8.1. Suppose you know statistics for X and Y shown below. You also know that the correlation of X to Y is 0.56. Use these to determine the equations of the least-squares best fit regression model to predict Y as a function of X. Produce a graph of this regression equation. Show all work.
Statistic | X-Variable | Y-Variable |
Mean | 15.27 | 107.93 |
Standard Deviation | 7.82 | 38.77 |
First Quartile | 5.3 | 47.1 |
Median | 15.2 | 105.4 |
Third Quartile | 22.6 | 160.3 |
8.2. The regression output below was developed from data relating the monthly usage of electricity (MonthlyUsage, measured in kilowatt-hours) to the size of homes (HomeSize, measured in square feet). One-variable statistics for each of these variables is also given below.
Results of simple regression for Monthly Usage
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Summary measures | |||||||
| Multiple R | 0.9120 | |||||
| R-Square | 0.8317 | |||||
| StErr of Est | 133.4377 | |||||
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ANOVA Table | |||||||
| Source | df | SS | MS | F | p-value | |
| Explained | 1 | 703957.1781 | 703957.1781 | 39.5357 | 0.0002 | |
| Unexplained | 8 | 142444.9219 | 17805.6152 | |||
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Regression coefficients | |||||||
| Lower | Upper | |||||
| Coefficient | Std Err | t-value | p-value | limit | limit | |
| Constant | 578.9277 | 166.9681 | 3.4673 | 0.0085 | 193.8984 | 963.9570 |
| HomeSize | 0.5403 | 0.0859 | 6.2877 | 0.0002 | 0.3421 | 0.7385 |
Summary measures for selected variables
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HomeSize | MonthlyUsage | |
Mean | 1880.000 | 1594.700 |
Median | 1775.000 | 1641.000 |
Standard deviation | 517.623 | 306.667 |
Minimum | 1290.000 | 1172.000 |
Maximum | 2930.000 | 1956.000 |
Variance | 267933.333 | 94044.678 |
First quartile | 1502.500 | 1321.250 |
Third quartile | 2167.500 | 1831.000 |
Interquartile range | 665.000 | 509.750 |
Skewness | 0.893 | -0.308 |
Kurtosis | 0.340 | -1.565 |
8.3. Pie in the Sky, Inc. runs a chain of pizza eateries (See data file C08 Pizza.xls [.rda].) The manager has collected data from each of the stores in the chain regarding the number of pizzas sold in one month, the average price of the pizzas, the amount the store spent on advertising that month, and the average disposable income of families in the area near the store.