 5.800000 2.20000000 -0.1059123414
## 106 6.914058 2.837382 6.600000 2.10000000 -0.2791229707
## 107 4.900000 2.625993 3.695978 1.70000000 0.1135900833
## 108 7.300000 2.900000 6.300000 1.80000000 -0.2020630674
## 109 6.700000 2.500000 5.764566 1.80000000 0.0000000000
## 110 7.200000 3.600000 6.100000 2.50000000 0.0000000000
## 111 6.500000 3.200000 5.100000 2.00000000 0.0000000000
## 112 6.815004 3.195852 5.536391 1.90000000 0.0000000000
## 113 6.800000 3.000000 5.500000 2.10000000 -0.0894708344
## 114 5.700000 2.664122 5.000000 2.00000000 -0.1028529977
## 115 7.072375 2.873360 6.492772 2.40000000 -0.3142250141
## 116 6.400000 3.165879 5.586610 2.30000000 0.0000000000
## 117 6.564927 3.000000 5.500000 1.80000000 -0.0179673779
## 118 7.700000 3.800000 6.700000 2.20000000 0.0000000000
## 119 7.700000 3.131961 6.900000 2.30000000 0.0000000000
## 120 6.000000 3.233064 5.000000 1.50000000 0.0000000000
## 121 6.900000 3.200000 5.700000 2.06506123 0.0000000000
## 122 5.600000 2.800000 4.900000 2.00000000 0.0000000000
## 123 7.700000 2.800000 6.301355 2.00000000 0.0000000000
## 124 6.708280 3.222278 4.900000 1.80000000 0.0000000000
## 125 6.700000 3.300000 5.700000 2.10000000 0.0000000000
## 126 7.200000 3.200000 6.000000 1.80000000 0.0038358310
## 127 6.200000 2.800000 4.800000 1.80000000 0.0000000000
## 128 6.100000 3.000000 4.900000 1.80000000 0.0000000000
## 129 6.400000 2.800000 5.600000 2.10000000 0.0000000000
## 130 7.200000 3.173600 5.800000 2.15463768 0.0000000000
## 131 7.400000 2.800000 6.100000 1.90000000 -0.2693038252
## 132 7.900000 3.143074 6.400000 2.40327725 0.0000000000
## 133 6.400000 2.800000 5.600000 2.20000000 0.0000000000
## 134 6.419291 2.942973 5.100000 1.77638294 -0.0003704196
## 135 6.100000 2.600000 5.112753 1.40000000 0.0000000000
## 136 7.700000 3.158192 6.100000 2.30000000 0.0000000000
## 137 6.300000 3.158374 5.600000 2.40000000 0.0000000000
## 138 6.400000 3.100000 5.500000 1.93780359 0.0000000000
## 139 6.000000 3.000000 4.800000 1.80000000 0.0000000000
## 140 6.900000 3.188203 5.400000 2.10000000 0.0000000000
## 141 6.700000 3.100000 5.606551 2.02378289 0.0000000000
## 142 6.900000 3.100000 5.100000 2.30000000 0.0000000000
## 143 5.800000 2.700000 5.100000 1.90000000 0.0000000000
## 144 6.800000 2.904064 5.900000 2.30000000 -0.2076265561
## 145 6.883000 3.180403 5.700000 2.06410151 0.0000000000
## 146 6.700000 3.180655 5.200000 2.30000000 0.0000000000
## 147 6.731911 2.500000 5.000000 1.90000000 0.0000000000
## 148 6.500000 3.204127 5.200000 1.90599812 0.0000000000
## 149 6.200000 3.400000 5.355546 2.30000000 0.0000000000
## 150 5.900000 2.768101 5.100000 1.80000000 -0.0423194546
## Speciesversicolor Speciesvirginica
## 1 0.00000000 0.000000000
## 2 0.00000000 0.000000000
## 3 0.42831020 -0.305131944
## 4 0.00000000 0.000000000
## 5 0.00000000 0.000000000
## 6 0.00000000 0.000000000
## 7 0.00000000 0.000000000
## 8 0.26834924 -0.145651552
## 9 0.00000000 0.000000000
## 10 0.00000000 0.000000000
## 11 0.00000000 0.000000000
## 12 0.00000000 0.000000000
## 13 0.00000000 0.000000000
## 14 0.00000000 0.000000000
## 15 0.00000000 0.000000000
## 16 0.00000000 0.000000000
## 17 0.00000000 0.000000000
## 18 0.00000000 0.000000000
## 19 0.00000000 0.000000000
## 20 0.00000000 0.000000000
## 21 0.00000000 0.000000000
## 22 0.00000000 0.000000000
## 23 0.36402686 -0.236105160
## 24 0.00000000 0.000000000
## 25 0.00000000 0.000000000
## 26 0.00000000 0.000000000
## 27 0.00000000 0.000000000
## 28 0.00000000 0.000000000
## 29 0.12432867 -0.040268588
## 30 0.00000000 0.000000000
## 31 0.00000000 0.000000000
## 32 0.10107791 -0.009937403
## 33 -0.83305008 0.482462356
## 34 0.00000000 0.000000000
## 35 0.00000000 0.000000000
## 36 0.00000000 0.000000000
## 37 0.00000000 0.000000000
## 38 0.00000000 0.000000000
## 39 0.00000000 0.000000000
## 40 0.00000000 0.000000000
## 41 0.00000000 0.000000000
## 42 1.63416888 -0.996653906
## 43 0.00000000 0.000000000
## 44 0.00000000 0.000000000
## 45 0.00000000 0.000000000
## 46 0.00000000 0.000000000
## 47 0.00000000 0.000000000
## 48 0.00000000 0.000000000
## 49 -0.34153127 0.274852514
## 50 0.23796618 -0.120018657
## 51 1.00000000 0.000000000
## 52 0.07948692 0.675942242
## 53 1.00000000 0.000000000
## 54 1.00000000 0.000000000
## 55 1.00000000 0.000000000
## 56 1.00000000 0.000000000
## 57 1.00000000 0.000000000
## 58 1.00000000 0.000000000
## 59 0.40637330 0.407636124
## 60 1.00000000 0.000000000
## 61 1.00000000 0.000000000
## 62 1.00000000 0.000000000
## 63 1.00000000 0.000000000
## 64 0.52834296 0.376847312
## 65 1.00000000 0.000000000
## 66 1.00000000 0.000000000
## 67 1.00000000 0.000000000
## 68 1.00000000 0.000000000
## 69 1.00000000 0.000000000
## 70 1.00000000 0.000000000
## 71 1.00000000 0.000000000
## 72 1.00000000 0.000000000
## 73 1.00000000 0.000000000
## 74 1.00000000 0.000000000
## 75 0.12278607 0.597537643
## 76 1.00000000 0.000000000
## 77 1.00000000 0.000000000
## 78 1.00000000 0.000000000
## 79 0.44947308 0.402528809
## 80 1.00000000 0.000000000
## 81 1.00000000 0.000000000
## 82 1.00000000 0.000000000
## 83 1.00000000 0.000000000
## 84 1.00000000 0.000000000
## 85 1.00000000 0.000000000
## 86 1.00000000 0.000000000
## 87 1.00000000 0.000000000
## 88 0.25023482 0.564290257
## 89 1.00000000 0.000000000
## 90 1.00000000 0.000000000
## 91 1.00000000 0.000000000
## 92 1.00000000 0.000000000
## 93 1.01516425 -0.072151207
## 94 1.52978117 -0.556256467
## 95 1.00000000 0.000000000
## 96 1.00000000 0.000000000
## 97 1.00000000 0.000000000
## 98 1.00000000 0.000000000
## 99 1.24633073 -0.386855435
## 100 1.00000000 0.000000000
## 101 0.00000000 1.000000000
## 102 0.65865902 0.342737878
## 103 0.00000000 1.000000000
## 104 0.00000000 1.000000000
## 105 0.31129165 0.794620690
## 106 0.43834996 0.840773006
## 107 1.00645054 -0.120040625
## 108 0.29235848 0.909704584
## 109 0.00000000 1.000000000
## 110 0.00000000 1.000000000
## 111 0.00000000 1.000000000
## 112 0.00000000 1.000000000
## 113 0.25113256 0.838338275
## 114 0.82712146 0.275731541
## 115 0.35841256 0.955812454
## 116 0.00000000 1.000000000
## 117 0.30714114 0.710826238
## 118 0.00000000 1.000000000
## 119 0.00000000 1.000000000
## 120 0.00000000 1.000000000
## 121 0.00000000 1.000000000
## 122 0.00000000 1.000000000
## 123 0.00000000 1.000000000
## 124 0.00000000 1.000000000
## 125 0.00000000 1.000000000
## 126 -0.07804064 1.074204809
## 127 0.00000000 1.000000000
## 128 0.00000000 1.000000000
## 129 0.00000000 1.000000000
## 130 0.00000000 1.000000000
## 131 0.39805490 0.871248927
## 132 0.00000000 1.000000000
## 133 0.00000000 1.000000000
## 134 0.40526481 0.595105612
## 135 0.00000000 1.000000000
## 136 0.00000000 1.000000000
## 137 0.00000000 1.000000000
## 138 0.00000000 1.000000000
## 139 0.00000000 1.000000000
## 140 0.00000000 1.000000000
## 141 0.00000000 1.000000000
## 142 0.00000000 1.000000000
## 143 0.00000000 1.000000000
## 144 0.36227466 0.845351891
## 145 0.00000000 1.000000000
## 146 0.00000000 1.000000000
## 147 0.00000000 1.000000000
## 148 0.00000000 1.000000000
## 149 0.00000000 1.000000000
## 150 0.68159950 0.360719950EM Algoritması Sonuçları
missMethods Paketi ile EM Algoritması
