3.1_3.4: Data Description

Credit Data

library(readr)
Credit <- read_csv("Credit.csv")

Descriptive Statistics

#install.packages("psych")
library(psych)
describe(Credit$Income)

##    vars   n  mean    sd median trimmed   mad   min    max  range skew kurtosis
## X1    1 400 45.22 35.24  33.12   38.67 23.12 10.35 186.63 176.28 1.73     2.87
##      se
## X1 1.76

describe(Credit$Balance)

##    vars   n   mean     sd median trimmed    mad min  max range skew kurtosis
## X1    1 400 520.01 459.76  459.5  475.13 593.04   0 1999  1999 0.58    -0.55
##       se
## X1 22.99

describeBy(Credit$Income,Credit$Gender)

## 
##  Descriptive statistics by group 
## group: Female
##    vars   n  mean    sd median trimmed  mad   min    max  range skew kurtosis
## X1    1 207 44.85 34.96  32.16   38.41 19.3 10.36 186.63 176.27  1.9     3.71
##      se
## X1 2.43
## ------------------------------------------------------------ 
## group: Male
##    vars   n  mean    sd median trimmed   mad   min    max  range skew kurtosis
## X1    1 193 45.61 35.64  33.44   39.29 25.14 10.35 182.73 172.37 1.55     1.98
##      se
## X1 2.57

describeBy(Credit$Income,Credit$Ethnicity)

## 
##  Descriptive statistics by group 
## group: African American
##    vars  n  mean   sd median trimmed   mad  min    max  range skew kurtosis  se
## X1    1 99 47.68 38.8  34.51   41.01 22.78 10.5 186.63 176.13 1.65     2.27 3.9
## ------------------------------------------------------------ 
## group: Asian
##    vars   n  mean   sd median trimmed   mad   min    max  range skew kurtosis
## X1    1 102 44.19 35.6  30.06    37.7 21.31 10.36 180.38 170.02 1.62     2.32
##      se
## X1 3.52
## ------------------------------------------------------------ 
## group: Caucasian
##    vars   n  mean    sd median trimmed   mad   min    max  range skew kurtosis
## X1    1 199 44.52 33.28  33.44   38.71 23.24 10.35 182.73 172.37 1.77     3.28
##      se
## X1 2.36

Quartiles

summary(Credit$Income)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   10.35   21.01   33.12   45.22   57.47  186.63

summary(Credit$Balance)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    0.00   68.75  459.50  520.01  863.00 1999.00

Application of Different Statistics by Group using the Aggregate Function

aggregate(Income ~ Married, data = Credit, FUN = mean)

##   Married   Income
## 1      No 43.64109
## 2     Yes 46.21708

aggregate(Income ~ Married, data = Credit, FUN = median)

##   Married Income
## 1      No 33.657
## 2     Yes 32.164

aggregate(Income~ Married, data = Credit, FUN = sd)

##   Married   Income
## 1      No 32.38303
## 2     Yes 36.97017

aggregate(Income~ Married, data = Credit, FUN = quantile, prob = 0.25)

##   Married  Income
## 1      No 20.8635
## 2     Yes 21.3740

aggregate(Income~ Married, data = Credit, FUN = quantile, prob = 0.50)

##   Married Income
## 1      No 33.657
## 2     Yes 32.164

aggregate(Income~ Married, data = Credit, FUN = quantile, prob = 0.75)

##   Married Income
## 1      No 53.523
## 2     Yes 58.929

Boxplot

boxplot(Credit$Income, main="Income Distribution",
   xlab="", ylab="Income") 

Boxplot

boxplot(Balance~Student,data=Credit, main="Balance Distribution by Student",
   xlab="Student", ylab="Balance") 

Boxplot

boxplot(Balance~Cards,data=Credit, main="Balance Distribution by Card",
   xlab="Student", ylab="Balance")