1. Data was collected on 82 vehicles of different models to study the relationship between the weight of a vehicle (wt) and the miles per gallon (mpg) of the vehicle. The output from a regression analysis of the data is attached to the end of the sheet. a)Use the estimated linear regression model for predicting miles per gallon from weight to predict the miles per gallon for a vehicle with a weight of 40. b)Given that the mean weight of vehicles in the sample was 30.9, and that the corrected sum of squares (Sxx ) for weight was 5369., compute an interval estimate of the miles per gallon for an individual vehicle with a weight of 40. c) Here is a listing for a subset of the vehicle data: mpg wt 40.9 22.5 38.4 25.0 33.2 30.0 31.4 30.0 23.6 40.0 19.5 45.0 For this subset of the data, list the Y and X matrices that would be used in the matrix-based approach to regression for predicting miles per gallon from weight. Assume that the simple linear regression model yi = B0 + B1xi + ei used. d) For the vehicle data, what is the correlation coefficient value between weight and miles per gallon?
1. Data was collected on 82 vehicles of different models to study the relationship between the weight of a vehicle (wt) and the miles per gallon (mpg) of the vehicle. The output from a
a)Use the estimated linear regression model for predicting miles per gallon from weight to predict the miles per gallon for a vehicle with a weight of 40.
b)Given that the mean weight of vehicles in the sample was 30.9, and that the corrected sum of squares (Sxx ) for weight was 5369., compute an
c) Here is a listing for a subset of the vehicle data:
| mpg | wt |
| 40.9 | 22.5 |
| 38.4 | 25.0 |
| 33.2 | 30.0 |
| 31.4 | 30.0 |
| 23.6 | 40.0 |
| 19.5 | 45.0 |
For this subset of the data, list the Y and X matrices that would be used in the matrix-based approach to regression for predicting miles per gallon from weight. Assume that the simple linear regression model yi = B0 + B1xi + ei used.
d) For the vehicle data, what is the
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