Question

Using program R, please help solve:

Data set is given in program R and can be seen by putting in code:

state.x77
x77<-data.frame(state.x77)

(if answered by Tuesday 6/11 evening, I will rate)

3.17 The state.x77 data set contains various information for each of the fifty United States. We wish to explore possible relationships among the variables. First, we make the data set easier to work with by turning it into a data frame. x77data.frame(state.x77) ; Now, make scatter plots of Population and Frost; Population and Murder; Population and Area; and Income and HS. Grad. Do any relationships appear linear? Are there any surprising correlations?

Answer 1

Converting the data to a data frame:

> x77 <- data.frame(state.x77)

Now, plotting the different variables to study their relationship:

> plot(x77$Population, x77$Frost)

Oo 0 5000 10000 15000 20000 x77$Population 00 00L 09 C x77$Frost

> plot(x77$Population, x77$Murder)

N 5000 15000 0 10000 20000 x77$Population x77$Murder 10 12 14 9

> plot(x77$Population, x77$Area)

5000 15000 0 10000 20000 x77$Population x77$Area 2e+05 4e+05 00+00

> plot(x77$Income, x77$HS.Grad)

O O 3000 3500 4000 4500 5000 5500 6000 x77$Income 09 95 09 x77$HS.Grad

As seen in the scatter plots above, none of the first 3 relationships appear linear, though there is a moderate linear relationship between Income and HS.Grad as seen in the last chart.

There is some degree of positive correlation between Population and murder rate, which is a bit surprising since this isn't something one would normally expect (population grows as murder rate increases? This isn't expected!)