library(missMethods)## Warning: package 'missMethods' was built under R version 4.4.3##
## Attaching package: 'missMethods'## The following objects are masked from 'package:naniar':
##
## impute_mean, impute_median, impute_modelibrary(mvtnorm)## Warning: package 'mvtnorm' was built under R version 4.4.3#Örnek veri seti oluşturma
ds_orig <- mvtnorm::rmvnorm(100, rep(0,7))
ds_mis <- delete_MCAR(ds_orig, p=0.2)
# EM ile eksik verileri doldurma (stokastik olmadan)
ds_imp <- impute_EM(ds_mis,stochastic=FALSE)
# EM ile eksik verileri doldurma (stokastik olarak)
ds_imp_stochastic <- impute_EM(ds_mis, stochastic=TRUE)Multiple Imputation (Çoklu atama)
library(mice)## Warning: package 'mice' was built under R version 4.4.3##
## Attaching package: 'mice'## The following object is masked from 'package:stats':
##
## filter## The following objects are masked from 'package:base':
##
## cbind, rbindEksik Verileri Gsörselleştirme
md.pattern(ogrenci)
## BSMMAT01 BSBG01 BSBM19A BSBM19C BSBM19B BSBM19I BSBM19G BSBM19H BSBM19D
## 4332 1 1 1 1 1 1 1 1 1
## 34 1 1 1 1 1 1 1 1 1
## 31 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 26 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 18 1 1 1 1 1 1 1 1 1
## 2 1 1 1 1 1 1 1 1 1
## 13 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 13 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 40 1 1 1 1 1 1 1 1 1
## 4 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 2 1 1 1 1 1 1 1 1 1
## 6 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 2 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 47 1 1 1 1 1 1 1 1 1
## 3 1 1 1 1 1 1 1 1 1
## 25 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 31 1 1 1 1 1 1 1 1 0
## 1 1 1 1 1 1 1 1 1 0
## 1 1 1 1 1 1 1 1 1 0
## 1 1 1 1 1 1 1 1 1 0
## 2 1 1 1 1 1 1 1 1 0
## 19 1 1 1 1 1 1 1 0 1
## 1 1 1 1 1 1 1 1 0 1
## 1 1 1 1 1 1 1 1 0 0
## 1 1 1 1 1 1 1 1 0 0
## 18 1 1 1 1 1 1 0 1 1
## 1 1 1 1 1 1 1 0 1 1
## 1 1 1 1 1 1 1 0 1 1
## 1 1 1 1 1 1 1 0 1 1
## 1 1 1 1 1 1 1 0 1 1
## 1 1 1 1 1 1 1 0 1 1
## 1 1 1 1 1 1 1 0 1 1
## 1 1 1 1 1 1 1 0 1 1
## 1 1 1 1 1 1 1 0 0 1
## 1 1 1 1 1 1 1 0 0 1
## 19 1 1 1 1 1 0 1 1 1
## 1 1 1 1 1 1 0 1 1 1
## 1 1 1 1 1 1 0 1 0 1
## 1 1 1 1 1 1 0 1 0 1
## 1 1 1 1 1 1 0 0 1 1
## 1 1 1 1 1 1 0 0 0 1
## 1 1 1 1 1 1 0 0 0 1
## 1 1 1 1 1 1 0 0 0 1
## 1 1 1 1 1 1 0 0 0 1
## 1 1 1 1 1 1 0 0 0 0
## 22 1 1 1 1 0 1 1 1 1
## 1 1 1 1 1 0 1 1 1 1
## 1 1 1 1 1 0 1 1 1 1
## 1 1 1 1 1 0 1 1 1 1
## 1 1 1 1 1 0 1 1 1 1
## 1 1 1 1 1 0 1 1 0 1
## 1 1 1 1 1 0 1 1 0 1
## 1 1 1 1 1 0 0 1 1 1
## 1 1 1 1 1 0 0 0 0 0
## 19 1 1 1 0 1 1 1 1 1
## 1 1 1 1 0 1 1 1 1 1
## 1 1 1 1 0 1 1 1 1 1
## 1 1 1 1 0 1 1 1 1 1
## 1 1 1 1 0 1 1 1 1 1
## 1 1 1 1 0 1 1 1 1 0
## 1 1 1 1 0 1 1 1 0 1
## 1 1 1 1 0 1 1 1 0 0
## 1 1 1 1 0 1 0 1 1 1
## 1 1 1 1 0 0 0 0 1 1
## 3 1 1 1 0 0 0 0 0 0
## 1 1 1 1 0 0 0 0 0 0
## 1 1 1 1 0 0 0 0 0 0
## 7 1 1 0 1 1 1 1 1 1
## 1 1 1 0 1 1 1 1 1 1
## 1 1 1 0 1 1 1 1 1 1
## 1 1 1 0 1 1 1 1 1 1
## 1 1 1 0 1 0 0 0 0 0
## 1 1 1 0 0 1 0 0 0 0
## 13 1 1 0 0 0 0 0 0 0
## 1 1 1 0 0 0 0 0 0 0
## 1 1 1 0 0 0 0 0 0 0
## 1 1 1 0 0 0 0 0 0 0
## 1 1 1 0 0 0 0 0 0 0
## 21 1 1 0 0 0 0 0 0 0
## 80 1 0 0 0 0 0 0 0 0
## 0 80 130 152 155 157 160 161 167
## BSBM19F BSBM22A BSBM22G BSBM19E BSBM22H BSBM22D BSBM22C BSBM22E BSBM22B
## 4332 1 1 1 1 1 1 1 1 1
## 34 1 1 1 1 1 1 1 1 1
## 31 1 1 1 1 1 1 1 1 0
## 1 1 1 1 1 1 1 1 1 0
## 26 1 1 1 1 1 1 1 0 1
## 1 1 1 1 1 1 1 1 0 0
## 18 1 1 1 1 1 1 0 1 1
## 2 1 1 1 1 1 1 0 1 1
## 13 1 1 1 1 1 0 1 1 1
## 1 1 1 1 1 1 0 1 1 1
## 1 1 1 1 1 1 0 1 1 0
## 1 1 1 1 1 1 0 1 0 1
## 1 1 1 1 1 1 0 0 1 1
## 13 1 1 1 1 0 1 1 1 1
## 1 1 1 1 1 0 1 1 1 1
## 1 1 1 1 1 0 1 1 1 0
## 1 1 1 1 1 0 1 1 0 1
## 40 1 1 1 0 1 1 1 1 1
## 4 1 1 1 0 1 1 1 1 1
## 1 1 1 1 0 1 1 1 1 0
## 1 1 1 1 0 1 1 1 0 1
## 2 1 1 1 0 1 0 1 1 1
## 6 1 1 0 1 1 1 1 1 1
## 1 1 1 0 1 1 0 0 0 0
## 1 1 1 0 1 0 1 1 1 1
## 1 1 1 0 1 0 1 1 0 1
## 1 1 1 0 1 0 0 1 0 1
## 1 1 1 0 1 0 0 0 0 1
## 1 1 1 0 0 1 1 1 1 1
## 2 1 0 1 1 1 1 1 1 1
## 1 1 0 1 1 1 1 0 1 1
## 1 1 0 1 1 1 1 0 1 0
## 47 1 0 0 1 0 0 0 0 0
## 3 1 0 0 0 0 0 0 0 0
## 25 0 1 1 1 1 1 1 1 1
## 1 0 1 1 1 1 0 1 1 1
## 1 0 0 0 0 0 0 0 0 0
## 31 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 0 0
## 1 1 1 1 1 1 1 0 1 1
## 1 1 1 1 0 1 0 1 1 1
## 2 0 1 1 1 1 1 1 1 1
## 19 1 1 1 1 1 1 1 1 1
## 1 1 0 0 1 0 0 0 0 0
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 0 1
## 18 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 0 1
## 1 1 1 1 1 1 1 0 1 1
## 1 1 1 1 1 1 0 1 1 0
## 1 1 1 1 0 1 1 1 1 1
## 1 1 1 0 1 1 1 1 1 1
## 1 1 1 0 0 1 1 1 1 1
## 1 0 1 1 1 1 1 1 1 1
## 1 0 1 1 1 1 1 1 1 1
## 19 1 1 1 1 1 1 1 1 1
## 1 0 1 1 1 1 1 1 1 1
## 1 1 0 0 1 0 0 0 0 0
## 1 0 1 1 1 1 0 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 0 1 1 1 1 1 1 1 0
## 1 0 1 0 1 0 1 1 0 1
## 1 0 0 0 1 0 0 0 0 0
## 1 0 1 1 0 1 1 1 1 1
## 22 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 0 1
## 1 1 1 1 1 1 1 0 1 1
## 1 1 1 1 0 1 1 1 1 1
## 1 0 1 1 1 1 1 1 1 1
## 1 1 1 1 0 1 1 1 1 1
## 1 1 0 0 0 0 0 0 0 0
## 1 0 1 1 0 1 1 1 1 1
## 1 0 0 0 0 1 0 0 0 0
## 19 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 0 0 1
## 1 1 1 1 0 1 1 1 1 1
## 1 1 0 0 1 0 0 0 0 0
## 1 0 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 0 0 0 0 0 0 0 0
## 1 0 0 0 1 1 1 1 1 0
## 1 1 1 1 1 1 1 1 1 1
## 1 0 1 1 0 1 0 0 1 0
## 3 0 1 0 0 0 0 0 0 0
## 1 0 0 0 0 0 1 0 0 0
## 1 0 0 0 0 0 0 1 0 0
## 7 1 1 1 1 1 1 1 1 1
## 1 1 1 1 1 1 1 1 1 1
## 1 1 0 0 1 0 0 0 0 0
## 1 0 1 1 1 1 1 1 1 1
## 1 0 1 0 0 0 0 0 0 0
## 1 1 0 0 0 0 0 1 0 0
## 13 0 1 1 0 1 1 1 1 1
## 1 0 1 1 0 1 1 1 1 1
## 1 0 1 0 0 0 1 0 0 1
## 1 0 1 0 0 0 0 0 0 0
## 1 0 0 1 0 0 1 1 0 0
## 21 0 0 0 0 0 0 0 0 0
## 80 0 0 0 0 0 0 0 0 0
## 168 169 185 190 190 194 197 210 212
## BSBM22F
## 4332 1 0
## 34 0 1
## 31 1 1
## 1 0 2
## 26 1 1
## 1 1 2
## 18 1 1
## 2 0 2
## 13 1 1
## 1 0 2
## 1 1 2
## 1 1 2
## 1 1 2
## 13 1 1
## 1 0 2
## 1 1 2
## 1 1 2
## 40 1 1
## 4 0 2
## 1 1 2
## 1 1 2
## 2 1 2
## 6 1 1
## 1 0 6
## 1 0 3
## 1 0 4
## 1 0 5
## 1 0 6
## 1 1 2
## 2 1 1
## 1 1 2
## 1 1 3
## 47 0 8
## 3 0 9
## 25 1 1
## 1 1 2
## 1 0 10
## 31 1 1
## 1 1 3
## 1 1 2
## 1 1 3
## 2 1 2
## 19 1 1
## 1 0 9
## 1 1 2
## 1 1 3
## 18 1 1
## 1 0 2
## 1 1 2
## 1 1 2
## 1 1 3
## 1 1 2
## 1 1 2
## 1 1 3
## 1 1 3
## 1 0 4
## 19 1 1
## 1 1 2
## 1 0 10
## 1 1 4
## 1 1 2
## 1 1 3
## 1 1 5
## 1 0 8
## 1 0 12
## 1 1 6
## 22 1 1
## 1 1 2
## 1 1 2
## 1 1 2
## 1 1 2
## 1 1 3
## 1 0 11
## 1 1 4
## 1 1 13
## 19 1 1
## 1 0 4
## 1 1 2
## 1 0 9
## 1 1 2
## 1 1 2
## 1 0 11
## 1 0 8
## 1 1 2
## 1 1 9
## 3 0 15
## 1 0 15
## 1 0 15
## 7 1 1
## 1 0 2
## 1 0 9
## 1 1 2
## 1 0 15
## 1 0 14
## 13 1 9
## 1 0 10
## 1 0 14
## 1 0 16
## 1 1 13
## 21 0 17
## 80 0 18
## 223 3100imputed_data <- mice(ogrenci, m=5, maxit=50, method='pmm', seed=500)##
## iter imp variable
## 1 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 1 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 1 