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A sports analyst wishes to have a linear regression model that predicts the number of wins using number of hits, number of home runs, and

A sports analyst wishes to have a linear regression model that predicts the number of wins using number of hits, number of home runs, and number of strikeouts over an entire season for future teams/seasons and will use this data as a representative sample.

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The following statistics were collected for 30 MLB (Major League Baseball) teams in 2016. Variable Description Wins Number of wins (out of 162 games) Hits Number of hits HR Number of home runs hit Strikeouts Number of strikeouts thrown A sports analyst wishes to create a linear regression model that predicts the number of wins using number of hits, number of home runs, and number of strikeouts over an entire season for future teams/seasons and will use this data as a representative sample. The following R output was generated. (Note: estimates, standard errors. and t values were rounded to two decimal places.) > lm_mlb summary(lrrl_mlb) Coefficients: Estimate Std. Error t value Pr(>|tl) (Intercept) 71.81 37.85 1.90 0.06894 Hits 0.04 0.02 1.91 0.06723 HR 0.10 0.05 2.06 0.04961 Stri keOuts 0.06 0.02 3.57 0.00143 Residual standard error: 8.183 on 26 degrees of freedom Multiple Rsquared: 0.4726, Adjusted Rsquared: 0.4117 Fstatistic: 7.765 on 3 and 26 DF, pva'lue: 0.0007302 Use the R output above to answer the following questions. 06.4 1 Point The sports analyst would like to run the following hypothesis test using a signicance level of 5%: Ho :H'its = 0 Ha l 5H2?\" > 0 What would be the corresponding pvalue'? Numeric answers only. Please do not include any additional text. Enter your answer here Save Answer 06.5 1 Point For every additional 20 home runs hit, we would estimate the average number of wins to increase by what value, controlling for number of hits and number of strikeouts thrown? Numeric answers only. Please do not include any additional text. Enter your answer here Save Answer 06.6 1 Point The sports analyst would like to determine if the linear regression model is statistically signicant overall at a 5% signicance level. What would be the null hypothesis? 031:52=l33 031:52=l33=0 Oo=l=2=3 Ou=5t=l52=l53=0 031=32=l3 0531:32: \"3:0 030=3t=32=3s 030=3t=32=33=0

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