#Aplikasi dalam R
simpan = read.table("data4.1.csv", header = TRUE, sep = ",") # membaca data4.1
simpan
##    data1 data2 data3
## 1      1    10     1
## 2      2    10     2
## 3      3    10     2
## 4      4    20     3
## 5      5    20     3
## 6      6    30     3
## 7      7    30     3
## 8      8    30     3
## 9      9    30     4
## 10    10    30     4
## 11    11    40     4
## 12    11    40     5
## 13    12    40     5
## 14    13    40     6
## 15    14    40     6
## 16    15    50    NA
## 17    16    50    NA
## 18    17    50    NA
## 19    18    50    NA
data_1 = simpan$data1     
data_11 = na.omit(data_1)

data_2 = simpan$data2     
data_21 = na.omit(data_2)

data_3 = simpan$data3     
data_31 = na.omit(data_3) 


data_1  
##  [1]  1  2  3  4  5  6  7  8  9 10 11 11 12 13 14 15 16 17 18
data_11  
##  [1]  1  2  3  4  5  6  7  8  9 10 11 11 12 13 14 15 16 17 18
data_2  
##  [1] 10 10 10 20 20 30 30 30 30 30 40 40 40 40 40 50 50 50 50
data_21 
##  [1] 10 10 10 20 20 30 30 30 30 30 40 40 40 40 40 50 50 50 50
data_3  
##  [1]  1  2  2  3  3  3  3  3  4  4  4  5  5  6  6 NA NA NA NA
data_31 
##  [1] 1 2 2 3 3 3 3 3 4 4 4 5 5 6 6
## attr(,"na.action")
## [1] 16 17 18 19
## attr(,"class")
## [1] "omit"
library(psych)
## Warning: package 'psych' was built under R version 4.5.3
describe(data_11)
##    vars  n mean  sd median trimmed  mad min max range  skew kurtosis   se
## X1    1 19 9.58 5.2     10    9.59 5.93   1  18    17 -0.04    -1.32 1.19
describe(data_21) 
##    vars  n  mean    sd median trimmed   mad min max range  skew kurtosis   se
## X1    1 19 32.63 13.68     30   32.94 14.83  10  50    40 -0.33    -1.17 3.14
describe(data_31) 
##    vars  n mean   sd median trimmed  mad min max range skew kurtosis   se
## X1    1 15  3.6 1.45      3    3.62 1.48   1   6     5 0.14    -1.01 0.38
library(pastecs)
## Warning: package 'pastecs' was built under R version 4.5.2
stat.desc(data_11)
##      nbr.val     nbr.null       nbr.na          min          max        range 
##   19.0000000    0.0000000    0.0000000    1.0000000   18.0000000   17.0000000 
##          sum       median         mean      SE.mean CI.mean.0.95          var 
##  182.0000000   10.0000000    9.5789474    1.1928535    2.5060921   27.0350877 
##      std.dev     coef.var 
##    5.1995276    0.5428078
stat.desc(data_21)
##      nbr.val     nbr.null       nbr.na          min          max        range 
##    19.000000     0.000000     0.000000    10.000000    50.000000    40.000000 
##          sum       median         mean      SE.mean CI.mean.0.95          var 
##   620.000000    30.000000    32.631579     3.138341     6.593410   187.134503 
##      std.dev     coef.var 
##    13.679711     0.419217
stat.desc(data_31)
##                       x
## nbr.val      15.0000000
## nbr.null      0.0000000
## nbr.na        0.0000000
## min           1.0000000
## max           6.0000000
## range         5.0000000
## sum          54.0000000
## median        3.0000000
## mean          3.6000000
## SE.mean       0.3754363
## CI.mean.0.95  0.8052307
## var           2.1142857
## std.dev       1.4540584
## coef.var      0.4039051
#Aplikasi R untuk Data Berkelompok
simpan = read.table("data4.2.csv", header = TRUE, sep = ",") 
simpan
