
Concept explainers
At the beginning of this chapter, we presented data on shoe size and height for a sample of students at Arizona State University. Using the
- a. Separate the data in the table on page 658 into two tables, one for males and the other for females. Parts (b)–(j) are for the male data.
- b. Determine the sample regression equation with shoe size as the predictor variable for height.
- c. Perform a residual analysis to decide whether considering Assumptions 1–3 for regression inferences to be satisfied by the variables shoe size and height appears reasonable.
- d. Find and interpret the standard error of the estimate.
- e. Determine the P-value for a test of whether shoe size is useful for predicting height. Then refer to Table 9.8 on page 386 to assess the evidence in favor of utility.
- f. Find a point estimate for the
mean height of all males who wear a size 10½ shoe. - g. Obtain a 95% confidence interval for the mean height of all males who wear a size 10½ shoe. Interpret your answer.
- h. Determine the predicted height of a male who wears a size 10½ shoe.
- i. Find a 95% prediction interval for the height of a male who wears a size 10½ shoe. Interpret your answer.
- j. At the 5% significance level, do the data provide sufficient evidence to conclude that shoe size and height ate
positively linearly correlated ? - k. Repeat parts (b)–(j) for the unabridged data on shoe size and height for females. Do the estimation and prediction problems for a size 8 shoe.
- l. Repeat part (k) for the data on shoe size and height for females with the outlier removed. Compare your results with those obtained in part (k).

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- Theorem 7.2 Suppose that E X = 0 for all k, that Var X = 0} x) ≤ 2P(S>x 1≤k≤n S√2), -S√2). P(max Sk>x) ≤ 2P(|S|>x- 1arrow_forwardThree players (one divider and two choosers) are going to divide a cake fairly using the lone divider method. The divider cuts the cake into three slices (s1, s2, and s3).If the chooser's declarations are Chooser 1: {s3} and Chooser 2: {s3}, which of the following is a fair division of the cake?arrow_forwardTheorem 1.4 (Chebyshev's inequality) (i) Suppose that Var X x)≤- x > 0. 2 (ii) If X1, X2,..., X, are independent with mean 0 and finite variances, then Στη Var Xe P(|Sn| > x)≤ x > 0. (iii) If, in addition, X1, X2, Xn are identically distributed, then nVar Xi P(|Sn> x) ≤ x > 0. x²arrow_forwardTheorem 2.5 (The Lyapounov inequality) For 0arrow_forwardTheorem 1.6 (The Kolmogorov inequality) Let X1, X2, Xn be independent random variables with mean 0 and suppose that Var Xk 0, P(max Sk>x) ≤ Isk≤n Σ-Var X In particular, if X1, X2,..., X, are identically distributed, then P(max Sx) ≤ Isk≤n nVar X₁ x2arrow_forwardTheorem 3.1 (The Cauchy-Schwarz inequality) Suppose that X and Y have finite variances. Then |EXYarrow_forwardarrow_back_iosSEE MORE QUESTIONSarrow_forward_iosRecommended textbooks for you
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