The following equation models a linear relationship of a worker's hourly remuneration (Wage in dollars) with her or his education (Educ in years), work experience (Exper in years) and tenure with the current employer (Tenur in years):

Wage = 0 + 1Educ + 2Exper + 3Tenur + with~N(0, some constant)

Answer the following questions by selecting the best option from the drop down menu or typing your answer in the box next to the question.

You may use Excel for calculation in answering the questions below.

Provide your numerical answers after rounding them to 3 digits after the decimal point. (Round up if the fourth digit is 5 or larger, down if it is 4 or smaller, e.g. type 1.783 if your calculation results in 1.7832, type 0.039 if it results in 0.0387, type 0.101 if it results in 0.1006, etc.) However, in order to obtain accurate final answers, do not round numbers during your calculation. If your answer is an integer, just type it, e.g. type 12 if your answer is 12.

The following table has been obtained by regressing Wage on the three exogenous variables. Several statistics are deliberately missing in the table. Obtain and type them in the relevant boxes provided.

Regression statistics Descriptive statistics for error

Multiple R 0.618 Skewness (S) 1.170

R2 0.382 Kurtosis (K) 4.830

Adjusted R2 Answer

Jarque-Berra (JB) Answer

S.E. Answer

Observations 65

ANOVA

df SS MS F stat F=.05, Reg. df, Error df

Regression Answer

507.720 169.240 Answer

Answer

Error Answer

Answer

13.471

Total 64 1329.448

Regression results

Coefficient S.E. t stat p-value 95% conf. int. lower limit 95% conf. int. upper limit

Intercept 6.700 2.701 2.481 0.016 1.299 12.101

Educ 4.899 2.189 2.238 0.029 0.522 9.276

Exper 2.500 1.146 Answer

Answer

0.208 4.792

Tenur 1.975 1.345 1.468 0.147 Answer

Answer

The p-values for the 4 estimated coefficients imply that Answer

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The computed F statistic and the upper-5% critical value imply that, at the 5% level of significance, we can reject the null hypothesis that the regression model can Answer

.

The adjusted R2 implies that the regression model can Answer

very well. Together with the p-values for the 4 estimated coefficients, the difference between the R2 and adjusted R2 implies that the regression model might Answer

.

The estimated 1 implies that Answer

The 95% confidence interval estimate for the parameter 2 implies that Answer

, holding the worker's education and workplace tenure constant.

The JB statistic implies that errors are Answer

, which Answer

the validity of the regression analysis.