7.39 Urban homeowners, Part II.

Exercise 7.33 gives a scatterplot displaying the relationship between the percent of families that own their home and the percent of the population living in urban areas. Below is a similar scatterplot, excluding District of Columbia, as well as the residuals plot. There were 51 cases.

(a) For these data, R2 = 0.28. What is the correlation?

correlation<- round(sqrt(0.28),2)
correlation
## [1] 0.53

How can you tell if it is positive or negative?

The trend in the scatter plot implies that a negative correlation between Urban population and homeownership, as the percent of urban population goes up, the percent of families who own their home goes down.

(b) Examine the residual plot. What do you observe?

Residuals increase as the independent variable increases.

Is a simple least squares fit appropriate for these data?

Since the data does not meet the ’constant variablility requirement,(the variability is not constant (it increases)) it is not appropriate to use least squares.