Homework Help is Here – Start Your Trial Now!
Math
Statistics
Major League Baseball (MLB) pitching statistics were reported for a random sample of 20 pitchers from the American League for one full season. Player Team wL ERA ERA so/IP HR/IP R/IP Verlander, ) 24 5 2.40 DET 1.00 0.10 0.29 Beckett, , ) BOS | 13 7 2.89 0.91 0.11 0.34 Wilson, C 16 7 0.40 TEX 2.94 0.92 0.07 Sabathia, C NYY 19 8 3.00 0.97 0.07 0.37 Haren, D LAA 16 10 3.17 0.81 0.08 0.38 McCarthy, B OAK 9 9 3.32 0.72 0.06 0.43 Santana, E LAA 11| 12 3.38 0.78 0.11 0.42 Lester, ) BOS 15 9 3.47 0.95 0.10 0.40 Hernandez, F SEA | 14 14 3.47 0.95 0.08 0.42 Buehrle, M CwS 13 9 3.59 0.53 0.10 0.45 Pineda, M SEA |9 10 3.74 1.01 0.11 0.44 Colon, B 8 10 4.00 0.82 0.13 0.52 NYY 8 Tomlin, J 12 7 CLE 4.25 0.54 0.15 0.48 Pavano, C MIN 9 13 4.30 0.46 0.10 0.55 Danks, J Cws 8 8 12 4.33 0.79 0.11 0.52 Guthrie, J |9 17 4.33 BAL 0.63 0.13 0.54 Lewis, C TEX 14 10 4.40 0.84 0.17 0.51 Scherzer, M DET 15 9 4.43 0.89 0.15 0.52 Davis, w TB 11 10 4.45 0.57 0.13 0.52 Porcello, R DET 14 9 4.75 0.57 0.10 0.57 (a) An estimated regression equation was developed relating the average number of runs given up per inning pitched given the average number of strikeouts per inning pitched and the average number of home runs per inning pitched. What are the values of R? and R2? (Round your answers to four decimal places.) R2 = R2 =

Major League Baseball (MLB) pitching statistics were reported for a random sample of 20 pitchers from the American League for one full season. Player Team wL ERA ERA so/IP HR/IP R/IP Verlander, ) 24 5 2.40 DET 1.00 0.10 0.29 Beckett, , ) BOS | 13 7 2.89 0.91 0.11 0.34 Wilson, C 16 7 0.40 TEX 2.94 0.92 0.07 Sabathia, C NYY 19 8 3.00 0.97 0.07 0.37 Haren, D LAA 16 10 3.17 0.81 0.08 0.38 McCarthy, B OAK 9 9 3.32 0.72 0.06 0.43 Santana, E LAA 11| 12 3.38 0.78 0.11 0.42 Lester, ) BOS 15 9 3.47 0.95 0.10 0.40 Hernandez, F SEA | 14 14 3.47 0.95 0.08 0.42 Buehrle, M CwS 13 9 3.59 0.53 0.10 0.45 Pineda, M SEA |9 10 3.74 1.01 0.11 0.44 Colon, B 8 10 4.00 0.82 0.13 0.52 NYY 8 Tomlin, J 12 7 CLE 4.25 0.54 0.15 0.48 Pavano, C MIN 9 13 4.30 0.46 0.10 0.55 Danks, J Cws 8 8 12 4.33 0.79 0.11 0.52 Guthrie, J |9 17 4.33 BAL 0.63 0.13 0.54 Lewis, C TEX 14 10 4.40 0.84 0.17 0.51 Scherzer, M DET 15 9 4.43 0.89 0.15 0.52 Davis, w TB 11 10 4.45 0.57 0.13 0.52 Porcello, R DET 14 9 4.75 0.57 0.10 0.57 (a) An estimated regression equation was developed relating the average number of runs given up per inning pitched given the average number of strikeouts per inning pitched and the average number of home runs per inning pitched. What are the values of R? and R2? (Round your answers to four decimal places.) R2 = R2 =

