INTRODUCTORY STATISTICS (LOOSELEAF)
INTRODUCTORY STATISTICS (LOOSELEAF)
3rd Edition
ISBN: 9780135163146
Author: Gould
Publisher: PEARSON
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Chapter 4, Problem 69SE

Predicting Home Runs Data on the number of home runs, strikeouts, and batting averages for a sample of 50 Major League Baseball players were obtained. Regression analyses were conducted on the relationships between home runs and strikeouts and between home runs and batting averages. The StatCrunch results are shown below. (Source: mlb.com)

Simple linear regression results:

Dependent Variable: Home Runs

Independent Variable: Strikeouts

Home Runs = 0.092770565 + 0.22866236 Strikeouts

Sample size: 50

R (correlation coefficient) = 0.63591835

R-sq = 0.40439215

Estimate of error standard deviation: 8.7661607

Simple linear regression results:

Dependent Variable: Home Runs

Independent Variable: Batting Average

Home Runs = 45.463921 71.232795 Batting Average

Sample size: 50

R (correlation coefficient) = 0.093683651

R-sq = 0.0087766264

Estimate of error standard deviation: 11.30876

Based on this sample, is there a stronger association between home runs and strikeouts or home runs and batting average? Provide a reason for your choice based on the StatCrunch results provided.

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Chapter 4 Solutions

INTRODUCTORY STATISTICS (LOOSELEAF)

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