library(foreign)
library(dplyr) # data manipulation
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(forcats) # to work with categorical variables
library(ggplot2) # data visualization
library(readr) # read specific csv files
library(janitor) # data exploration and cleaning
##
## Attaching package: 'janitor'
## The following objects are masked from 'package:stats':
##
## chisq.test, fisher.test
library(Hmisc) # several useful functions for data analysis
##
## Attaching package: 'Hmisc'
## The following objects are masked from 'package:dplyr':
##
## src, summarize
## The following objects are masked from 'package:base':
##
## format.pval, units
library(psych) # functions for multivariate analysis
##
## Attaching package: 'psych'
## The following object is masked from 'package:Hmisc':
##
## describe
## The following objects are masked from 'package:ggplot2':
##
## %+%, alpha
library(naniar) # summaries and visualization of missing values NAs
#library(dlookr) # summaries and visualization of missing values NAs
library(corrplot) # correlation plots
## corrplot 0.92 loaded
library(jtools) # presentation of regression analysis
##
## Attaching package: 'jtools'
## The following object is masked from 'package:Hmisc':
##
## %nin%
library(lmtest) # diagnostic checks - linear regression analysis
## Loading required package: zoo
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
library(car) # diagnostic checks - linear regression analysis
## Loading required package: carData
##
## Attaching package: 'car'
## The following object is masked from 'package:psych':
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## logit
## The following object is masked from 'package:dplyr':
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## recode
library(olsrr) # diagnostic checks - linear regression analysis
##
## Attaching package: 'olsrr'
## The following object is masked from 'package:datasets':
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## rivers
library(naniar) # identifying missing values
#library(funModeling) # create frequency tables
library(stargazer) # create publication quality tables
##
## Please cite as:
## Hlavac, Marek (2022). stargazer: Well-Formatted Regression and Summary Statistics Tables.
## R package version 5.2.3. https://CRAN.R-project.org/package=stargazer
#library(effects) # displays for linear and other regression models
data = read.csv("real_estate_data.csv")
head(data)
## medv cmedv crim zn indus chas nox rm age dis rad tax ptratio
## 1 24.0 24.0 0.00632 18 2.31 0 0.538 6.575 65.2 4.0900 1 296 15.3
## 2 21.6 21.6 0.02731 0 7.07 0 0.469 6.421 78.9 4.9671 2 242 17.8
## 3 34.7 34.7 0.02729 0 7.07 0 0.469 7.185 61.1 4.9671 2 242 17.8
## 4 33.4 33.4 0.03237 0 2.18 0 0.458 6.998 45.8 6.0622 3 222 18.7
## 5 36.2 36.2 0.06905 0 2.18 0 0.458 7.147 54.2 6.0622 3 222 18.7
## 6 28.7 28.7 0.02985 0 2.18 0 0.458 6.430 58.7 6.0622 3 222 18.7
## b lstat
## 1 396.90 4.98
## 2 396.90 9.14
## 3 392.83 4.03
## 4 394.63 2.94
## 5 396.90 5.33
## 6 394.12 5.21
# a. Exploratory Data Analysis
# Identify missing values
sum(is.na(data))
## [1] 0
colSums(is.na(data))
## medv cmedv crim zn indus chas nox rm age dis
## 0 0 0 0 0 0 0 0 0 0
## rad tax ptratio b lstat
## 0 0 0 0 0
str(data)
## 'data.frame': 506 obs. of 15 variables:
## $ medv : num 24 21.6 34.7 33.4 36.2 28.7 22.9 27.1 16.5 18.9 ...
## $ cmedv : num 24 21.6 34.7 33.4 36.2 28.7 22.9 22.1 16.5 18.9 ...
## $ crim : num 0.00632 0.02731 0.02729 0.03237 0.06905 ...
## $ zn : num 18 0 0 0 0 0 12.5 12.5 12.5 12.5 ...
## $ indus : num 2.31 7.07 7.07 2.18 2.18 2.18 7.87 7.87 7.87 7.87 ...
## $ chas : int 0 0 0 0 0 0 0 0 0 0 ...
## $ nox : num 0.538 0.469 0.469 0.458 0.458 0.458 0.524 0.524 0.524 0.524 ...
## $ rm : num 6.58 6.42 7.18 7 7.15 ...
## $ age : num 65.2 78.9 61.1 45.8 54.2 58.7 66.6 96.1 100 85.9 ...
## $ dis : num 4.09 4.97 4.97 6.06 6.06 ...
## $ rad : int 1 2 2 3 3 3 5 5 5 5 ...
## $ tax : int 296 242 242 222 222 222 311 311 311 311 ...
## $ ptratio: num 15.3 17.8 17.8 18.7 18.7 18.7 15.2 15.2 15.2 15.2 ...
## $ b : num 397 397 393 395 397 ...
## $ lstat : num 4.98 9.14 4.03 2.94 5.33 ...
summary(data)
## medv cmedv crim zn
## Min. : 5.00 Min. : 5.00 Min. : 0.00632 Min. : 0.00
## 1st Qu.:17.02 1st Qu.:17.02 1st Qu.: 0.08205 1st Qu.: 0.00
## Median :21.20 Median :21.20 Median : 0.25651 Median : 0.00
## Mean :22.53 Mean :22.53 Mean : 3.61352 Mean : 11.36
## 3rd Qu.:25.00 3rd Qu.:25.00 3rd Qu.: 3.67708 3rd Qu.: 12.50
## Max. :50.00 Max. :50.00 Max. :88.97620 Max. :100.00
## indus chas nox rm
## Min. : 0.46 Min. :0.00000 Min. :0.3850 Min. :3.561
## 1st Qu.: 5.19 1st Qu.:0.00000 1st Qu.:0.4490 1st Qu.:5.886
## Median : 9.69 Median :0.00000 Median :0.5380 Median :6.208
## Mean :11.14 Mean :0.06917 Mean :0.5547 Mean :6.285
## 3rd Qu.:18.10 3rd Qu.:0.00000 3rd Qu.:0.6240 3rd Qu.:6.623
## Max. :27.74 Max. :1.00000 Max. :0.8710 Max. :8.780
## age dis rad tax
## Min. : 2.90 Min. : 1.130 Min. : 1.000 Min. :187.0
## 1st Qu.: 45.02 1st Qu.: 2.100 1st Qu.: 4.000 1st Qu.:279.0
## Median : 77.50 Median : 3.207 Median : 5.000 Median :330.0
## Mean : 68.57 Mean : 3.795 Mean : 9.549 Mean :408.2
## 3rd Qu.: 94.08 3rd Qu.: 5.188 3rd Qu.:24.000 3rd Qu.:666.0
## Max. :100.00 Max. :12.127 Max. :24.000 Max. :711.0
## ptratio b lstat
## Min. :12.60 Min. : 0.32 Min. : 1.73
## 1st Qu.:17.40 1st Qu.:375.38 1st Qu.: 6.95
## Median :19.05 Median :391.44 Median :11.36
## Mean :18.46 Mean :356.67 Mean :12.65
## 3rd Qu.:20.20 3rd Qu.:396.23 3rd Qu.:16.95
## Max. :22.00 Max. :396.90 Max. :37.97
describe(data)
## vars n mean sd median trimmed mad min max range skew
## medv 1 506 22.53 9.20 21.20 21.56 5.93 5.00 50.00 45.00 1.10
## cmedv 2 506 22.53 9.18 21.20 21.56 5.93 5.00 50.00 45.00 1.10
## crim 3 506 3.61 8.60 0.26 1.68 0.33 0.01 88.98 88.97 5.19
## zn 4 506 11.36 23.32 0.00 5.08 0.00 0.00 100.00 100.00 2.21
## indus 5 506 11.14 6.86 9.69 10.93 9.37 0.46 27.74 27.28 0.29
## chas 6 506 0.07 0.25 0.00 0.00 0.00 0.00 1.00 1.00 3.39
## nox 7 506 0.55 0.12 0.54 0.55 0.13 0.38 0.87 0.49 0.72
## rm 8 506 6.28 0.70 6.21 6.25 0.51 3.56 8.78 5.22 0.40
## age 9 506 68.57 28.15 77.50 71.20 28.98 2.90 100.00 97.10 -0.60
## dis 10 506 3.80 2.11 3.21 3.54 1.91 1.13 12.13 11.00 1.01
## rad 11 506 9.55 8.71 5.00 8.73 2.97 1.00 24.00 23.00 1.00
## tax 12 506 408.24 168.54 330.00 400.04 108.23 187.00 711.00 524.00 0.67
## ptratio 13 506 18.46 2.16 19.05 18.66 1.70 12.60 22.00 9.40 -0.80
## b 14 506 356.67 91.29 391.44 383.17 8.09 0.32 396.90 396.58 -2.87
## lstat 15 506 12.65 7.14 11.36 11.90 7.11 1.73 37.97 36.24 0.90
## kurtosis se
## medv 1.45 0.41
## cmedv 1.47 0.41
## crim 36.60 0.38
## zn 3.95 1.04
## indus -1.24 0.30
## chas 9.48 0.01
## nox -0.09 0.01
## rm 1.84 0.03
## age -0.98 1.25
## dis 0.46 0.09
## rad -0.88 0.39
## tax -1.15 7.49
## ptratio -0.30 0.10
## b 7.10 4.06
## lstat 0.46 0.32
#Renombrando variables