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 1 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 1 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 2 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 2 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 2 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 2 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 2 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 3 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 3 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 3 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 3 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 3 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 4 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 4 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 4 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 4 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 4 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 5 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 5 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 5 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 5 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 5 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 6 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 6 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 6 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 6 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 6 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 7 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 7 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 7 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 7 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 7 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 8 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 8 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 8 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 8 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 8 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 9 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 9 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 9 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 9 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 9 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 10 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 10 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 10 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 10 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 10 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 11 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 11 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 11 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 11 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 11 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 12 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 12 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 12 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 12 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 12 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 13 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 13 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 13 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 13 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 13 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 14 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 14 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 14 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 14 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 14 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 15 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 15 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 15 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 15 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 15 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 16 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 16 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 16 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 16 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 16 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 17 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 17 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 17 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 17 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 17 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 18 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 18 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 18 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 18 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 18 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 19 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 19 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 19 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 19 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 19 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 20 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 20 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 20 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 20 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 20 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 21 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 21 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 21 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 21 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 21 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 22 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 22 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 22 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 22 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 22 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 23 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 23 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 23 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 23 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 23 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 24 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 24 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 24 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 24 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 24 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 25 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 25 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 25 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 25 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 25 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 26 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 26 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 26 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 26 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 26 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 27 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 27 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 27 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 27 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 27 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 28 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 28 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 28 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 28 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 28 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 29 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 29 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 29 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 29 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 29 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 30 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 30 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 30 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 30 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 30 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 31 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 31 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 31 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 31 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 31 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 32 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 32 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 32 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 32 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 32 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 33 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 33 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 33 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 33 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 33 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 34 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 34 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 34 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 34 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 34 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 35 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 35 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 35 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 35 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 35 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 36 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 36 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 36 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 36 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 36 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 37 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 37 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 37 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 37 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 37 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 38 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 38 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 38 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 38 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 38 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 39 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 39 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 39 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 39 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 39 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 40 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 40 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 40 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 40 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 40 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 41 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 41 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 41 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 41 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 41 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 42 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 42 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 42 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 42 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 42 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 43 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 43 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 43 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 43 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 43 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 44 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 44 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 44 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 44 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 44 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 45 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 45 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 45 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 45 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 45 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 46 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 46 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 46 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 46 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 46 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 47 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 47 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 47 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 47 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 47 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 48 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 48 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 48 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 48 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 48 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 49 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 49 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 49 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 49 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 49 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 50 1 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 50 2 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 50 3 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 50 4 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22H
## 50 5 BSBG01 BSBM19A BSBM19B BSBM19C BSBM19D BSBM19E BSBM19F BSBM19G BSBM19H BSBM19I BSBM22A BSBM22B BSBM22C BSBM22D BSBM22E BSBM22F BSBM22G BSBM22Himputed_data$imp## $BSBG01
## 1 2 3 4 5
## 122 1 2 1 2 2
## 818 1 2 2 2 2
## 878 1 2 2 1 2
## 939 2 1 2 1 2
## 960 1 1 1 1 2
## 961 2 2 2 2 2
## 962 1 1 1 1 2
## 963 1 1 1 2 2
## 964 2 1 2 2 2
## 965 2 1 2 1 1
## 966 1 2 1 1 2
## 967 1 1 1 2 1
## 968 2 2 2 1 2
## 969 1 1 1 1 1
## 970 1 2 1 2 1
## 971 1 1 1 1 1
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## 973 2 1 1 1 1
