Compute Using: Data in the table to the left, Microsoft Excel functions, or Data Analysis Toolpak, Regression

You are consulting for a business director at a television station, and she is concerned about a problem

related to labor and standby hours. Standby hours are hours in which unionized graphic artists at the

station are paid but are not actually involved in any activity- they are on standby in case they are needed. She thinks there is a relationship between the hours of Standby Staff, On-Site Labor, and Remote Labor. There are two types of labor categories: On-Site (hours worked on-site at the station) and Remote (hours worked at home). The business director is trying to predict how many Standby Sfaff hours she needs based on On-Site hours and Remote hours. After conducting your analysis, provide a recommendation. The data are provided for you in Standby.xls.

1. Determine the regression coefficient, b0, b1, and b2(be sure to indicate the units for b0, b1, and b2!!). State the multiple regression equation.

2. Interpret the meaning of b1, and b2.

3. Explain why the regression coefficient b0 has no practical meaning in the context of this problem.

4. Predict the standby hours for a week in which there are 310 on-site hours and 400 remote hours.

5. What future research would you recommend to better understand this business problem? Explain.

Standby Data
Standby Staff (hrs)	On-Site Labor (hrs)	Remote Labor (hrs)
245	338	414
177	333	598
271	358	656
211	372	631
196	339	528
135	289	409
195	334	382
118	293	399
116	325	343
147	311	338
154	304	353
146	312	289
115	283	388
161	307	402
274	322	151
245	335	228
201	350	271
183	339	440
237	327	475
175	328	347
152	319	449
188	325	336
188	322	267
197	317	235
261	315	164
232	331	270