Linear Models with R, Question 1.1

  1. The dataset teengamb concerns a study of teenage gambling in Britain. Make a numerical and graphical summary of the data, commenting on any features that you find interesting. Limit the output you present to a quantity that a busy reader would find sufficient to get a basic understanding of the data.
data(teengamb, package="faraway")
head(teengamb)
##   sex status income verbal gamble
## 1   1     51   2.00      8    0.0
## 2   1     28   2.50      8    0.0
## 3   1     37   2.00      6    0.0
## 4   1     28   7.00      4    7.3
## 5   1     65   2.00      8   19.6
## 6   1     61   3.47      6    0.1
summary(teengamb)
##       sex             status          income           verbal     
##  Min.   :0.0000   Min.   :18.00   Min.   : 0.600   Min.   : 1.00  
##  1st Qu.:0.0000   1st Qu.:28.00   1st Qu.: 2.000   1st Qu.: 6.00  
##  Median :0.0000   Median :43.00   Median : 3.250   Median : 7.00  
##  Mean   :0.4043   Mean   :45.23   Mean   : 4.642   Mean   : 6.66  
##  3rd Qu.:1.0000   3rd Qu.:61.50   3rd Qu.: 6.210   3rd Qu.: 8.00  
##  Max.   :1.0000   Max.   :75.00   Max.   :15.000   Max.   :10.00  
##      gamble     
##  Min.   :  0.0  
##  1st Qu.:  1.1  
##  Median :  6.0  
##  Mean   : 19.3  
##  3rd Qu.: 19.4  
##  Max.   :156.0

Found this info online: sex 0=male, 1=female

status Socioeconomic status score based on parents' occupation

income in pounds per week

verbal verbal score in words out of 12 correctly defined

gamble expenditure on gambling in pounds per year

Source: https://rdrr.io/cran/faraway/man/teengamb.html

I am going to choose the field "gamble" to look at because I feel like one's socioeconomic status effects how much one would gamble because we need money to gamble, therefore a certain amount of wealth/status is required.

hist(teengamb$status,xlab="Status",main="")

The histogram above is not showing a binomial , Poisson, or exponential distribution.

plot(density(teengamb$status,na.rm=TRUE),main="")

plot(sort(teengamb$status),ylab="Sorted Status")

I feel like the next 2 graphs did not give me any insight.

plot(gamble~ status,teengamb)

plot(gamble ~ sex, teengamb)