Data are collected on teacher salary (measured in 1000’s of $’s) and years of se

Question

Data are collected on teacher salary (measured in 1000’s of $’s) and years of service, rating by the administrator, and whether the teacher has a masters degree (=1) or not (=0)

a) Complete the following table

SUMMARY OUTPUT

Regression Statistics

Multiple R

R Square

Adjusted R Square

Standard Error

Observations         20

ANOVA

b) What is the estimated regression equation?

c) How much of the variation in income in explained by the regressors?

d) What is the standard error of the error term in the regression equation?

12 e) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know?

f) Is the regression equation as a whole significant at the 1% level of significance? How do you know?

g) What is the predicted value of income for a teacher that is does not have a masters degree, has 14 years of service, and has a rating of 3.5?

h) What is the effect on income of a teacher receiving their masters degree?

df SS MS F Significance F Regression 903.2 1.62311E-08 Residual 91.4 Total

Explanation / Answer

b)

9.915+0.899(years)+0.154(rating)-0.667(masters)

c)

90.81%

g)

9.915+0.899(years)+0.154(rating)-0.667(masters)

9.915+0.899(14)+0.154(3.5)-0.667(0)

9.915+12.586+0.539-0=23.04

h)

The income of a teacher receiving masters degree goes down by 0.667, all other factors remaining constant.

a)

ANOVA df SS MS F Significance F Regression 1 903.2 903.2 177.8730853 0.00000001623 Residual 18 91.4 5.077777778 Total 19 994.6 coefficients standard error t stat Pvalue Lower 95% Upper 95% Intercept 9.915 1.916 5.174843424 0 6.15964 13.67036 Years 0.899 0.088 10.21590909 0 0.72652 1.07148 Rating 0.154 0.031 4.967741935 0 0.09324 0.21476 Masters -0.667 1.214 -0.54942339 0.59 -3.04644 1.71244 SUMMARY OUTPUT Regression Statistics Multiple R 0.95294478 R Square 0.90810376 Adjusted R Square Standard Error Observations         20

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