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A The te perdoret pertemua to vote and to the meeting in the percentage of own way we conferenca (Can), Wher on the the percentage of our team int/ Cat / MC 65 0.00 500 MFC 7.1 0.002 0.033 0.004 25 GP 933 2014 0 Tulis 33223-223 0.000 125 46 023 JLS 3333333333333 0.020 hrew Sant 0.021 75 01044 500 San Francis 5 6.7 0.034 > on Red 0.041 1 Derson would be to protectors wonen ams. To investigate the importance of passing on the percentage of games won by a team, the following data show the conference (Col), average number of passing yards per ge of games won (Win%) for a random sample of 16 NFL teams for one full season program is recommended. Hational Football League (NFL) records a variety of performance Tata for individuals and teams. To investigate pt (Yds/Att), the number of interceptions thrown per attempt (It/Att), and the percentage of games won (WI Team Conf Yds/Att Int/Att Win% Arizona Cardinals NFC 6.5 0.042 50.0 Atlanta Falcons NFC 7.1 0.022 62.5 Carolina Panthers NFC 7.4 0.033 37.5 Cincinnati Bengals AFC 6.2. 0.026 56.3 Detroit Lions NFC 7.2 0.024 62.5 Green Bay Packers NFC 8.9 0.014 93.8 Houstan Texans AFC 7.5 0.019 62.5 Indianapolis Colts AFC 5.6 0.026 12.5 Jacksonville Jaguars AFC 4.6 0.032 31.3 Minnesota Vikings NFC 5.8 0.033 18.8 New England Patriots AFC 8.3 0.020 81.3 New Orleans Saints NFC 8.1 0.021 81.3 Oakland Raiders AFC 7.6 0.044 50.0 San Francisco 49ers NFC 6.5 0.011 81.3 Tennessee Titans AFC 6.7 0.024 56.3 Washington Redskins NFC 6.4 0.041 31.3 a) Develop the estimated regression equation that could be used to predict the percentage of games won givent We NC 0.041 LOW, in the women and women we were There are all The the Other than the actual DATAfile: MLBPitching A statistical program is recommended. 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 ERA SO/IP HR/IP R/IP w 245 2.40 Verlander, DET 1.00 0.10 0.29 Beckett, BOS 13 7 2.89 0.91 0.11 0.34 Wilson, TEX 16 7 2.14 0.92 0.07 0.40 Sabathia, 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 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 CWS Buthrie, M 13 9 3.59 0.53 0.10 0.45 SEA 9 Pineda, M 10 3.74 0.11 1.01 0.44 NYY Colon, B 8 10 4.00 0.82 0.13 0.52 Tomlin, CLE 12 4.25 0.54 0.48 0.15 9 MIN 4.30 Pavano, 13 0.46 0.10 0.55 McCarthy 132 12 000 0. an . 1112 OS 15 SEA 1414141 ta 0.40 Bu CW 19 10 045 PAH SA 1024 011 844 C 104.00 . 0.13 12 0.54 15 PwC HIN 0.46 0.10 40 #4 D CWS 011 00 he BAL 0.63 0.54 0.54 0.17 011 Sche. DET 0 0.15 053 De W 0.13 0:53 DET 6.75 0.57 0.10 0.57 (*) estimated regression equation was developed to the average number of runs von per ning pitched over the average sumber of respect and the neerumber of nero per ringed W Round your answers to four doces) RE (D) Does the estimated regression to provide a good to the catalan Considering the nature of the data, being able to explain why Send than 50% of the water from per ning pitched og pengen van Suppose the camerun verge (RA) is the dependent variable the reviews on the member of give up ping pitched the the data deel van som of the way I ERA can be explained by the literatur one rura per ning pitched (/2) and strike-outs per inning picted some Elet der the Since 10 - Player Team 3 L ERA SO/IP HR/IP R/IP Verlander, DET 24 5 2.40 1.00 0.10 0.29 Beckett, BOS 13 7 2.89 0.91 0.11 0.34 Wilson, 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, BOS 15 9 347 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 00 10 4.00 0.82 0.13 0.52 Tomlin, 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, CWS 8 12 4.33 0.79 0.11 0.52 Guthrie, ) BAL 9 17 4.33 0.63 0.13 0.54 Lewis, 