colnames(data) <- c("median_value", "cmedian_value", "crime_rate","residential_land", "non_retail_business", "river_view", "nitric_oxid", "rooms", "age", "distance", "access_to_highways", "property_tax_rate", "school", "b", "low_status_pop")
data
## median_value cmedian_value crime_rate residential_land non_retail_business
## 1 24.0 24.0 0.00632 18.0 2.31
## 2 21.6 21.6 0.02731 0.0 7.07
## 3 34.7 34.7 0.02729 0.0 7.07
## 4 33.4 33.4 0.03237 0.0 2.18
## 5 36.2 36.2 0.06905 0.0 2.18
## 6 28.7 28.7 0.02985 0.0 2.18
## 7 22.9 22.9 0.08829 12.5 7.87
## 8 27.1 22.1 0.14455 12.5 7.87
## 9 16.5 16.5 0.21124 12.5 7.87
## 10 18.9 18.9 0.17004 12.5 7.87
## 11 15.0 15.0 0.22489 12.5 7.87
## 12 18.9 18.9 0.11747 12.5 7.87
## 13 21.7 21.7 0.09378 12.5 7.87
## 14 20.4 20.4 0.62976 0.0 8.14
## 15 18.2 18.2 0.63796 0.0 8.14
## 16 19.9 19.9 0.62739 0.0 8.14
## 17 23.1 23.1 1.05393 0.0 8.14
## 18 17.5 17.5 0.78420 0.0 8.14
## 19 20.2 20.2 0.80271 0.0 8.14
## 20 18.2 18.2 0.72580 0.0 8.14
## 21 13.6 13.6 1.25179 0.0 8.14
## 22 19.6 19.6 0.85204 0.0 8.14
## 23 15.2 15.2 1.23247 0.0 8.14
## 24 14.5 14.5 0.98843 0.0 8.14
## 25 15.6 15.6 0.75026 0.0 8.14
## 26 13.9 13.9 0.84054 0.0 8.14
## 27 16.6 16.6 0.67191 0.0 8.14
## 28 14.8 14.8 0.95577 0.0 8.14
## 29 18.4 18.4 0.77299 0.0 8.14
## 30 21.0 21.0 1.00245 0.0 8.14
## 31 12.7 12.7 1.13081 0.0 8.14
## 32 14.5 14.5 1.35472 0.0 8.14
## 33 13.2 13.2 1.38799 0.0 8.14
## 34 13.1 13.1 1.15172 0.0 8.14
## 35 13.5 13.5 1.61282 0.0 8.14
## 36 18.9 18.9 0.06417 0.0 5.96
## 37 20.0 20.0 0.09744 0.0 5.96
## 38 21.0 21.0 0.08014 0.0 5.96
## 39 24.7 24.2 0.17505 0.0 5.96
## 40 30.8 30.8 0.02763 75.0 2.95
## 41 34.9 34.9 0.03359 75.0 2.95
## 42 26.6 26.6 0.12744 0.0 6.91
## 43 25.3 25.3 0.14150 0.0 6.91
## 44 24.7 24.7 0.15936 0.0 6.91
## 45 21.2 21.2 0.12269 0.0 6.91
## 46 19.3 19.3 0.17142 0.0 6.91
## 47 20.0 20.0 0.18836 0.0 6.91
## 48 16.6 16.6 0.22927 0.0 6.91
## 49 14.4 14.4 0.25387 0.0 6.91
## 50 19.4 19.4 0.21977 0.0 6.91
## 51 19.7 19.7 0.08873 21.0 5.64
## 52 20.5 20.5 0.04337 21.0 5.64
## 53 25.0 25.0 0.05360 21.0 5.64
## 54 23.4 23.4 0.04981 21.0 5.64
## 55 18.9 18.9 0.01360 75.0 4.00
## 56 35.4 35.4 0.01311 90.0 1.22
## 57 24.7 24.7 0.02055 85.0 0.74
## 58 31.6 31.6 0.01432 100.0 1.32
## 59 23.3 23.3 0.15445 25.0 5.13
## 60 19.6 19.6 0.10328 25.0 5.13
## 61 18.7 18.7 0.14932 25.0 5.13
## 62 16.0 16.0 0.17171 25.0 5.13
## 63 22.2 22.2 0.11027 25.0 5.13
## 64 25.0 25.0 0.12650 25.0 5.13
## 65 33.0 33.0 0.01951 17.5 1.38
## 66 23.5 23.5 0.03584 80.0 3.37
## 67 19.4 19.4 0.04379 80.0 3.37
## 68 22.0 22.0 0.05789 12.5 6.07
## 69 17.4 17.4 0.13554 12.5 6.07
## 70 20.9 20.9 0.12816 12.5 6.07
## 71 24.2 24.2 0.08826 0.0 10.81
## 72 21.7 21.7 0.15876 0.0 10.81
## 73 22.8 22.8 0.09164 0.0 10.81
## 74 23.4 23.4 0.19539 0.0 10.81
## 75 24.1 24.1 0.07896 0.0 12.83
## 76 21.4 21.4 0.09512 0.0 12.83
## 77 20.0 20.0 0.10153 0.0 12.83
## 78 20.8 20.8 0.08707 0.0 12.83
## 79 21.2 21.2 0.05646 0.0 12.83
## 80 20.3 20.3 0.08387 0.0 12.83
## 81 28.0 28.0 0.04113 25.0 4.86
## 82 23.9 23.9 0.04462 25.0 4.86
## 83 24.8 24.8 0.03659 25.0 4.86
## 84 22.9 22.9 0.03551 25.0 4.86
## 85 23.9 23.9 0.05059 0.0 4.49
## 86 26.6 26.6 0.05735 0.0 4.49
## 87 22.5 22.5 0.05188 0.0 4.49
## 88 22.2 22.2 0.07151 0.0 4.49
## 89 23.6 23.6 0.05660 0.0 3.41
## 90 28.7 28.7 0.05302 0.0 3.41
## 91 22.6 22.6 0.04684 0.0 3.41
## 92 22.0 22.0 0.03932 0.0 3.41
## 93 22.9 22.9 0.04203 28.0 15.04
## 94 25.0 25.0 0.02875 28.0 15.04
## 95 20.6 20.6 0.04294 28.0 15.04
## 96 28.4 28.4 0.12204 0.0 2.89
## 97 21.4 21.4 0.11504 0.0 2.89
## 98 38.7 38.7 0.12083 0.0 2.89
## 99 43.8 43.8 0.08187 0.0 2.89
## 100 33.2 33.2 0.06860 0.0 2.89
## 101 27.5 27.5 0.14866 0.0 8.56
## 102 26.5 26.5 0.11432 0.0 8.56
## 103 18.6 18.6 0.22876 0.0 8.56
## 104 19.3 19.3 0.21161 0.0 8.56
## 105 20.1 20.1 0.13960 0.0 8.56
## 106 19.5 19.5 0.13262 0.0 8.56
## 107 19.5 19.5 0.17120 0.0 8.56
## 108 20.4 20.4 0.13117 0.0 8.56
## 109 19.8 19.8 0.12802 0.0 8.56
## 110 19.4 19.4 0.26363 0.0 8.56
## 111 21.7 21.7 0.10793 0.0 8.56
## 112 22.8 22.8 0.10084 0.0 10.01
## 113 18.8 18.8 0.12329 0.0 10.01
## 114 18.7 18.7 0.22212 0.0 10.01
## 115 18.5 18.5 0.14231 0.0 10.01
## 116 18.3 18.3 0.17134 0.0 10.01
## 117 21.2 21.2 0.13158 0.0 10.01
## 118 19.2 19.2 0.15098 0.0 10.01
## 119 20.4 20.4 0.13058 0.0 10.01
## 120 19.3 19.3 0.14476 0.0 10.01
## 121 22.0 22.0 0.06899 0.0 25.65
## 122 20.3 20.3 0.07165 0.0 25.65
## 123 20.5 20.5 0.09299 0.0 25.65
## 124 17.3 17.3 0.15038 0.0 25.65
## 125 18.8 18.8 0.09849 0.0 25.65
## 126 21.4 21.4 0.16902 0.0 25.65
## 127 15.7 15.7 0.38735 0.0 25.65
## 128 16.2 16.2 0.25915 0.0 21.89
## 129 18.0 18.0 0.32543 0.0 21.89
## 130 14.3 14.3 0.88125 0.0 21.89
## 131 19.2 19.2 0.34006 0.0 21.89
## 132 19.6 19.6 1.19294 0.0 21.89
## 133 23.0 23.0 0.59005 0.0 21.89
## 134 18.4 18.4 0.32982 0.0 21.89
## 135 15.6 15.6 0.97617 0.0 21.89
## 136 18.1 18.1 0.55778 0.0 21.89
## 137 17.4 17.4 0.32264 0.0 21.89
## 138 17.1 17.1 0.35233 0.0 21.89
## 139 13.3 13.3 0.24980 0.0 21.89
## 140 17.8 17.8 0.54452 0.0 21.89
## 141 14.0 14.0 0.29090 0.0 21.89
## 142 14.4 14.4 1.62864 0.0 21.89
## 143 13.4 13.4 3.32105 0.0 19.58
## 144 15.6 15.6 4.09740 0.0 19.58
## 145 11.8 11.8 2.77974 0.0 19.58
## 146 13.8 13.8 2.37934 0.0 19.58
## 147 15.6 15.6 2.15505 0.0 19.58
## 148 14.6 14.6 2.36862 0.0 19.58
## 149 17.8 17.8 2.33099 0.0 19.58
## 150 15.4 15.4 2.73397 0.0 19.58
## 151 21.5 21.5 1.65660 0.0 19.58
## 152 19.6 19.6 1.49632 0.0 19.58
## 153 15.3 15.3 1.12658 0.0 19.58
## 154 19.4 19.4 2.14918 0.0 19.58
## 155 17.0 17.0 1.41385 0.0 19.58
## 156 15.6 15.6 3.53501 0.0 19.58
## 157 13.1 13.1 2.44668 0.0 19.58
## 158 41.3 41.3 1.22358 0.0 19.58
## 159 24.3 24.3 