## 974 2 1 1 2 2
## 975 1 2 1 2 1
## 976 1 1 2 2 2
## 977 2 2 2 1 1
## 978 1 2 2 1 2
## 979 2 1 2 2 1
## 980 2 2 2 2 2
## 981 1 2 1 2 1
## 982 2 2 1 2 1
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## 984 2 1 2 2 1
## 985 1 2 2 1 1
## 986 1 2 2 1 2
## 987 2 1 2 1 1
## 988 1 2 2 1 1
## 989 2 2 1 2 1
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## 991 1 2 2 1 1
## 992 1 2 1 1 1
## 993 1 1 1 1 2
## 994 2 2 1 1 1
## 995 1 2 1 2 1
## 996 2 2 2 1 2
## 997 2 2 2 1 2
## 998 1 1 1 2 1
## 999 2 1 1 1 1
## 1000 1 1 2 1 1
## 1001 1 1 2 1 2
## 1002 1 1 1 2 1
## 1003 2 1 1 2 1
## 1004 1 2 1 1 1
## 1005 1 2 2 2 1
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## 1008 2 2 2 1 1
## 1009 2 1 2 2 1
## 1010 1 2 1 2 2
## 1011 2 2 1 2 1
## 1012 2 2 1 2 1
## 1013 2 1 1 1 1
## 1014 1 2 2 1 2
## 1015 2 1 1 2 2
## 1016 2 2 1 2 2
## 1017 1 1 2 1 1
## 1018 2 2 2 1 1
## 1019 1 1 1 1 2
## 1020 1 2 2 1 1
## 1021 1 2 2 2 1
## 1022 2 2 2 1 2
## 1023 1 2 1 2 1
## 1024 2 1 2 2 1
## 1025 2 1 1 2 1
## 1710 2 1 2 1 1
## 2657 2 2 2 2 2
## 2670 2 2 1 2 2
## 2702 2 2 2 2 2
## 2714 1 2 1 1 1
## 2976 2 2 1 2 2
## 3459 1 1 2 1 1
## 3460 1 1 2 1 2
## 4357 2 2 1 2 1
## 4409 2 2 1 1 1
##
## $BSBM19A
## 1 2 3 4 5
## 110 2 2 1 1 1
## 122 3 2 2 2 3
## 198 1 1 1 1 1
## 214 4 2 4 3 1
## 251 2 1 2 1 2
## 362 2 3 3 2 3
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## 818 4 2 4 1 2
## 836 1 2 2 3 1
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## 963 3 2 3 2 4
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## 972 1 2 1 1 2
## 973 1 1 2 1 1
## 974 1 2 1 3 3
## 975 1 1 2 2 4
## 976 2 4 2 1 1
## 977 2 2 2 1 2
## 978 4 3 1 2 4
## 979 2 2 1 2 2
## 980 2 1 4 3 1
## 981 3 4 2 2 1
## 982 4 1 2 1 1
## 983 4 2 2 2 2
## 984 2 1 4 2 4
## 985 1 1 4 3 2
## 986 1 1 1 1 1
## 987 1 4 2 1 1
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## 989 2 4 1 2 1
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## 996 3 3 3 1 1
## 997 1 3 3 2 3
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## 1001 2 1 2 2 3
## 1002 4 2 1 1 1
## 1003 1 4 4 1 2
## 1004 1 3 1 2 1
## 1005 2 4 2 2 1
## 1006 2 3 1 2 1
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## 1008 2 3 1 2 2
## 1009 3 1 1 2 1
## 1010 1 2 1 1 4
## 1011 2 4 1 2 2
## 1012 2 3 4 3 1
## 1013 2 2 3 3 3
## 1014 2 2 2 2 3
## 1015 4 3 3 1 3
## 1016 2 2 4 1 1
## 1017 4 3 1 3 1
## 1018 1 2 4 1 2
## 1019 1 2 2 2 1
## 1020 2 2 2 3 3
## 1021 1 2 3 4 3
## 1022 1 1 4 2 1
## 1023 1 2 3 1 1
## 1024 4 2 2 1 1
## 1025 1 1 2 3 2
## 1033 4 4 2 4 2
## 1156 2 2 2 1 4
## 1158 2 1 3 1 4
## 1317 2 3 3 1 3
## 1464 2 4 4 4 4
## 1472 2 3 2 3 4
## 1710 3 3 1 1 4
## 1904 2 2 2 3 3
## 2022 1 2 2 1 2
## 2381 3 4 3 2 2
## 2657 1 1 1 1 2
## 2658 1 1 2 3 1
## 2670 2 4 2 1 1
## 2702 1 1 2 2 4
## 2714 3 2 1 4 2
## 2737 1 1 1 2 1
## 2759 2 4 4 2 2
## 2782 2 3 4 1 2
## 2813 1 1 2 1 1
## 2976 4 2 3 3 2
## 3062 4 2 1 2 2
## 3128 1 2 1 2 1
## 3304 2 4 3 1 3
## 3327 4 1 1 3 2
## 3340 3 3 4 4 4
## 3375 2 2 2 1 2
## 3448 1 3 1 3 2
## 3450 4 1 2 4 3
## 3459 2 1 1 1 3
## 3460 1 3 1 3 3
## 3467 1 1 1 2 1
## 3480 2 3 4 2 2
## 3534 2 4 2 3 4
## 3544 1 1 1 2 4
## 3865 4 3 3 2 3
## 3873 4 4 2 4 4
## 3879 2 4 3 3 1
## 3920 1 2 2 1 1
## 4081 1 1 1 1 1
## 4280 3 2 4 4 4
## 4281 3 4 4 4 1
## 4301 1 2 4 4 3
## 4340 4 2 2 3 4
## 4357 2 2 2 2 1
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## 4508 2 2 4 2 1
## 4523 3 3 3 2 4
## 4526 1 1 1 3 1
## 4590 2 2 3 3 1
## 4719 3 4 2 2 1
## 4810 4 3 1 1 3
##
## $BSBM19B
## 1 2 3 4 5
## 110 2 1 4 3 3
## 122 1 3 3 3 1
## 132 4 1 2 1 1
## 145 1 1 1 1 4
## 198 4 4 4 3 4
## 214 2 4 1 2 1
## 251 2 3 2 4 3
## 362 2 2 2 4 1
## 492 4 2 3 1 2
## 586 1 1 4 2 2
## 660 3 4 3 2 3
## 676 1 2 3 1 3
## 777 1 2 2 2 2
## 818 1 4 1 4 4
## 836 4 4 3 1 2
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## 873 1 2 1 1 1
## 878 2 1 2 1 2
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## 939 2 3 1 1 3
## 960 3 4 4 4 3
## 961 3 4 1 4 3
## 962 1 3 3 1 2
## 963 1 3 2 1 1
## 964 4 4 1 3 4
## 965 2 4 1 2 3
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## 967 1 4 4 3 2
## 968 2 3 4 3 3
## 969 2 1 3 3 4
## 970 2 4 1 1 1
## 971 4 4 1 4 3
## 972 4 3 4 2 3
## 973 4 1 2 4 4
## 974 2 3 3 4 2
## 975 4 1 4 2 1
## 976 2 2 4 3 4
## 977 1 4 1 1 1
## 978 1 3 3 4 1
## 979 4 3 4 1 3
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## 981 1 1 1 4 4
## 982 1 4 2 4 4
## 983 1 2 3 4 1
## 984 2 2 3 3 1
## 985 4 2 1 1 3
## 986 4 4 3 3 4
## 987 4 1 3 4 3
## 988 1 1 4 4 2
## 989 2 3 4 2 1
## 990 1 1 2 1 1
## 991 4 1 1 1 3
## 992 1 4 3 2 4
## 993 4 1 2 2 3
## 994 4 2 2 4 4
## 995 1 4 1 1 4
## 996 2 4 1 1 4
## 997 4 1 3 1 4
## 998 1 1 2 3 3
## 999 1 1 2 1 1
## 1000 1 2 2 1 1
## 1001 2 4 1 1 1
## 1002 2 3 4 3 4
## 1003 3 1 1 4 3
## 1004 1 1 3 1 3
## 1005 1 2 2 2 2
## 1006 1 1 4 2 2
## 1007 2 3 4 1 2
## 1008 2 1 4 2 2
## 1009 4 4 3 4 4
## 1010 2 4 4 4 2
## 1011 1 1 4 2 4
## 1012 4 1 1 4 2
## 1013 3 2 1 1 4
## 1014 1 1 1 2 1
## 1015 1 1 1 4 3
## 1016 2 2 1 4 4
## 1017 2 2 4 2 2
## 1018 4 4 2 3 4
## 1019 2 4 2 4 4
## 1020 2 4 1 1 2
## 1021 3 3 1 1 3
## 1022 4 2 1 4 4
## 1023 4 4 1 4 2
## 1024 1 4 3 3 2
## 1025 1 4 3 1 4
## 1033 4 1 2 1 2
## 1084 3 2 3 2 4
## 1156 2 2 4 4 1
## 1158 1 2 1 4 1
## 1317 1 3 1 2 1
## 1440 2 2 2 2 1
## 1464 2 2 1 1 1
## 1472 1 1 2 1 1
## 1710 1 1 4 4 1
## 1723 2 2 1 3 4
## 2022 3 1 4 3 2
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## 2086 4 3 3 4 4
## 2252 2 1 2 2 1
## 2284 2 1 3 3 2
## 2381 2 1 1 1 2
## 2657 3 4 2 4 3
## 2658 3 3 2 2 4
## 2661 1 2 3 2 4
## 2670 1 1 4 4 3
## 2702 2 2 2 4 1
## 2714 1 2 4 1 3
## 2717 2 4 4 3 4
## 2759 1 2 1 4 1
## 2763 4 4 2 4 4
## 2782 2 1 1 4 3
## 2976 1 3 1 1 2
## 2985 3 4 3 3 2
## 2988 2 3 1 4 1
## 3039 1 1 1 1 2
## 3062 4 4 1 4 4
## 3128 1 2 3 2 4
## 3192 1 2 4 2 2
## 3304 3 1 2 4 3
## 3327 1 2 4 1 4
## 3375 4 1 2 1 4
## 3423 4 4 4 1 4
## 3448 2 1 4 1 3
## 3450 1 4 2 1 2
## 3459 1 4 4 4 1
## 3460 4 2 4 2 1
## 3475 3 3 2 4 2
## 3485 1 2 2 1 2
## 3504 4 1 4 3 3
## 3534 1 1 4 2 1
## 3544 2 1 1 1 2
## 3879 2 1 1 1 2
## 3952 2 2 3 3 2
## 3953 4 1 1 4 2
## 4081 2 4 3 1 4
## 4122 1 4 2 3 1
## 4142 2 4 4 4 3
## 4280 2 1 2 1 1
## 4281 3 1 1 1 1
## 4301 3 3 1 1 3
## 4340 2 1 1 1 2
## 4357 2 4 4 2 3
## 4409 3 1 1 1 1
## 4515 1 4 2 4 2
## 4523 2 4 2 3 1
## 4526 2 2 3 1 2
## 4590 4 1 4 1 4
## 4718 2 2 2 3 4
## 4719 2 1 1 3 4
## 4730 2 2 4 2 4
## 4810 1 2 4 3 3
## 4860 3 3 1 2 1
## 4904 1 1 1 1 1
##
## $BSBM19C
## 1 2 3 4 5
## 110 2 1 4 1 3
## 122 3 3 1 2 1
## 198 4 4 4 3 4
## 214 2 3 1 1 3
## 251 3 4 3 4 2
## 362 3 2 1 3 1
## 464 4 4 4 4 