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 The te perdoret pertemua to vote and to the meeting in the percentage of own way we conferenca (Can), Wher on the the percentage of our team int/ Cat / MC 65 0.00 500 MFC 7.1 0.002 0.033 0.004 25 GP 933 2014 0 Tulis 33223-223 0.000 125 46 023 JLS 3333333333333 0.020 hrew Sant 0.021 75 01044 500 San Francis 5 6.7 0.034 > on Red 0.041 1 Derson would be to protectors wonen ams. To investigate the importance of passing on the percentage of games won by a team, the following data show the conference (Col), average number of passing yards per ge of games won (Win%) for a random sample of 16 NFL teams for one full season program is recommended. Hational Football League (NFL) records a variety of performance Tata for individuals and teams. To investigate pt (Yds/Att), the number of interceptions thrown per attempt (It/Att), and the percentage of games won (WI Team Conf Yds/Att Int/Att Win% Arizona Cardinals NFC 6.5 0.042 50.0 Atlanta Falcons NFC 7.1 0.022 62.5 Carolina Panthers NFC 7.4 0.033 37.5 Cincinnati Bengals AFC 6.2. 0.026 56.3 Detroit Lions NFC 7.2 0.024 62.5 Green Bay Packers NFC 8.9 0.014 93.8 Houstan Texans AFC 7.5 0.019 62.5 Indianapolis Colts AFC 5.6 0.026 12.5 Jacksonville Jaguars AFC 4.6 0.032 31.3 Minnesota Vikings NFC 5.8 0.033 18.8 New England Patriots AFC 8.3 0.020 81.3 New Orleans Saints NFC 8.1 0.021 81.3 Oakland Raiders AFC 7.6 0.044 50.0 San Francisco 49ers NFC 6.5 0.011 81.3 Tennessee Titans AFC 6.7 0.024 56.3 Washington Redskins NFC 6.4 0.041 31.3 a) Develop the estimated regression equation that could be used to predict the percentage of games won givent We NC 0.041 LOW, in the women and women we were There are all The the Other than the actual DATAfile: MLBPitching A statistical program is recommended. 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 ERA SO/IP HR/IP R/IP w 245 2.40 Verlander, DET 1.00 0.10 0.29 Beckett, BOS 13 7 2.89 0.91 0.11 0.34 Wilson, TEX 16 7 2.14 0.92 0.07 0.40 Sabathia, 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 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 CWS Buthrie, M 13 9 3.59 0.53 0.10 0.45 SEA 9 Pineda, M 10 3.74 0.11 1.01 0.44 NYY Colon, B 8 10 4.00 0.82 0.13 0.52 Tomlin, CLE 12 4.25 0.54 0.48 0.15 9 MIN 4.30 Pavano, 13 0.46 0.10 0.55 McCarthy 132 12 000 0. an . 1112 OS 15 SEA 1414141 ta 0.40 Bu CW 19 10 045 PAH SA 1024 011 844 C 104.00 . 0.13 12 0.54 15 PwC HIN 0.46 0.10 40 #4 D CWS 011 00 he BAL 0.63 0.54 0.54 0.17 011 Sche. DET 0 0.15 053 De W 0.13 0:53 DET 6.75 0.57 0.10 0.57 (*) estimated regression equation was developed to the average number of runs von per ning pitched over the average sumber of respect and the neerumber of nero per ringed W Round your answers to four doces) RE (D) Does the estimated regression to provide a good to the catalan Considering the nature of the data, being able to explain why Send than 50% of the water from per ning pitched og pengen van Suppose the camerun verge (RA) is the dependent variable the reviews on the member of give up ping pitched the the data deel van som of the way I ERA can be explained by the literatur one rura per ning pitched (/2) and strike-outs per inning picted some Elet der the Since 10 - Player Team 3 L ERA SO/IP HR/IP R/IP Verlander, DET 24 5 2.40 1.00 0.10 0.29 Beckett, BOS 13 7 2.89 0.91 0.11 0.34 Wilson, 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, BOS 15 9 347 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 00 10 4.00 0.82 0.13 0.52 Tomlin, 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, CWS 8 12 4.33 0.79 0.11 0.52 Guthrie, ) BAL 9 17 4.33 0.63 0.13 0.54 Lewis, 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
