11.19 Predicting the price of tablets: Individual variables.
Suppose your company needs to buy some tablets. To help in the purchasing decision, you decide to develop a model to predict the selling price. You decide to obtain price and product characteristic information on 20 tablets from Consumer Reports.6 The characteristics are screen size, battery life, weight (pounds), ease of use, display, and versatility. The latter three are scored on a 1 to 5 scale.
tablts
11.19
(a)
Variable | Mean | Median | Std Dev |
---|---|---|---|
Price | 395.50 | 400.00 | 119.76 |
Size | 9.15 | 9.90 | 1.21 |
Battery | 11.11 | 10.55 | 2.57 |
Weight | 1.07 | 1.10 | 0.29 |
Ease | 4.55 | 5.00 | 0.51 |
Display | 4.30 | 4.00 | 0.47 |
Versatility | 3.80 | 4.00 | 0.41 |
(c) Price is roughly Normal. Size has a bimodal distribution. Battery is right-skewed. Ease, Display and Versatility all only have 2 different values even though they were rated on a 1 to 5 scale. There aren’t really any unusual observations that might affect the regression analysis. (d) No, we do not make any assumption on the distribution of explanatory variables, so this is perfectly fine.