1.34284 0.0 19.58
## 160 23.3 23.3 1.42502 0.0 19.58
## 161 27.0 27.0 1.27346 0.0 19.58
## 162 50.0 50.0 1.46336 0.0 19.58
## 163 50.0 50.0 1.83377 0.0 19.58
## 164 50.0 50.0 1.51902 0.0 19.58
## 165 22.7 22.7 2.24236 0.0 19.58
## 166 25.0 25.0 2.92400 0.0 19.58
## 167 50.0 50.0 2.01019 0.0 19.58
## 168 23.8 23.8 1.80028 0.0 19.58
## 169 23.8 23.8 2.30040 0.0 19.58
## 170 22.3 22.3 2.44953 0.0 19.58
## 171 17.4 17.4 1.20742 0.0 19.58
## 172 19.1 19.1 2.31390 0.0 19.58
## 173 23.1 23.1 0.13914 0.0 4.05
## 174 23.6 23.6 0.09178 0.0 4.05
## 175 22.6 22.6 0.08447 0.0 4.05
## 176 29.4 29.4 0.06664 0.0 4.05
## 177 23.2 23.2 0.07022 0.0 4.05
## 178 24.6 24.6 0.05425 0.0 4.05
## 179 29.9 29.9 0.06642 0.0 4.05
## 180 37.2 37.2 0.05780 0.0 2.46
## 181 39.8 39.8 0.06588 0.0 2.46
## 182 36.2 36.2 0.06888 0.0 2.46
## 183 37.9 37.9 0.09103 0.0 2.46
## 184 32.5 32.5 0.10008 0.0 2.46
## 185 26.4 26.4 0.08308 0.0 2.46
## 186 29.6 29.6 0.06047 0.0 2.46
## 187 50.0 50.0 0.05602 0.0 2.46
## 188 32.0 32.0 0.07875 45.0 3.44
## 189 29.8 29.8 0.12579 45.0 3.44
## 190 34.9 34.9 0.08370 45.0 3.44
## 191 37.0 33.0 0.09068 45.0 3.44
## 192 30.5 30.5 0.06911 45.0 3.44
## 193 36.4 36.4 0.08664 45.0 3.44
## 194 31.1 31.1 0.02187 60.0 2.93
## 195 29.1 29.1 0.01439 60.0 2.93
## 196 50.0 50.0 0.01381 80.0 0.46
## 197 33.3 33.3 0.04011 80.0 1.52
## 198 30.3 30.3 0.04666 80.0 1.52
## 199 34.6 34.6 0.03768 80.0 1.52
## 200 34.9 34.9 0.03150 95.0 1.47
## 201 32.9 32.9 0.01778 95.0 1.47
## 202 24.1 24.1 0.03445 82.5 2.03
## 203 42.3 42.3 0.02177 82.5 2.03
## 204 48.5 48.5 0.03510 95.0 2.68
## 205 50.0 50.0 0.02009 95.0 2.68
## 206 22.6 22.6 0.13642 0.0 10.59
## 207 24.4 24.4 0.22969 0.0 10.59
## 208 22.5 22.5 0.25199 0.0 10.59
## 209 24.4 24.4 0.13587 0.0 10.59
## 210 20.0 20.0 0.43571 0.0 10.59
## 211 21.7 21.7 0.17446 0.0 10.59
## 212 19.3 19.3 0.37578 0.0 10.59
## 213 22.4 22.4 0.21719 0.0 10.59
## 214 28.1 28.1 0.14052 0.0 10.59
## 215 23.7 23.7 0.28955 0.0 10.59
## 216 25.0 25.0 0.19802 0.0 10.59
## 217 23.3 23.3 0.04560 0.0 13.89
## 218 28.7 28.7 0.07013 0.0 13.89
## 219 21.5 21.5 0.11069 0.0 13.89
## 220 23.0 23.0 0.11425 0.0 13.89
## 221 26.7 26.7 0.35809 0.0 6.20
## 222 21.7 21.7 0.40771 0.0 6.20
## 223 27.5 27.5 0.62356 0.0 6.20
## 224 30.1 30.1 0.61470 0.0 6.20
## 225 44.8 44.8 0.31533 0.0 6.20
## 226 50.0 50.0 0.52693 0.0 6.20
## 227 37.6 37.6 0.38214 0.0 6.20
## 228 31.6 31.6 0.41238 0.0 6.20
## 229 46.7 46.7 0.29819 0.0 6.20
## 230 31.5 31.5 0.44178 0.0 6.20
## 231 24.3 24.3 0.53700 0.0 6.20
## 232 31.7 31.7 0.46296 0.0 6.20
## 233 41.7 41.7 0.57529 0.0 6.20
## 234 48.3 48.3 0.33147 0.0 6.20
## 235 29.0 29.0 0.44791 0.0 6.20
## 236 24.0 24.0 0.33045 0.0 6.20
## 237 25.1 25.1 0.52058 0.0 6.20
## 238 31.5 31.5 0.51183 0.0 6.20
## 239 23.7 23.7 0.08244 30.0 4.93
## 240 23.3 23.3 0.09252 30.0 4.93
## 241 22.0 27.0 0.11329 30.0 4.93
## 242 20.1 20.1 0.10612 30.0 4.93
## 243 22.2 22.2 0.10290 30.0 4.93
## 244 23.7 23.7 0.12757 30.0 4.93
## 245 17.6 17.6 0.20608 22.0 5.86
## 246 18.5 18.5 0.19133 22.0 5.86
## 247 24.3 24.3 0.33983 22.0 5.86
## 248 20.5 20.5 0.19657 22.0 5.86
## 249 24.5 24.5 0.16439 22.0 5.86
## 250 26.2 26.2 0.19073 22.0 5.86
## 251 24.4 24.4 0.14030 22.0 5.86
## 252 24.8 24.8 0.21409 22.0 5.86
## 253 29.6 29.6 0.08221 22.0 5.86
## 254 42.8 42.8 0.36894 22.0 5.86
## 255 21.9 21.9 0.04819 80.0 3.64
## 256 20.9 20.9 0.03548 80.0 3.64
## 257 44.0 44.0 0.01538 90.0 3.75
## 258 50.0 50.0 0.61154 20.0 3.97
## 259 36.0 36.0 0.66351 20.0 3.97
## 260 30.1 30.1 0.65665 20.0 3.97
## 261 33.8 33.8 0.54011 20.0 3.97
## 262 43.1 43.1 0.53412 20.0 3.97
## 263 48.8 48.8 0.52014 20.0 3.97
## 264 31.0 31.0 0.82526 20.0 3.97
## 265 36.5 36.5 0.55007 20.0 3.97
## 266 22.8 22.8 0.76162 20.0 3.97
## 267 30.7 30.7 0.78570 20.0 3.97
## 268 50.0 50.0 0.57834 20.0 3.97
## 269 43.5 43.5 0.54050 20.0 3.97
## 270 20.7 20.7 0.09065 20.0 6.96
## 271 21.1 21.1 0.29916 20.0 6.96
## 272 25.2 25.2 0.16211 20.0 6.96
## 273 24.4 24.4 0.11460 20.0 6.96
## 274 35.2 35.2 0.22188 20.0 6.96
## 275 32.4 32.4 0.05644 40.0 6.41
## 276 32.0 32.0 0.09604 40.0 6.41
## 277 33.2 33.2 0.10469 40.0 6.41
## 278 33.1 33.1 0.06127 40.0 6.41
## 279 29.1 29.1 0.07978 40.0 6.41
## 280 35.1 35.1 0.21038 20.0 3.33
## 281 45.4 45.4 0.03578 20.0 3.33
## 282 35.4 35.4 0.03705 20.0 3.33
## 283 46.0 46.0 0.06129 20.0 3.33
## 284 50.0 50.0 0.01501 90.0 1.21
## 285 32.2 32.2 0.00906 90.0 2.97
## 286 22.0 22.0 0.01096 55.0 2.25
## 287 20.1 20.1 0.01965 80.0 1.76
## 288 23.2 23.2 0.03871 52.5 5.32
## 289 22.3 22.3 0.04590 52.5 5.32
## 290 24.8 24.8 0.04297 52.5 5.32
## 291 28.5 28.5 0.03502 80.0 4.95
## 292 37.3 37.3 0.07886 80.0 4.95
## 293 27.9 27.9 0.03615 80.0 4.95
## 294 23.9 23.9 0.08265 0.0 13.92
## 295 21.7 21.7 0.08199 0.0 13.92
## 296 28.6 28.6 0.12932 0.0 13.92
## 297 27.1 27.1 0.05372 0.0 13.92
## 298 20.3 20.3 0.14103 0.0 13.92
## 299 22.5 22.5 0.06466 70.0 2.24
## 300 29.0 29.0 0.05561 70.0 2.24
## 301 24.8 24.8 0.04417 70.0 2.24
## 302 22.0 22.0 0.03537 34.0 6.09
## 303 26.4 26.4 0.09266 34.0 6.09
## 304 33.1 33.1 0.10000 34.0 6.09
## 305 36.1 36.1 0.05515 33.0 2.18
## 306 28.4 28.4 0.05479 33.0 2.18
## 307 33.4 33.4 0.07503 33.0 2.18
## 308 28.2 28.2 0.04932 33.0 2.18
## 309 22.8 22.8 0.49298 0.0 9.90
## 310 20.3 20.3 0.34940 0.0 9.90
## 311 16.1 16.1 2.63548 0.0 9.90
## 312 22.1 22.1 0.79041 0.0 9.90
## 313 19.4 19.4 0.26169 0.0 9.90
## 314 21.6 21.6 0.26938 0.0 9.90
## 315 23.8 23.8 0.36920 0.0 9.90
## 316 16.2 16.2 0.25356 0.0 9.90
## 317 17.8 17.8 0.31827 0.0 9.90
## 318 19.8 19.8 0.24522 0.0 9.90
## 319 23.1 23.1 0.40202 0.0 9.90
## 320 21.0 21.0 0.47547 0.0 9.90
## 321 23.8 23.8 0.16760 0.0 7.38
## 322 23.1 23.1 0.18159 0.0 7.38
## 323 20.4 20.4 0.35114 0.0 7.38
## 324 18.5 18.5 0.28392 0.0 7.38
## 325 25.0 25.0 0.34109 0.0 7.38
## 326 24.6 24.6 0.19186 0.0 7.38
## 327 23.0 23.0 0.30347 0.0 7.38
## 328 22.2 22.2 0.24103 0.0 7.38
## 329 19.3 19.3 0.06617 0.0 3.24
## 330 22.6 22.6 0.06724 0.0 3.24
## 331 19.8 19.8 0.04544 0.0 3.24
## 332 17.1 17.1 0.05023 35.0 6.06
## 333 19.4 19.4 0.03466 35.0 6.06
## 334 22.2 22.2 0.05083 0.0 5.19
## 335 20.7 20.7 0.03738 0.0 5.19
## 336 21.1 21.1 0.03961 0.0 5.19
## 337 19.5 19.5 0.03427 0.0 5.19
## 338 18.5 18.5 0.03041 0.0 5.19
## 339 20.6 20.6 0.03306 0.0 5.19
## 340 19.0 19.0 0.05497 0.0 5.19