3
## 492 3 3 4 2 2
## 676 1 2 3 4 2
## 808 1 3 2 2 2
## 818 1 4 2 4 2
## 836 4 3 3 1 3
## 853 1 1 1 3 4
## 873 1 2 1 1 1
## 878 2 1 2 1 1
## 897 4 3 2 1 2
## 939 2 3 2 4 2
## 960 3 4 4 4 4
## 961 3 3 1 4 2
## 962 2 3 3 2 1
## 963 1 4 1 2 1
## 964 3 3 1 2 4
## 965 1 3 1 2 4
## 966 4 1 2 1 4
## 967 1 4 4 2 3
## 968 3 4 4 4 2
## 969 3 1 2 4 4
## 970 2 4 1 2 1
## 971 3 4 2 3 2
## 972 3 4 2 2 3
## 973 4 2 3 2 3
## 974 2 2 4 3 1
## 975 4 2 4 2 2
## 976 3 2 3 2 4
## 977 1 4 2 2 2
## 978 1 2 3 4 1
## 979 4 3 2 1 2
## 980 1 4 2 4 4
## 981 1 1 1 2 4
## 982 2 3 3 4 4
## 983 2 1 3 1 1
## 984 1 2 3 3 1
## 985 4 4 1 3 4
## 986 4 4 3 3 4
## 987 2 1 4 3 2
## 988 2 2 3 4 3
## 989 2 3 3 1 2
## 990 1 2 3 2 2
## 991 4 1 1 1 3
## 992 2 3 2 3 4
## 993 4 1 4 1 1
## 994 4 2 2 2 3
## 995 1 2 1 2 2
## 996 3 2 2 3 3
## 997 4 1 4 2 4
## 998 1 1 2 2 2
## 999 1 2 2 1 1
## 1000 2 2 1 1 1
## 1001 4 4 1 2 1
## 1002 1 3 4 4 4
## 1003 3 1 1 4 3
## 1004 4 1 4 1 2
## 1005 3 2 2 3 4
## 1006 1 1 4 2 3
## 1007 1 4 3 2 3
## 1008 4 1 4 1 3
## 1009 3 3 3 4 3
## 1010 2 4 2 4 1
## 1011 1 1 4 4 3
## 1012 3 1 1 2 2
## 1013 3 2 2 1 1
## 1014 2 1 1 2 1
## 1015 1 2 1 2 1
## 1016 1 2 1 4 4
## 1017 1 3 4 2 3
## 1018 4 4 2 2 4
## 1019 4 2 2 4 4
## 1020 3 4 1 1 2
## 1021 1 3 1 1 3
## 1022 4 3 1 3 3
## 1023 4 3 1 2 4
## 1024 1 4 3 4 2
## 1025 1 4 2 1 4
## 1033 3 1 2 2 1
## 1156 3 2 4 4 1
## 1158 1 2 3 4 1
## 1317 2 2 1 3 2
## 1464 2 1 1 1 1
## 1472 1 1 2 1 1
## 1607 2 2 2 2 2
## 1710 1 1 4 4 1
## 1907 1 1 1 3 1
## 2022 4 2 4 3 2
## 2039 4 3 3 3 4
## 2381 1 2 1 3 3
## 2419 4 4 4 4 3
## 2608 4 4 2 3 4
## 2647 1 2 1 1 1
## 2657 3 4 2 4 3
## 2658 4 4 2 2 4
## 2670 2 1 4 4 3
## 2700 2 2 2 2 2
## 2702 3 4 3 4 4
## 2705 2 2 3 1 2
## 2714 2 2 3 1 1
## 2759 2 1 1 3 2
## 2763 2 4 1 4 2
## 2782 3 2 1 4 2
## 2828 1 2 1 2 2
## 2964 2 2 3 3 2
## 2976 1 2 2 1 2
## 3042 2 2 3 1 1
## 3062 3 2 2 3 4
## 3128 4 2 4 2 4
## 3304 2 2 2 4 2
## 3325 3 2 2 2 2
## 3327 1 3 4 1 4
## 3352 1 4 4 3 3
## 3375 4 1 2 1 1
## 3423 2 4 4 1 4
## 3448 3 1 4 1 3
## 3450 1 4 3 1 1
## 3459 1 4 4 4 2
## 3460 3 2 4 2 1
## 3519 2 2 3 4 2
## 3534 2 1 2 1 1
## 3643 2 1 1 1 1
## 3652 4 4 3 4 4
## 3703 2 2 3 4 2
## 3710 1 1 1 2 1
## 3756 1 2 1 1 1
## 3759 4 3 1 3 3
## 3868 3 4 4 4 4
## 3879 4 1 1 1 2
## 3953 4 1 1 4 2
## 4081 2 4 2 4 4
## 4092 4 3 2 3 3
## 4102 4 1 4 2 3
## 4280 1 1 1 1 1
## 4281 2 1 1 1 1
## 4301 2 2 2 1 1
## 4340 2 1 1 1 2
## 4357 3 4 3 2 3
## 4389 3 4 2 3 3
## 4409 2 1 1 2 1
## 4508 1 2 1 1 3
## 4523 3 3 2 2 1
## 4526 4 2 3 1 3
## 4590 2 1 3 1 2
## 4719 1 1 2 3 4
## 4775 3 4 3 4 4
## 4810 1 3 3 3 1
##
## $BSBM19D
## 1 2 3 4 5
## 62 1 2 1 1 1
## 110 2 3 1 1 1
## 116 3 3 3 2 1
## 122 3 2 1 2 2
## 198 1 1 1 1 1
## 214 2 3 4 2 2
## 251 4 2 2 1 1
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## 362 1 1 1 3 3
## 391 2 1 3 2 1
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## 492 1 1 1 1 2
## 545 1 2 3 1 1
## 676 4 3 2 2 2
## 711 2 4 2 1 2
## 806 2 1 2 1 1
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## 836 1 2 1 2 1
## 853 3 3 2 1 1
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## 939 2 3 2 2 1
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## 975 2 1 1 3 2
## 976 1 4 1 1 2
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## 978 4 4 1 2 4
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## 982 1 1 1 1 1
## 983 4 1 1 2 2
## 984 3 1 4 1 4
## 985 1 2 4 2 2
## 986 1 1 2 3 1
## 987 4 3 1 1 1
## 988 3 4 1 4 1
## 989 1 4 1 2 2
## 990 4 1 1 1 3
## 991 1 1 1 4 2
## 992 2 2 1 1 1
## 993 2 1 2 3 1
## 994 1 2 4 4 1
## 995 3 4 1 4 4
## 996 2 2 1 2 1
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## 999 4 1 2 4 2
## 1000 1 2 2 3 2
## 1001 3 1 2 4 3
## 1002 1 1 1 2 2
## 1003 1 2 3 1 2
## 1004 1 2 1 2 1
## 1005 2 4 2 1 1
## 1006 3 2 1 2 2
## 1007 3 2 2 2 1
## 1008 2 3 1 1 2
## 1009 3 1 1 2 1
## 1010 1 1 1 1 4
## 1011 3 4 2 2 2
## 1012 2 3 2 4 1
## 1013 1 1 2 2 3
## 1014 2 2 2 2 4
## 1015 4 2 2 1 4
## 1016 1 1 4 1 1
## 1017 3 2 1 1 2
## 1018 1 2 4 1 1
## 1019 1 3 2 1 1
## 1020 1 2 1 2 2
## 1021 2 2 4 4 2
## 1022 1 1 1 2 1
## 1023 1 2 3 1 2
## 1024 4 1 3 1 1
## 1025 2 2 3 3 2
## 1033 2 4 3 3 2
## 1156 2 2 3 1 3
## 1158 1 1 3 1 4
## 1317 2 2 3 1 2
## 1360 1 2 2 1 1
## 1464 4 3 4 4 3
## 1472 1 3 3 4 1
## 1541 3 2 4 3 2
## 1710 3 4 1 1 1
## 1798 1 1 1 1 1
## 2008 1 1 1 1 1
## 2022 1 1 1 1 2
## 2035 2 1 3 2 1
## 2064 1 2 2 3 2
## 2289 1 1 1 1 2
## 2381 4 4 2 2 2
## 2414 1 1 2 1 2
## 2469 2 2 1 1 1
## 2490 4 1 4 3 1
## 2493 1 1 2 3 2
## 2657 1 1 1 1 1
## 2658 1 1 2 3 1
## 2670 4 4 2 2 1
## 2673 1 1 2 2 2
## 2702 1 2 2 3 4
## 2705 2 1 1 1 1
## 2714 3 1 1 1 3
## 2739 3 1 2 2 3
## 2759 1 4 4 2 2
## 2763 3 2 1 2 4
## 2782 3 1 3 1 2
## 2827 1 4 2 4 4
## 2828 1 1 1 1 1
## 2871 2 2 3 3 2
## 2976 4 2 3 4 2
## 2999 2 1 2 2 3
## 3023 1 1 1 1 1
## 3062 3 4 1 2 1
## 3087 2 1 2 1 1
## 3125 2 1 1 2 1
## 3128 1 1 1 1 4
## 3304 2 3 3 1 3
## 3327 4 1 1 2 1
## 3375 2 4 2 1 2
## 3423 1 2 1 1 1
## 3448 1 2 1 3 1
## 3450 3 2 2 3 4
## 3459 1 2 1 1 1
## 3460 1 2 1 3 1
## 3534 1 4 1 1 4
## 3544 1 1 1 4 2
## 3591 1 1 1 1 1
## 3631 1 1 1 1 1
## 3740 2 1 3 3 3
## 3755 1 1 1 3 1
## 3879 1 1 1 2 1
## 3899 1 1 1 2 1
## 3953 4 1 2 1 3
## 3971 3 2 3 2 4
## 4081 1 1 1 1 1
## 4082 2 2 3 2 1
## 4280 4 2 4 4 4
## 4281 2 2 4 2 3
## 4301 1 3 4 4 2
## 4340 2 1 1 4 4
## 4357 1 2 1 2 1
## 4409 3 4 2 1 3
## 4428 1 2 1 2 1
## 4462 2 1 1 2 2
## 4508 3 2 1 1 1
## 4523 2 1 4 2 4
## 4526 1 1 1 2 4
## 4590 1 1 3 2 2
## 4719 4 4 1 1 1
## 4769 2 2 2 1 1
## 4770 1 1 1 1 1
## 4810 2 2 3 4 3
## 4841 3 1 1 3 2
##
## $BSBM19E
## 1 2 3 4 5
## 56 1 1 1 1 1
## 110 3 2 1 1 1
## 115 2 2 2 1 2
## 122 2 3 2 3 2
## 181 3 3 2 4 3
## 198 1 1 1 1 1
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## 227 1 1 1 1 1
## 234 3 3 3 3 2
## 251 3 1 3 1 3
## 348 2 2 4 2 1
## 362 3 3 1 2 4
## 374 3 3 4 2 3
## 416 1 1 1 1 2
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## 549 1 2 1 1 1
## 626 2 1 1 1 1
## 676 4 4 4 2 2
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## 818 3 1 4 1 2
## 836 1 3 3 2 2
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## 878 4 4 1 4 4
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## 897 1 1 1 2 2
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## 960 3 1 1 1 1
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## 962 2 2 1 3 3
## 963 2 2 4 4 4
## 964 2 1 4 2 1
## 965 2 2 3 2 2
## 966 1 4 2 4 1
## 967 4 1 1 1 1
## 968 1 1 4 3 2
## 969 1 4 2 1 1
## 970 2 1 4 4 4
## 971 2 1 2 1 3
## 972 1 3 1 2 1
## 973 1 1 3 1 1
## 974 1 3 1 2 2
## 975 2 1 2 2 4
## 976 1 4 1 1 2
## 977 3 1 2 2 3
## 978 4 4 1 1 4
## 979 1 2 1 4 2
## 980 2 2 1 2 1
## 981 4 4 3 3 1
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## 991 1 2 2 3 2
## 992 4 2 3 2 1
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##
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##
## $BSBM22C
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##
## $BSBM22D
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## 2276 4 3 4 3 3
