No notecard for this quiz!! Quiz 11.1 Review No notecard for this quiz!! I will have the following formula on the board for your use if necessary.

Key Concept The slope b1 of the regression line varies less from sample to sample when: Sample size is larger Residuals are smaller Values of x are further apart

x = 15 If you want a regression equation with the smallest estimated standard error of the slope, which of these lists would you use for the values of the explanatory variable? You may assume that each conditional distribution of y has the same variability. A. 5, 10, 15, 20, 25 B. 5, 5, 5, 15, 15, 15, 25, 25, 25 C. 5, 5, 5, 5, 5, 25, 25, 25, 25, 25 D. 5, 5, 10, 10, 15, 15, 20, 20, 25, 25 E. 10, 10, 10, 15, 15, 15, 20, 20, 20

Page 750, P5 a. The standard deviation, σ, of the individual response values of y at each value of x: 3 or 5

Page 750, P5 b. The spread of the x-values: 3 or 10

Page 750, P5 c. The number of observations, n: 10 or 20

Page 750, P5 d. the true slope, β1: 1 or 3

Page 750, P5 e. the true intercept, βo: 1 or 7

Consider the scatterplots below. In which scatterplots is it reasonable to model the relationship between y and x with a line? I, III, IV, V (must be linear pattern)

Consider the scatterplots below. If you fit a line through each scatterplot by the method of least squares, which plot will give a line with slope closest to 0? IV (points most scattered)

Consider the scatterplots below. In which scatterplots is it meaningful to use correlation to describe the relationship between y and x? I, III, IV, V (must be linear pattern)

Consider the scatterplots below. Which plot shows a correlation coefficient closest to 1? V (points packed tightest to LSRL)

Page 744, D4 Two potential problems here. First, the data appear to have curvature. The centers of the conditional distributions of y do not lie on a straight line, which is one of the conditions for a linear fit.

Page 744, D4 Second, the conditional distribution of responses at x = 2 has far greater variation than either of the other two conditional distributions. The assumption of equal variances of responses across all values of x is violated.