## 341 18.7 18.7 0.06151 0.0 5.19
## 342 32.7 32.7 0.01301 35.0 1.52
## 343 16.5 16.5 0.02498 0.0 1.89
## 344 23.9 23.9 0.02543 55.0 3.78
## 345 31.2 31.2 0.03049 55.0 3.78
## 346 17.5 17.5 0.03113 0.0 4.39
## 347 17.2 17.2 0.06162 0.0 4.39
## 348 23.1 23.1 0.01870 85.0 4.15
## 349 24.5 24.5 0.01501 80.0 2.01
## 350 26.6 26.6 0.02899 40.0 1.25
## 351 22.9 22.9 0.06211 40.0 1.25
## 352 24.1 24.1 0.07950 60.0 1.69
## 353 18.6 18.6 0.07244 60.0 1.69
## 354 30.1 30.1 0.01709 90.0 2.02
## 355 18.2 18.2 0.04301 80.0 1.91
## 356 20.6 20.6 0.10659 80.0 1.91
## 357 17.8 17.8 8.98296 0.0 18.10
## 358 21.7 21.7 3.84970 0.0 18.10
## 359 22.7 22.7 5.20177 0.0 18.10
## 360 22.6 22.6 4.26131 0.0 18.10
## 361 25.0 25.0 4.54192 0.0 18.10
## 362 19.9 19.9 3.83684 0.0 18.10
## 363 20.8 20.8 3.67822 0.0 18.10
## 364 16.8 16.8 4.22239 0.0 18.10
## 365 21.9 21.9 3.47428 0.0 18.10
## 366 27.5 27.5 4.55587 0.0 18.10
## 367 21.9 21.9 3.69695 0.0 18.10
## 368 23.1 23.1 13.52220 0.0 18.10
## 369 50.0 50.0 4.89822 0.0 18.10
## 370 50.0 50.0 5.66998 0.0 18.10
## 371 50.0 50.0 6.53876 0.0 18.10
## 372 50.0 50.0 9.23230 0.0 18.10
## 373 50.0 50.0 8.26725 0.0 18.10
## 374 13.8 13.8 11.10810 0.0 18.10
## 375 13.8 13.8 18.49820 0.0 18.10
## 376 15.0 15.0 19.60910 0.0 18.10
## 377 13.9 13.9 15.28800 0.0 18.10
## 378 13.3 13.3 9.82349 0.0 18.10
## 379 13.1 13.1 23.64820 0.0 18.10
## 380 10.2 10.2 17.86670 0.0 18.10
## 381 10.4 10.4 88.97620 0.0 18.10
## 382 10.9 10.9 15.87440 0.0 18.10
## 383 11.3 11.3 9.18702 0.0 18.10
## 384 12.3 12.3 7.99248 0.0 18.10
## 385 8.8 8.8 20.08490 0.0 18.10
## 386 7.2 7.2 16.81180 0.0 18.10
## 387 10.5 10.5 24.39380 0.0 18.10
## 388 7.4 7.4 22.59710 0.0 18.10
## 389 10.2 10.2 14.33370 0.0 18.10
## 390 11.5 11.5 8.15174 0.0 18.10
## 391 15.1 15.1 6.96215 0.0 18.10
## 392 23.2 23.2 5.29305 0.0 18.10
## 393 9.7 9.7 11.57790 0.0 18.10
## 394 13.8 13.8 8.64476 0.0 18.10
## 395 12.7 12.7 13.35980 0.0 18.10
## 396 13.1 13.1 8.71675 0.0 18.10
## 397 12.5 12.5 5.87205 0.0 18.10
## 398 8.5 8.5 7.67202 0.0 18.10
## 399 5.0 5.0 38.35180 0.0 18.10
## 400 6.3 6.3 9.91655 0.0 18.10
## 401 5.6 5.6 25.04610 0.0 18.10
## 402 7.2 7.2 14.23620 0.0 18.10
## 403 12.1 12.1 9.59571 0.0 18.10
## 404 8.3 8.3 24.80170 0.0 18.10
## 405 8.5 8.5 41.52920 0.0 18.10
## 406 5.0 5.0 67.92080 0.0 18.10
## 407 11.9 11.9 20.71620 0.0 18.10
## 408 27.9 27.9 11.95110 0.0 18.10
## 409 17.2 17.2 7.40389 0.0 18.10
## 410 27.5 27.5 14.43830 0.0 18.10
## 411 15.0 15.0 51.13580 0.0 18.10
## 412 17.2 17.2 14.05070 0.0 18.10
## 413 17.9 17.9 18.81100 0.0 18.10
## 414 16.3 16.3 28.65580 0.0 18.10
## 415 7.0 7.0 45.74610 0.0 18.10
## 416 7.2 7.2 18.08460 0.0 18.10
## 417 7.5 7.5 10.83420 0.0 18.10
## 418 10.4 10.4 25.94060 0.0 18.10
## 419 8.8 8.8 73.53410 0.0 18.10
## 420 8.4 8.4 11.81230 0.0 18.10
## 421 16.7 16.7 11.08740 0.0 18.10
## 422 14.2 14.2 7.02259 0.0 18.10
## 423 20.8 20.8 12.04820 0.0 18.10
## 424 13.4 13.4 7.05042 0.0 18.10
## 425 11.7 11.7 8.79212 0.0 18.10
## 426 8.3 8.3 15.86030 0.0 18.10
## 427 10.2 10.2 12.24720 0.0 18.10
## 428 10.9 10.9 37.66190 0.0 18.10
## 429 11.0 11.0 7.36711 0.0 18.10
## 430 9.5 9.5 9.33889 0.0 18.10
## 431 14.5 14.5 8.49213 0.0 18.10
## 432 14.1 14.1 10.06230 0.0 18.10
## 433 16.1 16.1 6.44405 0.0 18.10
## 434 14.3 14.3 5.58107 0.0 18.10
## 435 11.7 11.7 13.91340 0.0 18.10
## 436 13.4 13.4 11.16040 0.0 18.10
## 437 9.6 9.6 14.42080 0.0 18.10
## 438 8.7 8.2 15.17720 0.0 18.10
## 439 8.4 8.4 13.67810 0.0 18.10
## 440 12.8 12.8 9.39063 0.0 18.10
## 441 10.5 10.5 22.05110 0.0 18.10
## 442 17.1 17.1 9.72418 0.0 18.10
## 443 18.4 14.8 5.66637 0.0 18.10
## 444 15.4 15.4 9.96654 0.0 18.10
## 445 10.8 10.8 12.80230 0.0 18.10
## 446 11.8 11.8 10.67180 0.0 18.10
## 447 14.9 14.9 6.28807 0.0 18.10
## 448 12.6 12.6 9.92485 0.0 18.10
## 449 14.1 14.1 9.32909 0.0 18.10
## 450 13.0 13.0 7.52601 0.0 18.10
## 451 13.4 13.4 6.71772 0.0 18.10
## 452 15.2 15.2 5.44114 0.0 18.10
## 453 16.1 16.1 5.09017 0.0 18.10
## 454 17.8 17.8 8.24809 0.0 18.10
## 455 14.9 14.4 9.51363 0.0 18.10
## 456 14.1 14.1 4.75237 0.0 18.10
## 457 12.7 12.7 4.66883 0.0 18.10
## 458 13.5 13.5 8.20058 0.0 18.10
## 459 14.9 14.9 7.75223 0.0 18.10
## 460 20.0 20.0 6.80117 0.0 18.10
## 461 16.4 16.4 4.81213 0.0 18.10
## 462 17.7 17.7 3.69311 0.0 18.10
## 463 19.5 19.5 6.65492 0.0 18.10
## 464 20.2 20.2 5.82115 0.0 18.10
## 465 21.4 21.4 7.83932 0.0 18.10
## 466 19.9 19.9 3.16360 0.0 18.10
## 467 19.0 19.0 3.77498 0.0 18.10
## 468 19.1 19.1 4.42228 0.0 18.10
## 469 19.1 19.1 15.57570 0.0 18.10
## 470 20.1 20.1 13.07510 0.0 18.10
## 471 19.9 19.9 4.34879 0.0 18.10
## 472 19.6 19.6 4.03841 0.0 18.10
## 473 23.2 23.2 3.56868 0.0 18.10
## 474 29.8 29.8 4.64689 0.0 18.10
## 475 13.8 13.8 8.05579 0.0 18.10
## 476 13.3 13.3 6.39312 0.0 18.10
## 477 16.7 16.7 4.87141 0.0 18.10
## 478 12.0 12.0 15.02340 0.0 18.10
## 479 14.6 14.6 10.23300 0.0 18.10
## 480 21.4 21.4 14.33370 0.0 18.10
## 481 23.0 23.0 5.82401 0.0 18.10
## 482 23.7 23.7 5.70818 0.0 18.10
## 483 25.0 25.0 5.73116 0.0 18.10
## 484 21.8 21.8 2.81838 0.0 18.10
## 485 20.6 20.6 2.37857 0.0 18.10
## 486 21.2 21.2 3.67367 0.0 18.10
## 487 19.1 19.1 5.69175 0.0 18.10
## 488 20.6 20.6 4.83567 0.0 18.10
## 489 15.2 15.2 0.15086 0.0 27.74
## 490 7.0 7.0 0.18337 0.0 27.74
## 491 8.1 8.1 0.20746 0.0 27.74
## 492 13.6 13.6 0.10574 0.0 27.74
## 493 20.1 20.1 0.11132 0.0 27.74
## 494 21.8 21.8 0.17331 0.0 9.69
## 495 24.5 24.5 0.27957 0.0 9.69
## 496 23.1 23.1 0.17899 0.0 9.69
## 497 19.7 19.7 0.28960 0.0 9.69
## 498 18.3 18.3 0.26838 0.0 9.69
## 499 21.2 21.2 0.23912 0.0 9.69
## 500 17.5 17.5 0.17783 0.0 9.69
## 501 16.8 16.8 0.22438 0.0 9.69
## 502 22.4 22.4 0.06263 0.0 11.93
## 503 20.6 20.6 0.04527 0.0 11.93
## 504 23.9 23.9 0.06076 0.0 11.93
## 505 22.0 22.0 0.10959 0.0 11.93
## 506 11.9 19.0 0.04741 0.0 11.93
## river_view nitric_oxid rooms age distance access_to_highways
## 1 0 0.5380 6.575 65.2 4.0900 1
## 2 0 0.4690 6.421 78.9 4.9671 2
## 3 0 0.4690 7.185 61.1 4.9671 2
## 4 0 0.4580 6.998 45.8 6.0622 3
## 5 0 0.4580 7.147 54.2 6.0622 3
## 6 0 0.4580 6.430 58.7 6.0622 3
## 7 0 0.5240 6.012 66.6 5.5605 5
## 8 0 0.5240 6.172 96.1 5.9505 5
## 9 0 0.5240 5.631 100.0 6.0821 5
## 10 0 0.5240 6.004 85.9 6.5921 5
## 11 0 0.5240 6.377 94.3 6.3467 5
## 12 0 0.5240 6.009 82.9 6.2267 5
## 