Holt Mcdougal Larson Pre-algebra: Student Edition 2012
Holt Mcdougal Larson Pre-algebra: Student Edition 2012
1st Edition
ISBN:9780547587776
Author:HOLT MCDOUGAL
Publisher:HOLT MCDOUGAL
Chapter11: Data Analysis And Probability
Section11.4: Collecting Data
Problem 5E
See similar textbooks
icon
Related questions
Question
(b) Does the estimated regression equation provide a good fit to the data? Explain. Considering the nature of the data, being able to explain slightly --Select--- v than 50% of the variability in the number of runs given up per inning pitched using just two independent variables is --Select--- (c) Suppose the earned run average (ERA) is used as the dependent variable in the estimated regression equation from (a) instead of the average number of runs given up per inning pitched. Does the estimated regression equation that uses the ERA provide a good fit to the data? Explain. Since ---Select- v than 50% of the variability in the ERA can be explained by the linear effect of home runs per inning pitched (HR/IP) and strike-outs per inning pitched (SO/IP), this is ---Select--- performance. considering the complexity of predicting pitching
Transcribed Image Text:(b) Does the estimated regression equation provide a good fit to the data? Explain. Considering the nature of the data, being able to explain slightly --Select--- v than 50% of the variability in the number of runs given up per inning pitched using just two independent variables is --Select--- (c) Suppose the earned run average (ERA) is used as the dependent variable in the estimated regression equation from (a) instead of the average number of runs given up per inning pitched. Does the estimated regression equation that uses the ERA provide a good fit to the data? Explain. Since ---Select- v than 50% of the variability in the ERA can be explained by the linear effect of home runs per inning pitched (HR/IP) and strike-outs per inning pitched (SO/IP), this is ---Select--- performance. considering the complexity of predicting pitching
Major League Baseball (MLB) pitching statistics were reported for a random sample of 20 pitchers from the American League for one full season. Player Team w L ERA so/IP HR/IP R/IP Verlander, J DET 24 2.40 1.00 0.10 0.29 Beckett, J BOS 13 7 2.89 0.91 0.11 0.34 Wilson, C TEX 16 7 2.94 0.92 0.07 0.40 Sabathia, C NYY 19 8 3.00 0.97 0.07 0.37 Haren, D LAA 16 10 3.17 0.81 0.08 0.38 McCarthy, B OAK 9 9 3.32 0.72 0.06 0.43 Santana, E LAA 11 12 3.38 0.78 0.11 0.42 Lester, J BOS 15 9 3.47 0.95 0.10 0.40 Hernandez, F SEA 14 14 3.47 0.95 0.08 0.42 Buehrle, M CWS 13 9 3.59 0.53 0.10 0.45 Pineda, M SEA 9 10 3.74 1.01 0.11 0.44 Colon, B NYY 8 10 4.00 0.82 0.13 0.52 Tomlin, J CLE 12 7 4.25 0.54 0.15 0.48 Pavano, C MIN 9 13 4.30 0.46 0.10 0.55 Danks, J CWS 8 12 4.33 0.79 0.11 0.52 Guthrie, J BAL 9 17 4.33 0.63 0.13 0.54 Lewis, C TEX 14| 10 4.40 0.84 0.17 0.51 Scherzer, M DET 15 9 4.43 0.89 0.15 0.52 Davis, W TB 11 10 4.45 0.57 0.13 0.52 Porcello, R DET 14 9 4.75 0.57 0.10 0.57 (a) An estimated regression equation was developed relating the average number of runs given up per inning pitched given the average number of strikeouts per inning pitched and the average number of home runs per inning pitched. What are the values of R and R_? (Round your answers to four decimal places.) R2 = R. =
Transcribed Image Text:Major League Baseball (MLB) pitching statistics were reported for a random sample of 20 pitchers from the American League for one full season. Player Team w L ERA so/IP HR/IP R/IP Verlander, J DET 24 2.40 1.00 0.10 0.29 Beckett, J BOS 13 7 2.89 0.91 0.11 0.34 Wilson, C TEX 16 7 2.94 0.92 0.07 0.40 Sabathia, C NYY 19 8 3.00 0.97 0.07 0.37 Haren, D LAA 16 10 3.17 0.81 0.08 0.38 McCarthy, B OAK 9 9 3.32 0.72 0.06 0.43 Santana, E LAA 11 12 3.38 0.78 0.11 0.42 Lester, J BOS 15 9 3.47 0.95 0.10 0.40 Hernandez, F SEA 14 14 3.47 0.95 0.08 0.42 Buehrle, M CWS 13 9 3.59 0.53 0.10 0.45 Pineda, M SEA 9 10 3.74 1.01 0.11 0.44 Colon, B NYY 8 10 4.00 0.82 0.13 0.52 Tomlin, J CLE 12 7 4.25 0.54 0.15 0.48 Pavano, C MIN 9 13 4.30 0.46 0.10 0.55 Danks, J CWS 8 12 4.33 0.79 0.11 0.52 Guthrie, J BAL 9 17 4.33 0.63 0.13 0.54 Lewis, C TEX 14| 10 4.40 0.84 0.17 0.51 Scherzer, M DET 15 9 4.43 0.89 0.15 0.52 Davis, W TB 11 10 4.45 0.57 0.13 0.52 Porcello, R DET 14 9 4.75 0.57 0.10 0.57 (a) An estimated regression equation was developed relating the average number of runs given up per inning pitched given the average number of strikeouts per inning pitched and the average number of home runs per inning pitched. What are the values of R and R_? (Round your answers to four decimal places.) R2 = R. =
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 3 steps

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Recommended textbooks for you
Holt Mcdougal Larson Pre-algebra: Student Edition…
Holt Mcdougal Larson Pre-algebra: Student Edition…
Algebra
ISBN:
9780547587776
Author:
HOLT MCDOUGAL
Publisher:
HOLT MCDOUGAL
Glencoe Algebra 1, Student Edition, 9780079039897…
Glencoe Algebra 1, Student Edition, 9780079039897…
Algebra
ISBN:
9780079039897
Author:
Carter
Publisher:
McGraw Hill
College Algebra (MindTap Course List)
College Algebra (MindTap Course List)
Algebra
ISBN:
9781305652231
Author:
R. David Gustafson, Jeff Hughes
Publisher:
Cengage Learning
Big Ideas Math A Bridge To Success Algebra 1: Stu…
Big Ideas Math A Bridge To Success Algebra 1: Stu…
Algebra
ISBN:
9781680331141
Author:
HOUGHTON MIFFLIN HARCOURT
Publisher:
Houghton Mifflin Harcourt
College Algebra
College Algebra
Algebra
ISBN:
9781938168383
Author:
Jay Abramson
Publisher:
OpenStax
SEE MORE TEXTBOOKS