chapter 1

Chapter 13: Nonlinear and Multiple Regression4.a. The (x, residual) pairs for the plot are (0, -.335), (7, -.508), (17. -.341), (114, .592), (133,.679), (142, .700), (190, .142), (218, 1.051), (237, -1.262), and (285, -.719). The plotshows substantial evidence of curvature.b. The standardized residuals (in order corresponding to increasing x) are -.50, -.75, -.50,.79, .90, .93, .19, 1.46, -1.80, and -1.12. A standardized residual plot shows the samepattern as the residual plot discussed in the previous exercise. The z percentiles for thenormal probability plot are –1.645, -1.04, -.68, -.39, -.13, .13, .39, .68, 1.04, 1.645. Theplot follows. The points follow a linear pattern, so the standardized residuals appear tohave a normal distribution.Normal Probability Plot for the Standardized Residuals1std resid0-1-2-2-1012percentile5.a. 97.7% of the variation in ice thickness can be explained by the linear relationshipbetween it and elapsed time. Based on this value, it appears that a linear model isreasonable.b. The residual plot shows a curve in the data, so perhaps a non-linear relationship exists.One observation (5.5, -3.14) is extreme.21residual0-1-2-30123456elapsed time395