## 2328 4 3 4 4 4
## 2341 2 3 3 1 1
## 2418 1 1 2 2 1
## 2419 2 2 2 2 1
## 2478 2 2 1 1 1
## 2557 3 4 4 4 3
## 2657 2 1 1 2 1
## 2658 2 1 1 2 2
## 2670 4 2 3 2 1
## 2677 4 3 4 4 4
## 2700 3 2 4 2 4
## 2702 1 2 3 3 4
## 2709 3 3 2 4 4
## 2714 4 4 4 4 4
## 2715 4 2 4 4 3
## 2717 2 3 3 3 1
## 2759 4 4 4 3 4
## 2760 4 4 3 4 3
## 2763 2 2 2 1 2
## 2782 3 3 3 2 3
## 2909 2 3 3 4 1
## 2976 1 2 4 4 4
## 3001 4 4 4 4 4
## 3062 3 3 3 3 3
## 3085 3 3 4 4 2
## 3102 4 2 3 3 4
## 3103 4 4 2 3 4
## 3199 3 4 4 4 3
## 3253 3 4 3 4 3
## 3270 4 4 4 4 2
## 3292 2 4 3 4 3
## 3304 2 3 2 3 4
## 3306 3 1 3 1 3
## 3327 3 2 2 4 4
## 3345 4 3 4 4 2
## 3423 1 3 1 2 1
## 3448 2 3 3 4 3
## 3450 3 2 4 4 4
## 3458 4 4 4 4 4
## 3459 2 2 1 1 3
## 3460 2 4 1 4 4
## 3497 4 4 4 4 4
## 3534 2 4 3 4 4
## 3544 2 1 1 1 1
## 3545 4 4 4 3 4
## 3552 3 4 4 4 4
## 3553 2 3 3 2 3
## 3557 3 2 4 2 3
## 3564 4 4 3 4 3
## 3655 2 1 2 2 2
## 3662 2 2 2 2 4
## 3673 3 4 3 4 4
## 3678 1 3 3 3 2
## 3710 4 4 4 4 2
## 3728 1 2 2 1 3
## 3799 1 4 1 2 2
## 3808 4 4 4 4 3
## 3818 2 4 2 1 2
## 3839 3 4 2 3 2
## 3872 3 2 2 3 3
## 3879 4 4 4 3 2
## 3891 3 3 4 3 4
## 3899 2 2 4 1 2
## 3902 3 4 4 3 3
## 3903 1 1 2 1 1
## 3920 4 2 3 4 2
## 3953 3 4 3 3 4
## 3960 4 4 4 3 2
## 4031 4 2 4 2 4
## 4077 4 3 3 4 4
## 4274 4 4 4 3 2
## 4301 2 4 4 4 3
## 4340 4 3 3 2 4
## 4357 3 2 2 2 3
## 4376 2 1 4 2 3
## 4409 1 4 4 3 4
## 4428 2 1 1 1 2
## 4442 3 3 3 3 3
## 4453 4 4 4 1 4
## 4496 2 3 3 2 3
## 4503 4 4 4 4 4
## 4508 4 3 3 3 4
## 4523 4 4 4 3 4
## 4526 2 4 4 3 3
## 4554 1 1 3 3 2
## 4590 4 4 4 4 4
## 4627 1 1 1 1 1
## 4678 3 3 2 1 2
## 4708 4 3 3 2 4
## 4719 4 4 4 2 2
## 4723 3 4 4 3 2
## 4786 2 1 3 2 2
## 4810 4 3 2 3 4
##
## $BSBM22F
## 1 2 3 4 5
## 74 3 2 3 4 3
## 94 3 1 2 1 1
## 122 4 2 3 2 2
## 181 3 3 3 2 3
## 209 2 4 4 4 2
## 219 4 3 2 4 4
## 234 4 4 4 4 2
## 242 3 4 4 4 3
## 251 1 4 2 3 2
## 294 3 3 4 2 3
## 333 1 3 3 1 3
## 390 3 4 4 3 3
## 484 4 4 2 1 4
## 492 2 2 2 3 3
## 506 3 4 4 4 3
## 572 1 3 1 2 1
## 591 1 2 2 2 2
## 594 3 4 3 1 4
## 626 3 2 4 4 2
## 676 3 2 3 3 2
## 679 2 2 4 4 3
## 709 3 3 3 2 4
## 722 1 1 1 2 1
## 818 2 2 4 3 4
## 836 2 4 2 4 2
## 843 4 4 3 4 3
## 844 2 2 2 2 4
## 853 4 4 4 3 3
## 854 2 2 4 4 4
## 862 4 4 4 3 4
## 873 4 4 4 2 4
## 878 4 4 1 1 2
## 879 4 3 4 3 4
## 885 4 1 1 3 4
## 889 1 2 1 3 2
## 939 2 3 2 3 3
## 946 1 2 1 1 2
## 960 4 1 1 2 3
## 961 3 4 4 1 4
## 962 3 2 4 3 2
## 963 3 1 3 4 4
## 964 2 2 4 1 1
## 965 2 3 2 3 4
## 966 1 4 2 2 2
## 967 2 3 3 3 1
## 968 2 2 3 4 3
## 969 2 3 3 1 1
## 970 1 1 4 4 3
## 971 1 1 2 1 2
## 972 1 4 2 2 1
## 973 1 2 3 1 2
## 974 1 3 1 1 2
## 975 3 2 2 2 3
## 976 2 2 1 2 1
## 977 3 2 2 4 3
## 978 4 4 2 3 2
## 979 2 3 1 2 1
## 980 2 4 3 2 2
## 981 4 4 4 3 1
## 982 2 3 3 3 2
## 983 4 3 2 3 1
## 984 3 1 4 2 4
## 985 4 3 4 4 3
## 986 1 2 2 1 1
## 987 4 4 2 2 3
## 988 4 4 2 4 2
## 989 2 3 3 4 4
## 990 4 2 3 4 1
## 991 2 2 1 4 2
## 992 2 1 3 1 3
## 993 3 4 2 2 3
## 994 2 4 4 4 3
## 995 3 4 3 4 4
## 996 4 4 4 2 2
## 997 2 4 4 2 4
## 998 2 2 2 3 4
## 999 4 2 2 4 3
## 1000 2 3 4 3 3
## 1001 2 2 4 4 4
## 1002 3 2 1 2 2
## 1003 1 4 4 2 4
## 1004 1 4 1 4 2
## 1005 2 4 2 2 2
## 1006 4 4 1 2 1
## 1007 4 4 3 2 4
## 1008 2 3 2 1 4
## 1009 3 1 2 3 2
## 1010 3 2 1 1 1
## 1011 2 4 4 2 4
## 1012 3 2 4 3 2
## 1013 1 4 4 4 2
## 1014 3 1 3 3 4
## 1015 4 4 3 4 4
## 1016 3 3 4 1 4
## 1017 3 1 2 3 1
## 1018 1 1 4 1 2
## 1019 1 3 3 2 1
## 1020 4 1 1 3 1
## 1021 3 4 2 4 4
## 1022 2 2 4 2 1
## 1023 2 1 3 2 1
## 1024 4 2 4 3 1
## 1025 2 4 3 3 2
## 1033 2 4 4 3 4
## 1116 1 1 1 2 1
## 1122 4 4 4 4 4
## 1156 4 3 2 2 3
## 1157 4 3 4 4 4
## 1158 2 2 4 2 4
## 1219 3 4 3 4 4
## 1262 2 3 2 2 1
## 1266 3 3 4 3 3
## 1316 1 1 4 1 3
## 1349 4 4 4 4 4
## 1353 3 4 1 3 2
## 1464 4 4 4 4 4
## 1587 2 2 3 3 3
## 1602 2 1 3 3 2
## 1609 4 4 4 4 3
## 1616 3 2 3 3 2
## 1696 1 1 2 4 4
## 1710 4 3 3 1 4
## 1722 3 2 2 3 3
## 1841 4 3 2 3 3
## 1848 2 3 2 4 4
## 2007 3 2 1 1 2
## 2163 2 3 3 3 2
## 2178 2 4 4 4 4
## 2219 4 4 4 4 4
## 2244 4 4 3 2 2
## 2252 4 3 3 4 3
## 2321 4 4 3 4 4
## 2328 4 4 4 4 4
## 2366 3 3 4 4 4
## 2368 4 4 4 4 4
## 2419 2 4 2 3 1
## 2427 1 1 1 1 1
## 2478 1 2 2 2 1
## 2486 2 3 2 2 4
## 2524 1 1 2 2 1
## 2557 3 3 3 4 4
## 2626 4 4 4 4 4
## 2657 2 1 3 1 2
## 2658 1 2 1 1 2
## 2670 4 3 1 1 3
## 2677 2 2 4 4 3
## 2700 3 1 3 3 4
## 2702 2 3 4 2 4
## 2714 4 3 3 4 4
## 2759 3 3 4 2 4
## 2760 4 2 4 4 3
## 2763 1 2 3 2 1
## 2782 4 1 4 2 3
## 2828 2 3 3 3 3
## 2909 3 2 2 2 1
## 2976 3 2 4 4 4
## 3067 2 3 2 4 3
## 3085 1 2 3 3 2
## 3102 4 3 4 2 2
## 3110 2 1 1 1 1
## 3203 1 1 4 4 2
## 3248 4 4 4 4 2
## 3270 4 2 3 1 1
## 3287 3 2 3 3 2
## 3292 2 4 3 4 4
## 3304 4 3 2 2 4
## 3306 3 1 1 1 1
## 3327 3 2 2 4 4
## 3345 4 3 4 4 2
## 3405 4 1 1 1 1
## 3423 1 2 2 1 2
## 3448 1 2 3 4 2
## 3450 2 2 3 2 4
## 3459 4 2 3 1 3
## 3460 3 4 1 2 3
## 3467 2 1 1 2 2
## 3476 3 4 3 4 4
## 3497 4 3 2 4 3
## 3534 1 4 2 4 4
## 3544 2 1 1 1 2
## 3545 4 4 4 1 4
## 3552 1 4 4 4 4
## 3557 3 1 4 1 3
## 3655 2 2 3 4 2
## 3678 1 2 2 4 2
## 3710 4 4 4 4 1
## 3728 1 3 2 1 3
## 3799 1 3 1 2 1
## 3808 4 4 4 4 4
## 3818 2 3 1 4 4
## 3866 2 3 2 3 4
## 3879 3 2 2 3 1
## 3891 3 3 3 2 3
## 3902 3 4 4 3 3
## 3903 1 1 2 1 2
## 3920 4 3 4 4 2
## 3953 3 4 2 4 4
## 3960 3 3 2 3 1
## 4031 4 2 3 2 4
## 4077 4 3 3 4 4
## 4187 2 1 1 2 3
## 4229 4 4 4 4 4
## 4274 1 3 4 3 4
## 4301 3 4 4 4 3
## 4304 4 4 4 4 4
## 4339 3 2 3 3 1
## 4340 4 3 4 3 4
## 4357 3 2 2 2 2
## 4403 2 2 2 3 2
## 4409 1 4 4 2 4
## 4453 4 4 4 2 4
## 4475 2 3 3 3 2
## 4508 4 4 4 3 2
## 4523 4 4 4 3 4
## 4526 3 3 3 2 1
## 4554 4 2 3 2 3
## 4590 3 4 3 4 3
## 4667 3 4 3 3 4
## 4678 1 2 1 1 3
## 4708 4 3 4 4 4
## 4719 3 3 4 2 3
## 4723 3 4 4 2 2
## 4810 3 3 3 4 4
##
## $BSBM22G
## 1 2 3 4 5
## 74 4 2 4 3 4
## 94 3 2 2 1 4
## 122 1 3 1 1 1
## 209 1 1 1 3 2
## 219 4 1 1 1 1
## 234 1 1 2 1 1
## 242 1 3 3 2 3
## 251 4 1 2 3 2
## 333 1 4 2 2 2
## 492 1 4 3 1 3
## 572 2 1 1 1 1
## 591 1 3 1 1 1
## 594 3 2 4 1 1
## 676 2 4 2 1 2
## 679 4 1 1 1 1
## 722 2 3 2 2 4
## 818 1 4 2 3 2
## 836 4 4 3 1 1
## 838 2 3 3 1 1
## 843 2 1 2 1 1
## 853 1 1 1 3 4
## 854 4 2 3 3 4
## 862 1 1 1 1 1
## 873 4 1 1 1 1
## 878 1 1 1 1 3
## 879 1 1 1 2 1
## 880 1 4 1 1 2
## 889 1 3 2 3 1
## 914 2 2 1 1 2
## 939 2 1 2 2 4
## 960 4 2 4 4 4
## 961 4 1 1 3 4
## 962 1 1 4 1 1
## 963 1 4 1 3 1
## 964 4 4 1 1 4
## 965 3 4 1 2 3
## 966 4 3 1 1 1
## 967 4 3 3 1 4
## 968 2 4 2 1 1
## 969 4 1 2 4 3
## 970 2 4 1 1 1
## 971 4 1 3 1 1
## 972 1 1 4 1 2
## 973 4 3 1 4 3
## 974 2 2 1 4 1
## 975 4 3 1 1 2
## 976 1 3 3 3 4
## 977 1 1 1 4 4
## 978 1 1 4 2 1
## 979 3 4 4 1 4
## 980 1 4 2 1 4
## 981 1 1 1 2 4
## 982 3 4 3 2 4
## 983 3 1 4 3 1
## 984 1 1 4 2 1
## 985 1 3 2 3 4
## 986 4 1 3 2 3
## 987 2 1 4 4 4
## 988 2 1 4 4 2
## 989 1 3 2 1 1
## 990 1 1 2 4 2
## 991 4 1 1 3 2
## 992 1 3 3 3 4
## 993 4 1 4 1 2
## 994 1 1 1 2 1
## 995 3 3 1 3 3
## 996 2 1 3 1 4
## 997 4 1 4 1 2
## 998 1 3 3 3 4
## 999 4 4 1 1 1
## 1000 1 1 4 1 1
## 1001 2 2 4 1 1
## 1002 2 4 4 3 4
## 1003 1 1 2 4 1
## 1004 4 1 4 1 4
## 1005 4 1 3 1 2
## 1006 1 4 2 1 1
## 1007 1 2 2 4 1
## 1008 4 1 3 4 1
## 1009 1 2 4 4 2
## 1010 4 3 3 3 1
## 1011 3 1 4 4 3
## 1012 4 1 1 3 1
## 1013 4 2 1 1 2
