(6)The variables y = annual income (thousands of dollars), = number of years of education, and = number of years of experience in job are measured for all the employees having city-funded jobs, in Knoxville, Tennessee.The following prediction equations and correlations apply:

i. r = 0.30

ii. r = 0.60

The correlation is -0.40 between and .Which of the following statements are true? (5 points)

a)The strongest sample association is between y and .

b)The weakest sample association is between and .

c)The prediction equation using to predict has negative slope.

d)A SD increase in education corresponds to a predicted increase of 0.3 SD in income.

e)There is a 30% reduction in error in using education, instead of , to predict income.

f)Each additional year on the job corresponds to a $400 increase in predicted income.

g)When is the predictor of y, the sum of squared residuals (SSE) is larger than when is the predictor of y.

h)The predicted mean income for employees having 20 years of experience is $4000 higher than the predicted mean income for employees having 10 years of experience.

i)If s = 8 for the model using to predict y, then it is not unusual to observe an income of $70,000 for an employee who has 10 years of education.

j)It is possible that = 12.0 and = 3.6

k)It is possible that = 20 and = 13