(a) Develop the estimated regression equation using all of the independent variables included in the data.
(b) How much of the variation in the sample values of delay does this estimated regression equation explain?
(c) Test the relationship between each independent variable and the dependent variable at the 0.05 level of significance. You will find one independent variable that is not significant. Which variable is this?
(d) Remove the nonsignificant variable and run a new regression.
(e) Give the resulting regression equation. Are all the independent variables significant now?
Use the regression equation in (e) to answer the remaining questions.
(f) Predict the audit delay for a public, industrial company whose quality rating is 3 and the "finished" rating is 4. (Hint: Remember you can ignore the given value for a variable that is not included in your regression equation. For example, if the variable "finished" was not significant so was not included in the regression, then its given value 4 will not be used in our calculation.) Express the answer rounded to the first decimal digit.
(g) According to the regression from (e), is audit delay longer for an industrial company or a non-industrial company? By how many days?
(h) Suppose company A and B are both non-industrial and have the same "finished" rating, but A's quality rating is 2 points higher than B's. Is A's audit delay longer or shorter than B? By how many days?