13 0 0.5240 5.889 39.0 5.4509 5
## 14 0 0.5380 5.949 61.8 4.7075 4
## 15 0 0.5380 6.096 84.5 4.4619 4
## 16 0 0.5380 5.834 56.5 4.4986 4
## 17 0 0.5380 5.935 29.3 4.4986 4
## 18 0 0.5380 5.990 81.7 4.2579 4
## 19 0 0.5380 5.456 36.6 3.7965 4
## 20 0 0.5380 5.727 69.5 3.7965 4
## 21 0 0.5380 5.570 98.1 3.7979 4
## 22 0 0.5380 5.965 89.2 4.0123 4
## 23 0 0.5380 6.142 91.7 3.9769 4
## 24 0 0.5380 5.813 100.0 4.0952 4
## 25 0 0.5380 5.924 94.1 4.3996 4
## 26 0 0.5380 5.599 85.7 4.4546 4
## 27 0 0.5380 5.813 90.3 4.6820 4
## 28 0 0.5380 6.047 88.8 4.4534 4
## 29 0 0.5380 6.495 94.4 4.4547 4
## 30 0 0.5380 6.674 87.3 4.2390 4
## 31 0 0.5380 5.713 94.1 4.2330 4
## 32 0 0.5380 6.072 100.0 4.1750 4
## 33 0 0.5380 5.950 82.0 3.9900 4
## 34 0 0.5380 5.701 95.0 3.7872 4
## 35 0 0.5380 6.096 96.9 3.7598 4
## 36 0 0.4990 5.933 68.2 3.3603 5
## 37 0 0.4990 5.841 61.4 3.3779 5
## 38 0 0.4990 5.850 41.5 3.9342 5
## 39 0 0.4990 5.966 30.2 3.8473 5
## 40 0 0.4280 6.595 21.8 5.4011 3
## 41 0 0.4280 7.024 15.8 5.4011 3
## 42 0 0.4480 6.770 2.9 5.7209 3
## 43 0 0.4480 6.169 6.6 5.7209 3
## 44 0 0.4480 6.211 6.5 5.7209 3
## 45 0 0.4480 6.069 40.0 5.7209 3
## 46 0 0.4480 5.682 33.8 5.1004 3
## 47 0 0.4480 5.786 33.3 5.1004 3
## 48 0 0.4480 6.030 85.5 5.6894 3
## 49 0 0.4480 5.399 95.3 5.8700 3
## 50 0 0.4480 5.602 62.0 6.0877 3
## 51 0 0.4390 5.963 45.7 6.8147 4
## 52 0 0.4390 6.115 63.0 6.8147 4
## 53 0 0.4390 6.511 21.1 6.8147 4
## 54 0 0.4390 5.998 21.4 6.8147 4
## 55 0 0.4100 5.888 47.6 7.3197 3
## 56 0 0.4030 7.249 21.9 8.6966 5
## 57 0 0.4100 6.383 35.7 9.1876 2
## 58 0 0.4110 6.816 40.5 8.3248 5
## 59 0 0.4530 6.145 29.2 7.8148 8
## 60 0 0.4530 5.927 47.2 6.9320 8
## 61 0 0.4530 5.741 66.2 7.2254 8
## 62 0 0.4530 5.966 93.4 6.8185 8
## 63 0 0.4530 6.456 67.8 7.2255 8
## 64 0 0.4530 6.762 43.4 7.9809 8
## 65 0 0.4161 7.104 59.5 9.2229 3
## 66 0 0.3980 6.290 17.8 6.6115 4
## 67 0 0.3980 5.787 31.1 6.6115 4
## 68 0 0.4090 5.878 21.4 6.4980 4
## 69 0 0.4090 5.594 36.8 6.4980 4
## 70 0 0.4090 5.885 33.0 6.4980 4
## 71 0 0.4130 6.417 6.6 5.2873 4
## 72 0 0.4130 5.961 17.5 5.2873 4
## 73 0 0.4130 6.065 7.8 5.2873 4
## 74 0 0.4130 6.245 6.2 5.2873 4
## 75 0 0.4370 6.273 6.0 4.2515 5
## 76 0 0.4370 6.286 45.0 4.5026 5
## 77 0 0.4370 6.279 74.5 4.0522 5
## 78 0 0.4370 6.140 45.8 4.0905 5
## 79 0 0.4370 6.232 53.7 5.0141 5
## 80 0 0.4370 5.874 36.6 4.5026 5
## 81 0 0.4260 6.727 33.5 5.4007 4
## 82 0 0.4260 6.619 70.4 5.4007 4
## 83 0 0.4260 6.302 32.2 5.4007 4
## 84 0 0.4260 6.167 46.7 5.4007 4
## 85 0 0.4490 6.389 48.0 4.7794 3
## 86 0 0.4490 6.630 56.1 4.4377 3
## 87 0 0.4490 6.015 45.1 4.4272 3
## 88 0 0.4490 6.121 56.8 3.7476 3
## 89 0 0.4890 7.007 86.3 3.4217 2
## 90 0 0.4890 7.079 63.1 3.4145 2
## 91 0 0.4890 6.417 66.1 3.0923 2
## 92 0 0.4890 6.405 73.9 3.0921 2
## 93 0 0.4640 6.442 53.6 3.6659 4
## 94 0 0.4640 6.211 28.9 3.6659 4
## 95 0 0.4640 6.249 77.3 3.6150 4
## 96 0 0.4450 6.625 57.8 3.4952 2
## 97 0 0.4450 6.163 69.6 3.4952 2
## 98 0 0.4450 8.069 76.0 3.4952 2
## 99 0 0.4450 7.820 36.9 3.4952 2
## 100 0 0.4450 7.416 62.5 3.4952 2
## 101 0 0.5200 6.727 79.9 2.7778 5
## 102 0 0.5200 6.781 71.3 2.8561 5
## 103 0 0.5200 6.405 85.4 2.7147 5
## 104 0 0.5200 6.137 87.4 2.7147 5
## 105 0 0.5200 6.167 90.0 2.4210 5
## 106 0 0.5200 5.851 96.7 2.1069 5
## 107 0 0.5200 5.836 91.9 2.2110 5
## 108 0 0.5200 6.127 85.2 2.1224 5
## 109 0 0.5200 6.474 97.1 2.4329 5
## 110 0 0.5200 6.229 91.2 2.5451 5
## 111 0 0.5200 6.195 54.4 2.7778 5
## 112 0 0.5470 6.715 81.6 2.6775 6
## 113 0 0.5470 5.913 92.9 2.3534 6
## 114 0 0.5470 6.092 95.4 2.5480 6
## 115 0 0.5470 6.254 84.2 2.2565 6
## 116 0 0.5470 5.928 88.2 2.4631 6
## 117 0 0.5470 6.176 72.5 2.7301 6
## 118 0 0.5470 6.021 82.6 2.7474 6
## 119 0 0.5470 5.872 73.1 2.4775 6
## 120 0 0.5470 5.731 65.2 2.7592 6
## 121 0 0.5810 5.870 69.7 2.2577 2
## 122 0 0.5810 6.004 84.1 2.1974 2
## 123 0 0.5810 5.961 92.9 2.0869 2
## 124 0 0.5810 5.856 97.0 1.9444 2
## 125 0 0.5810 5.879 95.8 2.0063 2
## 126 0 0.5810 5.986 88.4 1.9929 2
## 127 0 0.5810 5.613 95.6 1.7572 2
## 128 0 0.6240 5.693 96.0 1.7883 4
## 129 0 0.6240 6.431 98.8 1.8125 4
## 130 0 0.6240 5.637 94.7 1.9799 4
## 131 0 0.6240 6.458 98.9 2.1185 4
## 132 0 0.6240 6.326 97.7 2.2710 4
## 133 0 0.6240 6.372 97.9 2.3274 4
## 134 0 0.6240 5.822 95.4 2.4699 4
## 135 0 0.6240 5.757 98.4 2.3460 4
## 136 0 0.6240 6.335 98.2 2.1107 4
## 137 0 0.6240 5.942 93.5 1.9669 4
## 138 0 0.6240 6.454 98.4 1.8498 4
## 139 0 0.6240 5.857 98.2 1.6686 4
## 140 0 0.6240 6.151 97.9 1.6687 4
## 141 0 0.6240 6.174 93.6 1.6119 4
## 142 0 0.6240 5.019 100.0 1.4394 4
## 143 1 0.8710 5.403 100.0 1.3216 5
## 144 0 0.8710 5.468 100.0 1.4118 5
## 145 0 0.8710 4.903 97.8 1.3459 5
## 146 0 0.8710 6.130 100.0 1.4191 5
## 147 0 0.8710 5.628 100.0 1.5166 5
## 148 0 0.8710 4.926 95.7 1.4608 5
## 149 0 0.8710 5.186 93.8 1.5296 5
## 150 0 0.8710 5.597 94.9 1.5257 5
## 151 0 0.8710 6.122 97.3 1.6180 5
## 152 0 0.8710 5.404 100.0 1.5916 5
## 153 1 0.8710 5.012 88.0 1.6102 5
## 154 0 0.8710 5.709 98.5 1.6232 5
## 155 1 0.8710 6.129 96.0 1.7494 5
## 156 1 0.8710 6.152 82.6 1.7455 5
## 157 0 0.8710 5.272 94.0 1.7364 5
## 158 0 0.6050 6.943 97.4 1.8773 5
## 159 0 0.6050 6.066 100.0 1.7573 5
## 160 0 0.8710 6.510 100.0 1.7659 5
## 161 1 0.6050 6.250 92.6 1.7984 5
## 162 0 0.6050 7.489 90.8 1.9709 5
## 163 1 0.6050 7.802 98.2 2.0407 5
## 164 1 0.6050 8.375 93.9 2.1620 5
## 165 0 0.6050 5.854 91.8 2.4220 5
## 166 0 0.6050 6.101 93.0 2.2834 5
## 167 0 0.6050 7.929 96.2 2.0459 5
## 168 0 0.6050 5.877 79.2 2.4259 5
## 169 0 0.6050 6.319 96.1 2.1000 5
## 170 0 0.6050 6.402 95.2 2.2625 5
## 171 0 0.6050 5.875 94.6 2.4259 5
## 172 0 0.6050 5.880 97.3 2.3887 5
## 173 0 0.5100 5.572 88.5 2.5961 5
## 174 0 0.5100 6.416 84.1 2.6463 5
## 175 0 0.5100 5.859 68.7 2.7019 5
## 176 0 0.5100 6.546 33.1 3.1323 5
## 177 0 0.5100 6.020 47.2 3.5549 5
## 178 0 0.5100 6.315 73.4 3.3175 5
## 179 0 0.5100 6.860 74.4 2.9153 5
## 180 0 0.4880 6.980 58.4 2.8290 3
## 181 0 0.4880 7.765 83.3 2.7410 3
## 182 0 0.4880 6.144 62.2 2.5979 3
## 183 0 0.4880 7.155 92.2 2.7006 3
## 184 0 0.4880 6.563 95.6 2.8470 3
## 185 0 0.4880 5.604 89.8 2.9879 3
## 186 0 0.4880 6.153 68.8 3.2797 3
## 187 0 0.4880 7.831 53.6 3.1992 3
## 188 0 0.4370 6.782 41.1 3.7886 5
## 189 0 0.4370 6.556 29.1 4.5667 5
## 