1. Class 24
Case: Edgcomb Metals

2. Edgcomb Metals 21 service centers doing $500 million in sales
Supplied by large steel companies
35,000 customers (any firm using some kind of steel)
Services include cutting, shaping, and daily delivery.

3. Troy Plant 72K plant serving customers in Virginia
Seven trucks, eight trailers
Seven drivers
$9.50 and hour with 50% for overtime
Customized uniforms with American flag patch
Daily deliveries to seven “sectors”
Product for each “run” was loaded at the plant each morning in “optimum” order.
Customers unload.
Drivers assigned “randomly” to sectors.

4. Spencer versus Williams
Spencer spoke up at the most recent drivers’ meeting:
We get paid by the hour with time and a half for overtime.
Some of us hustle throughout the day, finish early, and help in the shop.
Some of us don’t hustle and end up with overtime as a result.
I want to work hard…..and it’s not right that others get rewarded for NOT working hard.

5. Exhibit 2 Month TONS MILES STOPS REG HRS OT HRS Jun-83 3043 34907 719
1182
362
May-83
2889
38799
728
1259
360
Apr-83
2384
33367
695
1230
382
Mar-83
2500
35288
763
1345
283
Feb-83
2312
29876
613
1205
257
Jan-83
2678
35056
709
1253
306
Dec-82
1678
27171
568
962
187
Nov-82
2209
29917
624
915
276
Oct-82
2382
30143
713
239
Sep-82
2315
34771
617
1091
272
Aug-82
2624
36523
724
1108
Jul-82
1745
34693
640
1030
249

6. Exhibit 4 Williams . Miles(W) Stops(W) Hours(W) 331 3 10.17 206 2 8.00
221 4
8.25
193
10.00 .
261 7
11.40
292
10.75
200
10.50
11.33

7. Exhibit 4 Spencer . Miles(S) Stops(S) Hours(S) 182 3 8.25 364 9 12.50
227
10.50
188 4
6.50 .
346
10.00
320
11.50
181
9.50
369 7
11.75

8. Notes

9. Task A
Calculate summary statistics for both the Williams and Spencer Data.
Be prepared to present and comment BRIEFLY on the results.

10. Task B Test the hypothesis that mean hours is equal for S and W.
Formulate you own alternative hypothesis
Do not use regression
Be prepared to report and interpret the results.

11. Task C Combine (Stack) the Williams and Spencer Data.
Create a dummy variable which designates driver
Regress hours on the dummy variable.
Be prepared to interpret the results and to test the statistical significance of the results.

12. Task D
Test the hypothesis that Spencer’s mean miles (per run) is equal to Williams’ mean miles.
Ha: mean miles for Spencer is greater than mean miles for Williams.
Be prepared to interpret the results.

13. Task E
Test the hypothesis that Spencer’s mean Stops (per run) is equal to Williams’ mean Stops.
Ha: mean Stops for Spencer is greater than mean Stops for Williams.
Be prepared to interpret the results.

14. Task F For the Williams Data For the Spencer Data
Regress Hours on both Miles and Stops.
Be prepared to report and interpret the results.
For the Spencer Data
Based on your comparison of the two models, who is the better driver?

15. Task G Combine (Stack) the Williams and Spencer Data.
Create a dummy variable which designates driver.
Regress hours on the dummy variable, Miles, and Stops.
A multiple regression with three X variables.
Be prepared to interpret the results and to test the statistical significance of the results.

16. Edgcomb Metals
What Happened