Question

Using R or RStudio

After loading the data crime2005 data set from the library smss, use (non-robust) linear regression to model the crime rate per 10,000 people (VI2) as a function of the percentage of the population that live in metropolitan areas (ME) and the percentage of the population that live below the poverty line (PO).

Enter your R code below.

Answer 1

# Assign more meaningful variable names, also
# Convert is.south to a factor
# Divide average.ed by 10 so that the variable is actually average education
# Convert median assets to 1000's of dollars instead of 10's
crime <- crime %>%
rename(crime.per.million = R,
young.males = Age,
is.south = S,
average.ed = Ed,
exp.per.cap.1960 = Ex0,
exp.per.cap.1959 = Ex1,
labour.part = LF,
male.per.fem = M,
population = N,
nonwhite = NW,
unemp.youth = U1,
unemp.adult = U2,
median.assets = W,
num.low.salary = X) %>%
mutate(is.south = as.factor(is.south),
average.ed = average.ed / 10,
median.assets = median.assets / 100)
# print summary of the data
summary(crime)