Age Gender Housing Saving accounts Checking account Credit amount Duration
1 67 male own <NA> little 1169 6
2 22 female own little moderate 5951 48
3 49 male own little <NA> 2096 12
4 45 male free little little 7882 42
5 53 male free little little 4870 24
6 35 male free <NA> <NA> 9055 36
7 53 male own quite rich <NA> 2835 24
8 35 male rent little moderate 6948 36
9 61 male own rich <NA> 3059 12
10 28 male own little moderate 5234 30
Purpose Class Risk
1 radio/TV 1
2 radio/TV 2
3 education 1
4 furniture/equipment 1
5 car 2
6 education 1
7 furniture/equipment 1
8 car 1
9 radio/TV 1
10 car 2
tail(german,10)
Age Gender Housing Saving accounts Checking account Credit amount Duration
991 37 male own <NA> <NA> 3565 12
992 34 male own moderate <NA> 1569 15
993 23 male rent <NA> little 1936 18
994 30 male own little little 3959 36
995 50 male own <NA> <NA> 2390 12
996 31 female own little <NA> 1736 12
997 40 male own little little 3857 30
998 38 male own little <NA> 804 12
999 23 male free little little 1845 45
1000 27 male own moderate moderate 4576 45
Purpose Class Risk
991 education 1
992 radio/TV 1
993 radio/TV 1
994 furniture/equipment 1
995 car 1
996 furniture/equipment 1
997 car 1
998 radio/TV 1
999 radio/TV 2
1000 car 1
summary(german)
Age Gender Housing Saving accounts
Min. :19.00 Length:1000 Length:1000 Length:1000
1st Qu.:27.00 Class :character Class :character Class :character
Median :33.00 Mode :character Mode :character Mode :character
Mean :35.55
3rd Qu.:42.00
Max. :75.00
Checking account Credit amount Duration Purpose
Length:1000 Min. : 250 Min. : 4.0 Length:1000
Class :character 1st Qu.: 1366 1st Qu.:12.0 Class :character
Mode :character Median : 2320 Median :18.0 Mode :character
Mean : 3271 Mean :20.9
3rd Qu.: 3972 3rd Qu.:24.0
Max. :18424 Max. :72.0
Class Risk
Min. :1.0
1st Qu.:1.0
Median :1.0
Mean :1.3
3rd Qu.:2.0
Max. :2.0
table(german$Gender,german$Housing)
free own rent
female 19 196 95
male 89 517 84
table(german$Gender,german$`Saving accounts`)
little moderate quite rich rich
female 194 32 16 19
male 409 71 47 29
table(german$Gender,german$`Checking account`)
little moderate rich
female 88 86 20
male 186 183 43
table(german$Gender,german$Purpose)
business car domestic appliances education furniture/equipment
female 19 94 6 24 74
male 78 243 6 35 107
radio/TV repairs vacation/others
female 85 5 3
male 195 17 9
library(ggplot2)library(datasetsICR)data(german)class <-factor(german$`Class Risk`)ggplot(data = german, mapping =aes(x=`Credit amount`, y= Duration, color= class)) +geom_smooth() +geom_point() +scale_x_log10() +labs(title ="Comparison of Credit Amount, Duration, and Class Risk",subtitle ="Credit Risk with the duration of the credit",caption ="Source: [german] dataset",x="Credit Amount Borrowed(in log base 10)",y="Durations in months(in log base 10)",color="Class(1=good,2=bad)")
`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
This graph shows the relationship between the credit amount borrowed, the duration in months of that amount and the class that they are associated with. When looking at the graph we see that the two classes are very similar to each other. There is a lot of overlap in the distribution between the amount borrowed and the duration. Due to this overlap the credit amount and the duration due have a positive relationship but it is not strong enough to predict the Class Risk.