190 0 0.4370 7.185 38.9 4.5667 5
## 191 0 0.4370 6.951 21.5 6.4798 5
## 192 0 0.4370 6.739 30.8 6.4798 5
## 193 0 0.4370 7.178 26.3 6.4798 5
## 194 0 0.4010 6.800 9.9 6.2196 1
## 195 0 0.4010 6.604 18.8 6.2196 1
## 196 0 0.4220 7.875 32.0 5.6484 4
## 197 0 0.4040 7.287 34.1 7.3090 2
## 198 0 0.4040 7.107 36.6 7.3090 2
## 199 0 0.4040 7.274 38.3 7.3090 2
## 200 0 0.4030 6.975 15.3 7.6534 3
## 201 0 0.4030 7.135 13.9 7.6534 3
## 202 0 0.4150 6.162 38.4 6.2700 2
## 203 0 0.4150 7.610 15.7 6.2700 2
## 204 0 0.4161 7.853 33.2 5.1180 4
## 205 0 0.4161 8.034 31.9 5.1180 4
## 206 0 0.4890 5.891 22.3 3.9454 4
## 207 0 0.4890 6.326 52.5 4.3549 4
## 208 0 0.4890 5.783 72.7 4.3549 4
## 209 1 0.4890 6.064 59.1 4.2392 4
## 210 1 0.4890 5.344 100.0 3.8750 4
## 211 1 0.4890 5.960 92.1 3.8771 4
## 212 1 0.4890 5.404 88.6 3.6650 4
## 213 1 0.4890 5.807 53.8 3.6526 4
## 214 0 0.4890 6.375 32.3 3.9454 4
## 215 0 0.4890 5.412 9.8 3.5875 4
## 216 0 0.4890 6.182 42.4 3.9454 4
## 217 1 0.5500 5.888 56.0 3.1121 5
## 218 0 0.5500 6.642 85.1 3.4211 5
## 219 1 0.5500 5.951 93.8 2.8893 5
## 220 1 0.5500 6.373 92.4 3.3633 5
## 221 1 0.5070 6.951 88.5 2.8617 8
## 222 1 0.5070 6.164 91.3 3.0480 8
## 223 1 0.5070 6.879 77.7 3.2721 8
## 224 0 0.5070 6.618 80.8 3.2721 8
## 225 0 0.5040 8.266 78.3 2.8944 8
## 226 0 0.5040 8.725 83.0 2.8944 8
## 227 0 0.5040 8.040 86.5 3.2157 8
## 228 0 0.5040 7.163 79.9 3.2157 8
## 229 0 0.5040 7.686 17.0 3.3751 8
## 230 0 0.5040 6.552 21.4 3.3751 8
## 231 0 0.5040 5.981 68.1 3.6715 8
## 232 0 0.5040 7.412 76.9 3.6715 8
## 233 0 0.5070 8.337 73.3 3.8384 8
## 234 0 0.5070 8.247 70.4 3.6519 8
## 235 1 0.5070 6.726 66.5 3.6519 8
## 236 0 0.5070 6.086 61.5 3.6519 8
## 237 1 0.5070 6.631 76.5 4.1480 8
## 238 0 0.5070 7.358 71.6 4.1480 8
## 239 0 0.4280 6.481 18.5 6.1899 6
## 240 0 0.4280 6.606 42.2 6.1899 6
## 241 0 0.4280 6.897 54.3 6.3361 6
## 242 0 0.4280 6.095 65.1 6.3361 6
## 243 0 0.4280 6.358 52.9 7.0355 6
## 244 0 0.4280 6.393 7.8 7.0355 6
## 245 0 0.4310 5.593 76.5 7.9549 7
## 246 0 0.4310 5.605 70.2 7.9549 7
## 247 0 0.4310 6.108 34.9 8.0555 7
## 248 0 0.4310 6.226 79.2 8.0555 7
## 249 0 0.4310 6.433 49.1 7.8265 7
## 250 0 0.4310 6.718 17.5 7.8265 7
## 251 0 0.4310 6.487 13.0 7.3967 7
## 252 0 0.4310 6.438 8.9 7.3967 7
## 253 0 0.4310 6.957 6.8 8.9067 7
## 254 0 0.4310 8.259 8.4 8.9067 7
## 255 0 0.3920 6.108 32.0 9.2203 1
## 256 0 0.3920 5.876 19.1 9.2203 1
## 257 0 0.3940 7.454 34.2 6.3361 3
## 258 0 0.6470 8.704 86.9 1.8010 5
## 259 0 0.6470 7.333 100.0 1.8946 5
## 260 0 0.6470 6.842 100.0 2.0107 5
## 261 0 0.6470 7.203 81.8 2.1121 5
## 262 0 0.6470 7.520 89.4 2.1398 5
## 263 0 0.6470 8.398 91.5 2.2885 5
## 264 0 0.6470 7.327 94.5 2.0788 5
## 265 0 0.6470 7.206 91.6 1.9301 5
## 266 0 0.6470 5.560 62.8 1.9865 5
## 267 0 0.6470 7.014 84.6 2.1329 5
## 268 0 0.5750 8.297 67.0 2.4216 5
## 269 0 0.5750 7.470 52.6 2.8720 5
## 270 1 0.4640 5.920 61.5 3.9175 3
## 271 0 0.4640 5.856 42.1 4.4290 3
## 272 0 0.4640 6.240 16.3 4.4290 3
## 273 0 0.4640 6.538 58.7 3.9175 3
## 274 1 0.4640 7.691 51.8 4.3665 3
## 275 1 0.4470 6.758 32.9 4.0776 4
## 276 0 0.4470 6.854 42.8 4.2673 4
## 277 1 0.4470 7.267 49.0 4.7872 4
## 278 1 0.4470 6.826 27.6 4.8628 4
## 279 0 0.4470 6.482 32.1 4.1403 4
## 280 0 0.4429 6.812 32.2 4.1007 5
## 281 0 0.4429 7.820 64.5 4.6947 5
## 282 0 0.4429 6.968 37.2 5.2447 5
## 283 1 0.4429 7.645 49.7 5.2119 5
## 284 1 0.4010 7.923 24.8 5.8850 1
## 285 0 0.4000 7.088 20.8 7.3073 1
## 286 0 0.3890 6.453 31.9 7.3073 1
## 287 0 0.3850 6.230 31.5 9.0892 1
## 288 0 0.4050 6.209 31.3 7.3172 6
## 289 0 0.4050 6.315 45.6 7.3172 6
## 290 0 0.4050 6.565 22.9 7.3172 6
## 291 0 0.4110 6.861 27.9 5.1167 4
## 292 0 0.4110 7.148 27.7 5.1167 4
## 293 0 0.4110 6.630 23.4 5.1167 4
## 294 0 0.4370 6.127 18.4 5.5027 4
## 295 0 0.4370 6.009 42.3 5.5027 4
## 296 0 0.4370 6.678 31.1 5.9604 4
## 297 0 0.4370 6.549 51.0 5.9604 4
## 298 0 0.4370 5.790 58.0 6.3200 4
## 299 0 0.4000 6.345 20.1 7.8278 5
## 300 0 0.4000 7.041 10.0 7.8278 5
## 301 0 0.4000 6.871 47.4 7.8278 5
## 302 0 0.4330 6.590 40.4 5.4917 7
## 303 0 0.4330 6.495 18.4 5.4917 7
## 304 0 0.4330 6.982 17.7 5.4917 7
## 305 0 0.4720 7.236 41.1 4.0220 7
## 306 0 0.4720 6.616 58.1 3.3700 7
## 307 0 0.4720 7.420 71.9 3.0992 7
## 308 0 0.4720 6.849 70.3 3.1827 7
## 309 0 0.5440 6.635 82.5 3.3175 4
## 310 0 0.5440 5.972 76.7 3.1025 4
## 311 0 0.5440 4.973 37.8 2.5194 4
## 312 0 0.5440 6.122 52.8 2.6403 4
## 313 0 0.5440 6.023 90.4 2.8340 4
## 314 0 0.5440 6.266 82.8 3.2628 4
## 315 0 0.5440 6.567 87.3 3.6023 4
## 316 0 0.5440 5.705 77.7 3.9450 4
## 317 0 0.5440 5.914 83.2 3.9986 4
## 318 0 0.5440 5.782 71.7 4.0317 4
## 319 0 0.5440 6.382 67.2 3.5325 4
## 320 0 0.5440 6.113 58.8 4.0019 4
## 321 0 0.4930 6.426 52.3 4.5404 5
## 322 0 0.4930 6.376 54.3 4.5404 5
## 323 0 0.4930 6.041 49.9 4.7211 5
## 324 0 0.4930 5.708 74.3 4.7211 5
## 325 0 0.4930 6.415 40.1 4.7211 5
## 326 0 0.4930 6.431 14.7 5.4159 5
## 327 0 0.4930 6.312 28.9 5.4159 5
## 328 0 0.4930 6.083 43.7 5.4159 5
## 329 0 0.4600 5.868 25.8 5.2146 4
## 330 0 0.4600 6.333 17.2 5.2146 4
## 331 0 0.4600 6.144 32.2 5.8736 4
## 332 0 0.4379 5.706 28.4 6.6407 1
## 333 0 0.4379 6.031 23.3 6.6407 1
## 334 0 0.5150 6.316 38.1 6.4584 5
## 335 0 0.5150 6.310 38.5 6.4584 5
## 336 0 0.5150 6.037 34.5 5.9853 5
## 337 0 0.5150 5.869 46.3 5.2311 5
## 338 0 0.5150 5.895 59.6 5.6150 5
## 339 0 0.5150 6.059 37.3 4.8122 5
## 340 0 0.5150 5.985 45.4 4.8122 5
## 341 0 0.5150 5.968 58.5 4.8122 5
## 342 0 0.4420 7.241 49.3 7.0379 1
## 343 0 0.5180 6.540 59.7 6.2669 1
## 344 0 0.4840 6.696 56.4 5.7321 5
## 345 0 0.4840 6.874 28.1 6.4654 5
## 346 0 0.4420 6.014 48.5 8.0136 3
## 347 0 0.4420 5.898 52.3 8.0136 3
## 348 0 0.4290 6.516 27.7 8.5353 4
## 349 0 0.4350 6.635 29.7 8.3440 4
## 350 0 0.4290 6.939 34.5 8.7921 1
## 351 0 0.4290 6.490 44.4 8.7921 1
## 352 0 0.4110 6.579 35.9 10.7103 4
## 353 0 0.4110 5.884 18.5 10.7103 4
## 354 0 0.4100 6.728 36.1 12.1265 5
## 355 0 0.4130 5.663 21.9 10.5857 4
## 356 0 0.4130 5.936 19.5 10.5857 4
## 357 1 0.7700 6.212 97.4 2.1222 24
## 358 1 0.7700 6.395 91.0 2.5052 24
## 359 1 0.7700 6.127 83.4 2.7227 24
## 360 0 0.7700 6.112 81.3 2.5091 24
## 361 0 0.7700 6.398 88.0 2.5182 24
## 362 0 0.7700 6.251 91.1 2.2955 24
## 363 0 0.7700 5.362 96.2 2.1036 24
## 364 1 0.7700 