This preview shows pages 1–2. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.View Full Document
Unformatted text preview: 206 CHAPTER 12. LINEAR REGRESSION AND CORRELATION b. r = -0.8, significant c. yhat = 48.4-0.00725x d. For every one pound increase in weight, the fuel efficiency decreases by 0.00725 miles per gallon. (For every one thousand pound increase in weight, the fuel efficiency decreases by 7.25 miles per gallon.) e. 64% of the variation in fuel efficiency is explained by the variation in weight using the regression line. g. yhat=48.4-0.00725(3000)=26.65 mpg. y-yhat=25-26.65=-1.65. Because yhat=26.5 is greater than y=25, the line overestimates the observed fuel efficiency. h. (2750,38) is the outlier. Be sure you know how to justify it using the requested graphical or numerical methods, not just by guessing. i. yhat = 42.4-0.00578x j. Without outlier, r=-0.885, rsquare=0.76; with outlier, r=-0.8, rsquare=0.64. The new linear model is a better fit, after the outlier is removed from the data, because the new correlation coefficient is farther from 0 and the new coefficient of determination is larger....
View Full Document