You ran a regression of income (y) on years of education (x). Income is measured in thousands of US$. Because of heteroscedasticity, you transformed your dependent variable. Your regression line is now: predicted ln (income) = 2.4 + 0.06 x education What is the predicted income for a person who has 9 years of education?

A. $12,940
B. $ 18,916
C. $ 29,400
D. $ 2,940

D. $2940

Step-by-step explanation:

The given regression model is

Income=2.4+0.06 x education.

The predicted income of person with 9 years of education can be computed by replacing education year with 9 in the regression model

Income=2.4+0.06*9

Income=2.4+0.54

Income=2.94

As the income is measured in thousands of US $ so,

Income=2.94*1000 $

Income=$2940.

Thus, the predicted income of person with 9 years of education is $2940.

a 270° rotation about point p says on e d g e n u it y (had to space it out because it says it's a misspelling so i couldn't submit it

126.66 m²

step-by-step explanation:

the pertinent area formula is a = πr², where r is the radius.

here, a = π(6.35 m)² = 40.32π, or approximately 126.66 m²