Twenty-one executives in a large corporation were randomly selected for a study to determine the effect of several factors on annual salary (expressed in $000's). The factors selected were age, seniority, years of college, number of company divisions they had been exposed to and the level of their responsibility. A regression analysis was performed using a popular spreadsheet program with the following regression output:

Write out the multiple regression equation.
Which independent variable has the most significant effect on annual salary?
What proportion of the total variation in salary is accounted for by the set of independent variables?
Test the hypothesis that the regression coefficient for age is equal to 0 at the 0.05 significance level. Report the degrees of freedom, the test statistic, the critical value, and your decision.

23.00371 Std Error of Y estimate Rsquarec No. of Observations Degrees of Freedom 291933 0.91404 21 15 Age Sen Educ #Of Div Level X Coefficients -0.031 0.381 14520.089 3.554 Std Err of Coef 0.183 0.158 0.387 0.541 0.833