##    jurusan.angka jurusan.label jenis.angka jenis.label  IQ  EQ
## 1              1    matematika           1   laki-laki 101 102
## 2              1    matematika           1   laki-laki 104 104
## 3              1    matematika           1   laki-laki 102 104
## 4              1    matematika           2   perempuan 111 105
## 5              1    matematika           2   perempuan 101 106
## 6              1    matematika           2   perempuan 105 102
## 7              2    statistika           1   laki-laki 104 101
## 8              2    statistika           1   laki-laki 103 112
## 9              2    statistika           1   laki-laki 104 104
## 10             2    statistika           2   perempuan 102 101
## 11             2    statistika           2   perempuan 101 102
## 12             2    statistika           2   perempuan 101 104
library(psych)
describeBy(simpan$IQ, simpan$jurusan.angka)
## 
##  Descriptive statistics by group 
## group: 1
##    vars n mean   sd median trimmed  mad min max range skew kurtosis   se
## X1    1 6  104 3.79    103     104 2.97 101 111    10 0.86    -0.93 1.55
## ------------------------------------------------------------ 
## group: 2
##    vars n  mean   sd median trimmed  mad min max range skew kurtosis   se
## X1    1 6 102.5 1.38  102.5   102.5 2.22 101 104     3    0    -2.06 0.56
describeBy(simpan$IQ, simpan$jurusan.label)
## 
##  Descriptive statistics by group 
## group: matematika
##    vars n mean   sd median trimmed  mad min max range skew kurtosis   se
## X1    1 6  104 3.79    103     104 2.97 101 111    10 0.86    -0.93 1.55
## ------------------------------------------------------------ 
## group: statistika
##    vars n  mean   sd median trimmed  mad min max range skew kurtosis   se
## X1    1 6 102.5 1.38  102.5   102.5 2.22 101 104     3    0    -2.06 0.56
describeBy(simpan$EQ, simpan$jurusan.angka)
## 
##  Descriptive statistics by group 
## group: 1
##    vars n   mean  sd median trimmed  mad min max range  skew kurtosis   se
## X1    1 6 103.83 1.6    104  103.83 2.22 102 106     4 -0.02    -1.82 0.65
## ------------------------------------------------------------ 
## group: 2
##    vars n mean   sd median trimmed  mad min max range skew kurtosis   se
## X1    1 6  104 4.15    103     104 2.22 101 112    11 1.05    -0.59 1.69
describeBy(simpan$EQ, simpan$jurusan.label)
## 
##  Descriptive statistics by group 
## group: matematika
##    vars n   mean  sd median trimmed  mad min max range  skew kurtosis   se
## X1    1 6 103.83 1.6    104  103.83 2.22 102 106     4 -0.02    -1.82 0.65
## ------------------------------------------------------------ 
## group: statistika
##    vars n mean   sd median trimmed  mad min max range skew kurtosis   se
## X1    1 6  104 4.15    103     104 2.22 101 112    11 1.05    -0.59 1.69
library(doBy)
## Warning: package 'doBy' was built under R version 4.5.3
summaryBy(IQ + EQ ~ jurusan.label + jenis.label, data = simpan, 
          FUN = function(x) { 
            c(ratarata = mean(x), standar_deviasi = sd(x), jumlah = sum(x)) 
          })
##   jurusan.label jenis.label IQ.ratarata IQ.standar_deviasi IQ.jumlah
## 1    matematika   laki-laki    102.3333          1.5275252       307
## 2    matematika   perempuan    105.6667          5.0332230       317
## 3    statistika   laki-laki    103.6667          0.5773503       311
## 4    statistika   perempuan    101.3333          0.5773503       304
##   EQ.ratarata EQ.standar_deviasi EQ.jumlah
## 1    103.3333           1.154701       310
## 2    104.3333           2.081666       313
## 3    105.6667           5.686241       317
## 4    102.3333           1.527525       307