Regression Analysis using Standby Hours
Question: The business problem facing the director of broadcasting operations for a television station was the issue of standby hours (i.e hours in which unionized graphic artists at the station are paid but are not actually involved in any activity) and what factors were related to standby hours. The study included the following variables:
– Standby Hours (Y) – total number of standby hours in a week
– Total Staff present (X1) – Weekly total of people – days
– Remote hours (X2) – Total number of hours worked by employees at locations away from the central plant
Data were collected for 26 weeks: these data are organized and stored in Standby (Excel attached)
A. Use Excel to state the multiple regression equation. Make sure to explain any verbal answers with reference to the appropriate table and numbers.
B. Interpret the meaning of the slopes, bi and b2.
C. Explain why the regression coefficient, b0, has no practical meaning in the context of this problem.
D. Predict the standby hours for a week in which the total staff present have 310 people-days and the remote hours are 400.
E. Interpret the estimated adjusted coefficient of determination and construct a 95% confidence interval estimate for the mean standby hours for weeks in which the total staff present have 310 people-days and the remote hours are 400.