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Significance Levels for baseball data; Spearman's Rank-Order correlation

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1. Refer to the baseball data for 2005 on 30 major league teams (see bottom of page). Use a Contingency Table to analyze the relationship between games won and salary. Set up a variable that divides the teams into two groups, those that had a winning season and those that did not. There are 162 games in the season, so define a winning team as having won 82 or more games. Next, divide the teams into two salary groups. Let the 15 teams with the largest salaries be in one group and the 15 teams with the smallest salaries in the other group. At the .05 level of significance is there a relationship between salary and winning?

B. Use Spearman's Rank-Order Correlation method to compute the coefficient of correlation between salary and the number of wins. Test the significance of this correlation using the t-test. At the .05 and .01 level of significance, is there a relationship between salary and winning?

C. Use linear regression analysis to compute the correlation between Wins and Salary. List the regression equation, and all associated regression output. At the .05 and .01 level of significance, is there a relationship between salary and winning?

BASEBALL TEAM TABLE OF SALARIES AND WINS (BELOW):

Team: Sal-mil Wins

Boston 123.5 95.0
New York Yankees 208.3 95.0
Oakland 55.4 88.0
Baltimore 73.9 74.0
Los Angles Angels 97.7 95.0
Cleveland 41.5 93.0
Chicago White Sox 75.2 99.0
Toronto 45.7 80.0
Minnesota 56.2 83.0
Tampa Bay 29.7 67.0
Texas 55.8 79.0
Detroit 69.1 71.00
Seattle 87.8 69.0
Kansas City 36.9 56.0
Atlanta 86.5 90.0
Arizona 62.3 77.0
Houston 76.8 89.0
Cincinnati 61.9 73.0
New York Mets 101.3 83.0
Pittsburgh 38.1 67.0
Los Angeles 83.0 71.0
San diego 63.3 82.0
Washington 48.6 81.0
San Francisco 90.2 75.0
St. Louis 92.1 100.0
Florida 60.4 83.0
Philadelphia 95.5 88.0
Milwaukee 39.9 81.0
Chicago cubs 87.0 79.0
Colorado 48.2 67.0

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Significance level for baseball data is examined.

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Refer to the baseball data for 2005 on 30 major league teams (see bottom of page). Use a Contingency Table to analyze the relationship between games won and salary. Set up a variable that divides the teams into two groups, those that had a winning season and those that did not. There are 162 games in the season, so define a winning team as having won 82 or more games. Next, divide the teams into two salary groups. Let the 15 teams with the largest salaries be in one group and the 15 teams with the smallest salaries in the other group. At the .05 level of significance is there a relationship between salary and winning?
Answer: I created two variables. One was win_season, where a winning team was defined as having won 82 or more games (0 indicated a losing team and 1 indicated a winning team). The other variable was high_low_sal, where the 15 teams with the largest salaries were in one group and the 15 teams with the smallest salaries in the other group (1 indicated high salary and 0 indicated low ...

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