Bundle: Statistics for Business & Economics, Loose-Leaf Version, 13th + MindTap Business Statistics with XLSTAT, 1 term (6 months) Printed Access Card
Bundle: Statistics for Business & Economics, Loose-Leaf Version, 13th + MindTap Business Statistics with XLSTAT, 1 term (6 months) Printed Access Card
13th Edition
ISBN: 9781337148092
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: Cengage Learning
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Chapter 16.4, Problem 18E

Jeff Sagarin has been providing sports ratings for USA today since 1985. In baseball his predicted RPG (runs/game) statistic takes into account the entire player’s offensive statistics, and is claimed to be the best measure of a player’s true offensive value. The following data show the RPG and a variety of offensive statistics for a recent Major League Baseball (MLB) season for 20 members of the New York Yankees. The labels on columns are defined as follows: RPG, predicted runs per game statistic; H, hits; 2B, doubles; 3B, triples; HR, home runs; RBI, runs batted in; BB, bases on balls (walks); SO, strikeouts; SB, stolen bases; CS, caught stealing; OBP, on-base percentage; SLG, slugging percentage; and AVG, batting average.

Player RPG H 2B 3B HR RBI BB SO SB CS OBP SLG AVG
D Jeter 6.51 202 25 5 19 70 77 117 14 5 .3S9 .450 .309
H Matsui 6.32 192 45 3 23 116 63 7S 2 2 .367 .496 .305
A Rodriguez 9.06 194 29 1 4S 130 91 139 21 6 .421 .610 .321
G Sheffield 6.93 170 27 0 34 123 7S 76 10 2 .379 .512 .291
R Cano 5.01 155 34 4 14 62 16 6S 1 3 .320 .45S .297
B Williams 4.14 121 19 1 12 64 53 75 1 2 .321 .367 .249
J Posada 5.36 124 23 0 19 71 66 94 1 0 .352 .430 .262
J Giambi 9.11 113 14 0 32 S7 10S 109 0 0 .440 .535 .271
T Womack 2.91 S2 S 1 0 15 12 49 27 5 .276 .2S0 .249
T Martinez 5.0S 73 9 0 17 49 3S 54 2 0 .32S .439 .241
M Bellhorn 4.07 63 20 0 S 30 52 112 3 0 .324 .357 .210
R Sierra 3.27 39 12 0 4 29 9 41 0 0 .265 .371 .229
J Flaherty 1.S3 21 5 0 2 11 6 26 0 0 .206 .252 .165
B Crosby 3.4S 27 0 1 1 6 4 14 4 1 .304 .327 .276
M Lawton 5.15 6 0 0 2 4 7 S 1 0 .263 .250 .125
R Sanchez 3.36 12 1 0 0 2 2 3 0 1 .326 .302 .279
A Phillips 2.13 6 4 0 1 4 1 13 0 0 .171 .325 .150
M Cabrera 1.19 4 0 0 0 0 0 2 0 0 .211 .211 .211
R Johnson 3.44 4 2 0 0 0 1 4 0 0 .300 .333 .222
F Escalona 5.31 4 1 0 0 2 1 4 0 0 .375 .357 .2S6

Let the dependent variable be the RPG statistic.

  1. a. Develop the best one-variable estimated regression equation.
  2. b. Use the methods in this section to develop the best estimated multiple regression equation for predicting a player’s RPG.
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