{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

Intro to Stat_Part_64

# Intro to Stat_Part_64 - 206 CHAPTER 12 LINEAR REGRESSION...

This preview shows pages 1–2. Sign up to view the full content.

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. Solution to Exercise 12.27 (p. 202) a. All four data sets have the same correlation coefficient r=0.816 and the same least squares regression line yhat=3+0.5x b. Set 2 ; c. Set 4 ; d. Set 3 ; e. Set 1 Figure 12.1

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### Page1 / 3

Intro to Stat_Part_64 - 206 CHAPTER 12 LINEAR REGRESSION...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online