5.803 89.0 1.9047 24
## 365 1 0.7180 8.780 82.9 1.9047 24
## 366 0 0.7180 3.561 87.9 1.6132 24
## 367 0 0.7180 4.963 91.4 1.7523 24
## 368 0 0.6310 3.863 100.0 1.5106 24
## 369 0 0.6310 4.970 100.0 1.3325 24
## 370 1 0.6310 6.683 96.8 1.3567 24
## 371 1 0.6310 7.016 97.5 1.2024 24
## 372 0 0.6310 6.216 100.0 1.1691 24
## 373 1 0.6680 5.875 89.6 1.1296 24
## 374 0 0.6680 4.906 100.0 1.1742 24
## 375 0 0.6680 4.138 100.0 1.1370 24
## 376 0 0.6710 7.313 97.9 1.3163 24
## 377 0 0.6710 6.649 93.3 1.3449 24
## 378 0 0.6710 6.794 98.8 1.3580 24
## 379 0 0.6710 6.380 96.2 1.3861 24
## 380 0 0.6710 6.223 100.0 1.3861 24
## 381 0 0.6710 6.968 91.9 1.4165 24
## 382 0 0.6710 6.545 99.1 1.5192 24
## 383 0 0.7000 5.536 100.0 1.5804 24
## 384 0 0.7000 5.520 100.0 1.5331 24
## 385 0 0.7000 4.368 91.2 1.4395 24
## 386 0 0.7000 5.277 98.1 1.4261 24
## 387 0 0.7000 4.652 100.0 1.4672 24
## 388 0 0.7000 5.000 89.5 1.5184 24
## 389 0 0.7000 4.880 100.0 1.5895 24
## 390 0 0.7000 5.390 98.9 1.7281 24
## 391 0 0.7000 5.713 97.0 1.9265 24
## 392 0 0.7000 6.051 82.5 2.1678 24
## 393 0 0.7000 5.036 97.0 1.7700 24
## 394 0 0.6930 6.193 92.6 1.7912 24
## 395 0 0.6930 5.887 94.7 1.7821 24
## 396 0 0.6930 6.471 98.8 1.7257 24
## 397 0 0.6930 6.405 96.0 1.6768 24
## 398 0 0.6930 5.747 98.9 1.6334 24
## 399 0 0.6930 5.453 100.0 1.4896 24
## 400 0 0.6930 5.852 77.8 1.5004 24
## 401 0 0.6930 5.987 100.0 1.5888 24
## 402 0 0.6930 6.343 100.0 1.5741 24
## 403 0 0.6930 6.404 100.0 1.6390 24
## 404 0 0.6930 5.349 96.0 1.7028 24
## 405 0 0.6930 5.531 85.4 1.6074 24
## 406 0 0.6930 5.683 100.0 1.4254 24
## 407 0 0.6590 4.138 100.0 1.1781 24
## 408 0 0.6590 5.608 100.0 1.2852 24
## 409 0 0.5970 5.617 97.9 1.4547 24
## 410 0 0.5970 6.852 100.0 1.4655 24
## 411 0 0.5970 5.757 100.0 1.4130 24
## 412 0 0.5970 6.657 100.0 1.5275 24
## 413 0 0.5970 4.628 100.0 1.5539 24
## 414 0 0.5970 5.155 100.0 1.5894 24
## 415 0 0.6930 4.519 100.0 1.6582 24
## 416 0 0.6790 6.434 100.0 1.8347 24
## 417 0 0.6790 6.782 90.8 1.8195 24
## 418 0 0.6790 5.304 89.1 1.6475 24
## 419 0 0.6790 5.957 100.0 1.8026 24
## 420 0 0.7180 6.824 76.5 1.7940 24
## 421 0 0.7180 6.411 100.0 1.8589 24
## 422 0 0.7180 6.006 95.3 1.8746 24
## 423 0 0.6140 5.648 87.6 1.9512 24
## 424 0 0.6140 6.103 85.1 2.0218 24
## 425 0 0.5840 5.565 70.6 2.0635 24
## 426 0 0.6790 5.896 95.4 1.9096 24
## 427 0 0.5840 5.837 59.7 1.9976 24
## 428 0 0.6790 6.202 78.7 1.8629 24
## 429 0 0.6790 6.193 78.1 1.9356 24
## 430 0 0.6790 6.380 95.6 1.9682 24
## 431 0 0.5840 6.348 86.1 2.0527 24
## 432 0 0.5840 6.833 94.3 2.0882 24
## 433 0 0.5840 6.425 74.8 2.2004 24
## 434 0 0.7130 6.436 87.9 2.3158 24
## 435 0 0.7130 6.208 95.0 2.2222 24
## 436 0 0.7400 6.629 94.6 2.1247 24
## 437 0 0.7400 6.461 93.3 2.0026 24
## 438 0 0.7400 6.152 100.0 1.9142 24
## 439 0 0.7400 5.935 87.9 1.8206 24
## 440 0 0.7400 5.627 93.9 1.8172 24
## 441 0 0.7400 5.818 92.4 1.8662 24
## 442 0 0.7400 6.406 97.2 2.0651 24
## 443 0 0.7400 6.219 100.0 2.0048 24
## 444 0 0.7400 6.485 100.0 1.9784 24
## 445 0 0.7400 5.854 96.6 1.8956 24
## 446 0 0.7400 6.459 94.8 1.9879 24
## 447 0 0.7400 6.341 96.4 2.0720 24
## 448 0 0.7400 6.251 96.6 2.1980 24
## 449 0 0.7130 6.185 98.7 2.2616 24
## 450 0 0.7130 6.417 98.3 2.1850 24
## 451 0 0.7130 6.749 92.6 2.3236 24
## 452 0 0.7130 6.655 98.2 2.3552 24
## 453 0 0.7130 6.297 91.8 2.3682 24
## 454 0 0.7130 7.393 99.3 2.4527 24
## 455 0 0.7130 6.728 94.1 2.4961 24
## 456 0 0.7130 6.525 86.5 2.4358 24
## 457 0 0.7130 5.976 87.9 2.5806 24
## 458 0 0.7130 5.936 80.3 2.7792 24
## 459 0 0.7130 6.301 83.7 2.7831 24
## 460 0 0.7130 6.081 84.4 2.7175 24
## 461 0 0.7130 6.701 90.0 2.5975 24
## 462 0 0.7130 6.376 88.4 2.5671 24
## 463 0 0.7130 6.317 83.0 2.7344 24
## 464 0 0.7130 6.513 89.9 2.8016 24
## 465 0 0.6550 6.209 65.4 2.9634 24
## 466 0 0.6550 5.759 48.2 3.0665 24
## 467 0 0.6550 5.952 84.7 2.8715 24
## 468 0 0.5840 6.003 94.5 2.5403 24
## 469 0 0.5800 5.926 71.0 2.9084 24
## 470 0 0.5800 5.713 56.7 2.8237 24
## 471 0 0.5800 6.167 84.0 3.0334 24
## 472 0 0.5320 6.229 90.7 3.0993 24
## 473 0 0.5800 6.437 75.0 2.8965 24
## 474 0 0.6140 6.980 67.6 2.5329 24
## 475 0 0.5840 5.427 95.4 2.4298 24
## 476 0 0.5840 6.162 97.4 2.2060 24
## 477 0 0.6140 6.484 93.6 2.3053 24
## 478 0 0.6140 5.304 97.3 2.1007 24
## 479 0 0.6140 6.185 96.7 2.1705 24
## 480 0 0.6140 6.229 88.0 1.9512 24
## 481 0 0.5320 6.242 64.7 3.4242 24
## 482 0 0.5320 6.750 74.9 3.3317 24
## 483 0 0.5320 7.061 77.0 3.4106 24
## 484 0 0.5320 5.762 40.3 4.0983 24
## 485 0 0.5830 5.871 41.9 3.7240 24
## 486 0 0.5830 6.312 51.9 3.9917 24
## 487 0 0.5830 6.114 79.8 3.5459 24
## 488 0 0.5830 5.905 53.2 3.1523 24
## 489 0 0.6090 5.454 92.7 1.8209 4
## 490 0 0.6090 5.414 98.3 1.7554 4
## 491 0 0.6090 5.093 98.0 1.8226 4
## 492 0 0.6090 5.983 98.8 1.8681 4
## 493 0 0.6090 5.983 83.5 2.1099 4
## 494 0 0.5850 5.707 54.0 2.3817 6
## 495 0 0.5850 5.926 42.6 2.3817 6
## 496 0 0.5850 5.670 28.8 2.7986 6
## 497 0 0.5850 5.390 72.9 2.7986 6
## 498 0 0.5850 5.794 70.6 2.8927 6
## 499 0 0.5850 6.019 65.3 2.4091 6
## 500 0 0.5850 5.569 73.5 2.3999 6
## 501 0 0.5850 6.027 79.7 2.4982 6
## 502 0 0.5730 6.593 69.1 2.4786 1
## 503 0 0.5730 6.120 76.7 2.2875 1
## 504 0 0.5730 6.976 91.0 2.1675 1
## 505 0 0.5730 6.794 89.3 2.3889 1
## 506 0 0.5730 6.030 80.8 2.5050 1
## property_tax_rate school b low_status_pop
## 1 296 15.3 396.90 4.98
## 2 242 17.8 396.90 9.14
## 3 242 17.8 392.83 4.03
## 4 222 18.7 394.63 2.94
## 5 222 18.7 396.90 5.33
## 6 222 18.7 394.12 5.21
## 7 311 15.2 395.60 12.43
## 8 311 15.2 396.90 19.15
## 9 311 15.2 386.63 29.93
## 10 311 15.2 386.71 17.10
## 11 311 15.2 392.52 20.45
## 12 311 15.2 396.90 13.27
## 13 311 15.2 390.50 15.71
## 14 307 21.0 396.90 8.26
## 15 307 21.0 380.02 10.26
## 16 307 21.0 395.62 8.47
## 17 307 21.0 386.85 6.58
## 18 307 21.0 386.75 14.67
## 19 307 21.0 288.99 11.69
## 20 307 21.0 390.95 11.28
## 21 307 21.0 376.57 21.02
## 22 307 21.0 392.53 13.83
## 23 307 21.0 396.90 18.72
## 24 307 21.0 394.54 19.88
## 25 307 21.0 394.33 16.30
## 26 307 21.0 303.42 16.51
## 27 307 21.0 376.88 14.81
## 28 307 21.0 306.38 17.28
## 29 307 21.0 387.94 12.80
## 30 307 21.0 380.23 11.98
## 31 307 21.0 360.17 22.60
## 32 307 21.0 376.73 13.04
## 33 307 21.0 232.60 27.71
## 34 307 21.0 358.77 18.35
## 35 307 21.0 248.31 