Regression; choosing among models (chapter appendix) Tilbert Toys (TT) makes the popular Floppin’ Freddy Frog and Jumpin’ Jill Junebug dolls in batches. TT has recently adopted activity-based costing. TT incurs setup costs for each batch of dolls that it produces. TT uses “number of setups” as the cost driver for setup costs.

TT has just hired Bebe Williams, an accountant. Bebe thinks that “number of setup hours” might be a better cost driver because the setup time for each product is different. Bebe collects the following data.

1. Estimate the regression equation for (a) setup costs and number of setups and (b) setup costs and number of setup hours. You should obtain the following results:

Regression 1: Setup costs = a + (b × Number of setups)

Regression 2: Setup costs = a + (b × Number of setup-hours)

2. On two different graphs plot the data and the regression lines for each of the following cost functions. 

 a. Setup costs = a + (b × Number of setups)

 b. Setup costs = a + (b × Number of setup hours)

3. Evaluate the regression models for “Number of setups” and “Number of setup-hours” as the cost driver according to the format of Exhibit 10-18.

4. Based on your analysis, which cost driver should Tilbert Toys use for setup costs, and why?

Transcribed Image Text:

Number of setups 195 Number of setup hours Setup costs Month $52,300 920 1,340 240 63,850 28,740 3 100 580 220 1,900 118,420 4 1,840 89,440 140 1,950 106,880 230 210 1,490 104,810 600 45,040 150 185 1,640 110,520