## 1014 1 3 1 1 4
## 1015 1 1 1 1 1
## 1016 1 4 2 2 1
## 1017 4 4 1 2 1
## 1018 3 3 2 2 4
## 1019 4 3 2 2 4
## 1020 4 4 3 1 1
## 1021 1 4 1 1 2
## 1022 3 4 1 1 4
## 1023 3 1 1 4 3
## 1024 1 1 4 3 2
## 1025 1 4 4 1 3
## 1033 1 1 3 1 2
## 1122 1 2 2 1 1
## 1156 4 3 3 3 1
## 1157 1 3 3 3 4
## 1158 2 3 2 4 4
## 1219 3 1 1 1 1
## 1262 4 4 2 3 4
## 1616 1 1 1 1 3
## 1696 2 2 1 2 1
## 1710 3 1 4 4 1
## 1841 2 2 1 1 1
## 1919 1 1 1 1 1
## 2163 1 1 1 4 1
## 2252 1 1 2 2 1
## 2328 1 1 1 1 1
## 2348 2 1 1 1 1
## 2478 4 2 3 4 4
## 2557 1 2 1 2 2
## 2657 3 4 3 3 4
## 2658 4 4 4 1 4
## 2670 3 2 2 4 4
## 2677 1 1 1 1 1
## 2700 1 4 2 2 2
## 2702 1 1 3 4 1
## 2714 1 4 2 2 3
## 2759 1 1 1 4 1
## 2760 2 1 2 1 1
## 2763 1 4 3 4 4
## 2782 1 1 2 4 3
## 2828 2 2 2 1 2
## 2909 4 3 2 4 4
## 2976 2 4 1 1 1
## 2986 1 3 1 4 1
## 3085 1 1 2 1 1
## 3102 2 2 2 3 1
## 3232 2 4 4 4 4
## 3270 1 2 1 1 2
## 3292 1 1 1 3 1
## 3304 1 4 2 1 1
## 3306 1 1 1 4 1
## 3324 2 3 3 2 4
## 3327 1 2 3 1 4
## 3345 1 2 2 1 1
## 3423 4 4 2 2 4
## 3448 2 1 4 2 1
## 3450 1 1 2 4 1
## 3459 2 4 4 2 2
## 3460 1 1 1 1 1
## 3497 4 2 2 1 1
## 3534 2 1 1 1 3
## 3544 2 4 3 1 4
## 3545 3 1 1 1 1
## 3552 1 1 1 1 1
## 3557 1 3 1 1 1
## 3655 4 4 4 2 4
## 3678 3 4 2 4 2
## 3687 1 1 2 4 4
## 3710 1 1 2 1 1
## 3728 3 4 4 3 4
## 3799 4 3 4 4 4
## 3808 1 1 1 1 1
## 3818 3 1 2 1 3
## 3879 2 1 1 1 1
## 3891 4 4 1 2 1
## 3902 2 1 1 1 2
## 3903 1 2 2 2 1
## 3920 1 1 4 1 1
## 3953 3 1 1 1 1
## 3960 1 1 1 1 4
## 4031 2 3 1 3 1
## 4077 1 2 2 2 1
## 4274 1 1 2 1 1
## 4301 2 2 3 1 1
## 4340 1 2 3 1 1
## 4357 1 3 3 4 3
## 4403 3 1 4 3 1
## 4409 2 1 1 2 3
## 4453 2 1 1 1 3
## 4508 1 4 3 4 1
## 4523 1 4 2 4 1
## 4526 3 1 2 1 2
## 4554 3 4 3 1 1
## 4590 2 1 1 2 1
## 4678 4 2 4 4 4
## 4708 1 4 1 2 1
## 4719 2 1 1 1 4
## 4723 1 1 1 4 4
## 4772 4 2 4 3 4
## 4810 1 2 3 4 2
##
## $BSBM22H
## 1 2 3 4 5
## 74 2 2 4 1 4
## 94 4 1 1 1 2
## 122 1 4 1 1 4
## 209 1 2 1 2 2
## 219 4 1 1 1 1
## 232 1 1 1 1 1
## 234 1 1 1 1 1
## 242 2 3 1 1 3
## 251 2 1 3 3 1
## 333 2 1 3 3 1
## 492 2 3 4 2 3
## 572 4 1 2 1 1
## 591 2 3 1 1 1
## 594 2 2 3 1 4
## 676 2 2 2 1 2
## 679 2 1 1 1 1
## 722 2 4 3 2 3
## 807 2 1 1 3 1
## 818 2 4 1 2 2
## 836 4 4 3 1 1
## 843 2 1 1 1 1
## 853 1 1 2 3 4
## 854 4 3 3 2 4
## 862 1 1 1 1 1
## 873 3 1 1 1 1
## 878 1 2 2 1 2
## 879 1 2 2 2 1
## 889 2 2 2 1 2
## 939 2 2 2 2 1
## 960 4 2 4 3 4
## 961 3 3 1 2 4
## 962 2 3 3 1 2
## 963 1 3 1 2 1
## 964 4 4 1 3 4
## 965 4 3 1 2 4
## 966 4 2 2 1 1
## 967 3 3 2 3 3
## 968 3 4 2 2 1
## 969 2 3 1 2 2
## 970 2 4 1 2 1
## 971 4 1 2 3 1
## 972 2 1 4 1 2
## 973 2 1 1 3 3
## 974 2 2 2 2 1
## 975 2 3 2 1 3
## 976 2 4 4 2 4
## 977 1 2 1 4 1
## 978 1 1 4 3 2
## 979 2 4 2 1 4
## 980 1 4 3 1 4
## 981 1 1 1 3 4
## 982 2 2 4 1 3
## 983 3 1 2 2 4
## 984 1 1 4 3 1
## 985 2 3 1 4 3
## 986 4 2 3 3 2
## 987 3 1 2 3 3
## 988 1 1 3 4 4
## 989 1 3 2 1 2
## 990 1 1 2 2 3
## 991 4 1 1 1 2
## 992 1 4 3 3 4
## 993 2 1 4 1 1
## 994 3 4 2 1 2
## 995 2 4 1 3 4
## 996 2 1 4 1 4
## 997 4 1 4 1 2
## 998 1 2 4 2 2
## 999 3 4 1 1 1
## 1000 1 1 2 1 2
## 1001 3 4 3 1 1
## 1002 4 4 4 3 4
## 1003 2 1 2 4 1
## 1004 4 1 4 1 2
## 1005 2 1 2 1 4
## 1006 1 2 2 1 1
## 1007 3 2 4 3 2
## 1008 1 1 2 3 1
## 1009 1 3 3 4 2
## 1010 4 4 1 2 1
## 1011 3 2 4 3 2
## 1012 3 1 2 3 1
## 1013 1 2 1 1 1
## 1014 1 4 1 1 3
## 1015 1 1 1 1 1
## 1016 2 3 1 3 2
## 1017 2 3 2 2 2
## 1018 3 3 2 3 4
## 1019 4 4 1 2 4
## 1020 2 4 2 1 1
## 1021 1 4 3 1 2
## 1022 4 2 1 1 4
## 1023 3 1 1 2 2
## 1024 1 1 4 4 2
## 1025 1 2 4 1 3
## 1033 2 4 1 1 2
## 1122 1 2 2 2 1
## 1156 2 3 2 4 1
## 1157 1 2 3 4 3
## 1158 2 3 3 2 2
## 1219 2 4 1 1 1
## 1262 2 3 3 4 4
## 1616 1 1 1 1 4
## 1696 4 1 1 2 1
## 1710 2 1 4 4 2
## 1823 2 2 2 2 1
## 1841 2 2 1 3 1
## 1898 4 4 2 4 2
## 2163 1 2 2 2 2
## 2252 1 1 3 1 2
## 2328 1 2 2 2 1
## 2330 2 4 2 3 2
## 2426 1 2 2 1 2
## 2478 4 2 2 4 3
## 2557 1 2 2 2 3
## 2657 2 4 4 4 2
## 2658 4 3 4 1 3
## 2670 2 2 2 3 3
## 2677 1 1 1 1 1
## 2700 1 2 2 1 3
## 2702 2 1 1 4 3
## 2714 1 3 2 3 2
## 2715 4 4 4 4 1
## 2759 1 1 1 2 1
## 2760 3 2 2 1 1
## 2763 1 4 3 3 4
## 2782 2 1 1 2 2
## 2846 1 1 1 1 1
## 2909 4 3 1 3 4
## 2976 2 4 1 1 1
## 3062 2 2 3 2 2
## 3085 2 1 3 1 1
## 3102 1 2 3 2 2
## 3167 2 2 2 4 2
## 3183 2 4 3 2 2
## 3198 1 1 2 1 2
## 3270 1 2 1 1 4
## 3304 2 3 2 1 1
## 3306 1 2 1 4 2
## 3327 1 2 2 1 3
## 3339 3 3 3 2 3
## 3345 1 1 4 1 1
## 3423 2 3 1 2 4
## 3448 2 1 3 2 1
## 3450 1 1 3 2 1
## 3459 1 2 3 3 4
## 3460 1 1 1 1 1
## 3497 4 2 2 2 1
## 3534 2 1 1 3 2
## 3544 2 2 2 2 2
## 3545 2 2 2 1 1
## 3552 1 1 1 1 3
## 3557 1 3 1 2 1
## 3655 2 2 3 2 2
## 3678 3 2 3 3 1
## 3710 1 1 1 2 1
## 3728 2 3 3 1 4
## 3799 3 3 4 4 4
## 3808 1 1 1 1 1
## 3818 4 1 3 4 2
## 3879 4 1 1 1 4
## 3880 1 2 2 1 1
## 3891 4 1 1 2 3
## 3902 1 1 4 2 3
## 3903 1 2 2 1 1
## 3920 1 1 4 1 2
## 3953 2 3 1 1 1
## 3960 4 1 1 1 2
## 4031 1 4 1 2 1
## 4077 1 1 2 2 1
## 4274 1 1 3 1 1
## 4301 1 1 3 1 1
## 4330 2 4 2 2 1
## 4340 1 2 2 1 1
## 4357 1 3 2 4 2
## 4403 3 1 1 3 1
## 4409 2 4 1 2 3
## 4453 1 1 1 1 3
## 4475 2 2 2 3 3
## 4508 1 3 3 3 1
## 4523 2 4 3 3 1
## 4526 1 1 2 1 4
## 4554 4 4 1 4 1
## 4570 2 4 4 4 2
## 4590 1 1 1 2 1
## 4678 2 4 3 3 3
## 4708 1 4 1 4 1
## 4719 2 1 1 2 2
## 4723 1 1 2 3 3
## 4810 1 4 2 3 1
##
## $BSMMAT01
## [1] 1 2 3 4 5
## <0 rows> (or 0-length row.names)Ortalama atamak
ogrenci <- ogrenci %>%
mutate(BSBM22F=ifelse(is.na(BSBM22F), mean(BSBM22F, na.rm=TRUE),
BSBM22F)) %>% na.omit()
summary(ogrenci)## BSBG01 BSBM19A BSBM19B BSBM19C
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000
## Median :1.000 Median :2.000 Median :2.000 Median :2.000
## Mean :1.498 Mean :2.187 Mean :2.434 Mean :2.462
## 3rd Qu.:2.000 3rd Qu.:3.000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :2.000 Max. :4.000 Max. :4.000 Max. :4.000
## BSBM19D BSBM19E BSBM19F BSBM19G
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000
## Median :2.000 Median :2.000 Median :2.000 Median :2.000
## Mean :2.074 Mean :2.304 Mean :2.425 Mean :2.425
## 3rd Qu.:3.000 3rd Qu.:3.000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :4.000 Max. :4.000 Max. :4.000 Max. :4.000
## BSBM19H BSBM19I BSBM22A BSBM22B
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:2.000 1st Qu.:1.000 1st Qu.:2.000 1st Qu.:1.000
## Median :3.000 Median :3.000 Median :2.000 Median :2.000
## Mean :2.924 Mean :2.675 Mean :2.404 Mean :2.513
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:3.000 3rd Qu.:4.000
## Max. :4.000 Max. :4.000 Max. :4.000 Max. :4.000
## BSBM22C BSBM22D BSBM22E BSBM22F
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000
## Median :2.000 Median :3.000 Median :3.000 Median :3.000
## Mean :2.408 Mean :2.687 Mean :2.848 Mean :2.649
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :4.000 Max. :4.000 Max. :4.000 Max. :4.000
## BSBM22G BSBM22H BSMMAT01
## Min. :1.000 Min. :1.000 Min. :221.6
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:425.4
## Median :2.000 Median :2.000 Median :507.9
## Mean :2.284 Mean :2.197 Mean :508.8
## 3rd Qu.:4.000 3rd Qu.:3.000 3rd Qu.:590.2
## Max. :4.000 Max. :4.000 Max. :851.1