Use the "wage" data. Wage is the dependent variable and the independent variables are education and experience.
Use the “wage” data. Wage is the dependent variable and the independent variables are education and experience.
Determine the bivariate correlation between wage and education. What is the interpretation? ;
strong, negative, significant
moderate, positive, not significant
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moderate, negative, significant
strong, positive, not significant
moderate, positive, significant
strong, positive, significant
None of the above
Use the “wage” data. Wage is the dependent variable and the independent variables are education and experience. Determine the regression equation. What is the y-intercept?
.483
3.75
.070
-10.55
.453
2.31
.063
Use the “wage” data. Wage is the dependent variable and the independent variables are education and experience. How much money is each additional year of education worth?2.31
2.31 thousand bucks
0.06 thousand bucks
10.55 thousand bucks
.483 thousand bucks
0.0255 thousand bucks
0.845 thousand bucks
None of the above
Use the “wage” data. Wage is the dependent variable and the independent variables are education and experience. How much of the variance in the dependent variable is explained by these independent variables?
69.6%
48.4%
35.5%
6.89%
-10.55%
None of the abov3
Use the “wage” data. Wage is the dependent variable and the independent variables are education and experience. Imagine a person with zero education and zero experience. How much money would we expect them to earn according to this statistical model?
they would earn $695
they would earn $-10, 551, meaning they’d live on credit
they would earn $10, 551
they would earn $-2, 313
they would earn $485
they would earn $13, 393, the same as all high school dropouts
None of the above