Question

A statistcal pregram is recommended Major League Baseball [MLB) pitching statistics were reported for ฉิ random sample of 20 pitchers from the American League for one full season. Player Team L ERA SO/IP HR/IP R/IP Verlander, J Beckett, Wison, C Sabathia, C NYY Haren, D McCarthy, OAK 993.32 0.72 0.06 0.43 Santans, E Lester, ) Hernande, F SEA 1414 3.47 095 008 0.42 Buehrle, M Pineda, M Colon, B Tomlin, Pavano, C Danks, ) Guthrie, Lewis, C Scherzer, M Davis, W Porcello, R DET 2.40 1.00 0.100.29 J DET 24 5 BOS 13 7 12.89 0.91 TEX 16 72.9 0.92 0.11 0.34 LAA 16 103.17 080.08 0.38 LAA 11 12 3.380.78 0.11 0.42 47 0.950.100.40 BOS 15 CWS 13 9 3.5 053 SEA 0 3.741.00.1 CLE 12 74.25 0.54015 0.48 MJN 9 13 4.30 0.46 CWS 8 12 4,33 0.79 BAL 9 174.33 0.63 0 TEX 14 0 4.400.84 0.11 0.52 0.13 0.54 170.51 .570.130.52 TB 11 | 10| 4.45 0.57 14 9 4.75 0.57 (a) An cstimated rogrsion squation was developed reiatingthe vera number ot runs given up per inning pitched given the average number of strikcouts per inning pitched and the average number of homeruns per inning pitched. What are the v o R an (Rond your answers to four decimal places

Answer 1

Compute an estimated regression equation by using MINITAB MINITAB procedure Step 1: Choose Stat > Regression > Regression Step 2 In Response, enter the column RIP Step 3: In Predictors, enter the column SOIP, HRIP Step 4: Click OK. MINITAB output Regression Analysis: R/IP versus SOIP, HRIP The regression equation is R/1p 0.537-0.248 SO/1P + 1.03 HR/IP Predictor Constant 0.53651 0.081416.59 0.000 SO/IP HR/IP Coef SE Coef -0.24835 0.071813.46 0.003 1.0319 0.4359 2.37 0.030 S 0.0537850 R-Sq 56.34 R-Sq (adj ) 51.2% # Analysis of Variance Source Regression Residual Error 17 0.049178 0.002893 Total DE MS 2 0.063477 0.031738 10.97 0.001 19 0.112655 Source DF SO/IP HR/IP 1 0.016214 Seq ss 1 0.047263 Unusual Observations Obs SO/IP R/IP Fit SE Fit Residual St Resid 1 1.00 0.2900 0.3914 0.0194 -0.1014 -2.02R R denotes an observation with a large standardized residual From the MINITAB output the estimated regression equation is R/IP 0.537-0.248 (SOIP 1.03 (HR/IP)

r^2 = 0.5635

R^2_a = 1 - (1- 0.563463 ) *19/17

= 0.5121