20.34
## 36 279 19.2 396.90 9.68
## 37 279 19.2 377.56 11.41
## 38 279 19.2 396.90 8.77
## 39 279 19.2 393.43 10.13
## 40 252 18.3 395.63 4.32
## 41 252 18.3 395.62 1.98
## 42 233 17.9 385.41 4.84
## 43 233 17.9 383.37 5.81
## 44 233 17.9 394.46 7.44
## 45 233 17.9 389.39 9.55
## 46 233 17.9 396.90 10.21
## 47 233 17.9 396.90 14.15
## 48 233 17.9 392.74 18.80
## 49 233 17.9 396.90 30.81
## 50 233 17.9 396.90 16.20
## 51 243 16.8 395.56 13.45
## 52 243 16.8 393.97 9.43
## 53 243 16.8 396.90 5.28
## 54 243 16.8 396.90 8.43
## 55 469 21.1 396.90 14.80
## 56 226 17.9 395.93 4.81
## 57 313 17.3 396.90 5.77
## 58 256 15.1 392.90 3.95
## 59 284 19.7 390.68 6.86
## 60 284 19.7 396.90 9.22
## 61 284 19.7 395.11 13.15
## 62 284 19.7 378.08 14.44
## 63 284 19.7 396.90 6.73
## 64 284 19.7 395.58 9.50
## 65 216 18.6 393.24 8.05
## 66 337 16.1 396.90 4.67
## 67 337 16.1 396.90 10.24
## 68 345 18.9 396.21 8.10
## 69 345 18.9 396.90 13.09
## 70 345 18.9 396.90 8.79
## 71 305 19.2 383.73 6.72
## 72 305 19.2 376.94 9.88
## 73 305 19.2 390.91 5.52
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# b. Data Visualization
# 1.Median value of owner-occupied homes by pupil-teacher ratio by town
ggplot(data, aes(x=school, y=median_value, col=crime_rate)) + geom_point() +
ggtitle("Median Value & School") +
xlab("School") +
ylab("Median Value") +
scale_color_gradient(low="green",high="red",
name="Crime Rate")
# 2.Median value of owner-occupied homes by percentage of lower status of the population
ggplot(data, aes(x=low_status_pop,y=median_value)) +
geom_point(aes(size=crime_rate))
# Histogram of dependent variable
hist(data$median_value)
hist(log(data$median_value))
# Correlation Plot
datab<- data %>% select(-river_view) # Remove qualitative data
corrplot(cor(datab),type='upper',order='hclust')
#Regression Analysis 1
modelo_multiple_1 <- lm(formula = median_value ~ crime_rate + residential_land + non_retail_business + river_view + rooms + distance + access_to_highways + property_tax_rate + school + b + low_status_pop, data = data)
summary(modelo_multiple_1)
##
## Call:
## lm(formula = median_value ~ crime_rate + residential_land + non_retail_business +
## river_view + rooms + distance + access_to_highways + property_tax_rate +
## school + b + low_status_pop, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -16.8808 -2.8171 -0.7587 1.7176 26.6875
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 23.108557 4.354055 5.307 1.68e-07 ***
## crime_rate -0.098378 0.033498 -2.937 0.003471 **
## residential_land 0.050975 0.013881 3.672 0.000267 ***
## non_retail_business -0.060498 0.060393 -1.002 0.316957
## river_view 2.486994 0.877634 2.834 0.004789 **
## rooms 3.894948 0.417198 9.336 < 2e-16 ***
## distance -1.121279 0.179465 -6.248 8.99e-10 ***
## access_to_highways 0.265392 0.067009 3.961 8.58e-05 ***
## property_tax_rate -0.013877 0.003824 -3.629 0.000315 ***
## school -0.750648 0.126124 -5.952 5.04e-09 ***
## b 0.010097 0.002732 3.696 0.000244 ***
## low_status_pop -0.564127 0.047926 -11.771 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4.846 on 494 degrees of freedom
## Multiple R-squared: 0.7284, Adjusted R-squared: 0.7224
## F-statistic: 120.5 on 11 and 494 DF, p-value: < 2.2e-16
AIC (modelo_multiple_1)
## [1] 3046.858
# Regression Analysis 2
modelo_multiple_2 <- lm(formula = log(median_value) ~ crime_rate + residential_land + non_retail_business + river_view + rooms + distance + access_to_highways + property_tax_rate + school + b + low_status_pop, data = data)
summary(modelo_multiple_2)
##
## Call:
## lm(formula = log(median_value) ~ crime_rate + residential_land +
## non_retail_business + river_view + rooms + distance + access_to_highways +
## property_tax_rate + school + b + low_status_pop, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.74427 -0.11107 -0.01225 0.08947 0.96890
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.5216289 0.1749117 20.134 < 2e-16 ***
## crime_rate -0.0098555 0.0013457 -7.324 9.87e-13 ***
## residential_land 0.0013458 0.0005576 2.413 0.01617 *
## non_retail_business -0.0010203 0.0024261 -0.421 0.67425
## river_view 0.0928912 0.0352564 2.635 0.00868 **
## rooms 0.0956772 0.0167597 5.709 1.97e-08 ***
## distance -0.0346369 0.0072095 -4.804 2.06e-06 ***
## access_to_highways 0.0124489 0.0026919 4.625 4.80e-06 ***
## property_tax_rate -0.0006906 0.0001536 -4.495 8.67e-06 ***
## school -0.0294347 0.0050667 -5.809 1.12e-08 ***
## b 0.0004497 0.0001098 4.097 4.89e-05 ***
## low_status_pop -0.0304928 0.0019253 -15.838 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1947 on 494 degrees of freedom
## Multiple R-squared: 0.7781, Adjusted R-squared: 0.7732
## F-statistic: 157.5 on 11 and 494 DF, p-value: < 2.2e-16
AIC (modelo_multiple_2)
## [1] -206.2981
# Regression Analysis 3
modelo_multiple_3 <- lm(formula = log(median_value) ~ crime_rate + residential_land + non_retail_business + river_view + I(rooms^2) + distance + access_to_highways + property_tax_rate + school + b + low_status_pop, data = data)
summary(modelo_multiple_3)
##
## Call:
## lm(formula = log(median_value) ~ crime_rate + residential_land +
## non_retail_business + river_view + I(rooms^2) + distance +
## access_to_highways + property_tax_rate + school + b + low_status_pop,
## data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.74384 -0.10483 -0.01286 0.08970 0.95760
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.7274107 0.1340314 27.810 < 2e-16 ***
## crime_rate -0.0099001 0.0013289 -7.450 4.20e-13 ***
## residential_land 0.0012356 0.0005515 2.241 0.02550 *
## non_retail_business -0.0006142 0.0023987 -0.256 0.79801
## river_view 0.0903880 0.0348289 2.595 0.00973 **
## I(rooms^2) 0.0086600 0.0012794 6.769 3.70e-11 ***
## distance -0.0320597 0.0071567 -4.480 9.30e-06 ***
## access_to_highways 0.0119458 0.0026615 4.488 8.94e-06 ***
## property_tax_rate -0.0006772 0.0001518 -4.462 1.01e-05 ***
## school -0.0281128 0.0050180 -5.602 3.52e-08 ***
## b 0.0004521 0.0001083 4.174 3.53e-05 ***
## low_status_pop -0.0296588 0.0018905 -15.688 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1923 on 494 degrees of freedom
## Multiple R-squared: 0.7836, Adjusted R-squared: 0.7788
## F-statistic: 162.6 on 11 and 494 DF, p-value: < 2.2e-16
AIC (modelo_multiple_3)
## [1] -218.8483