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Mlb Regression Analysis Data

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Mlb Regression Analysis Data
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Log(Attendance) = B1wins + B2FCI + B3tktprice + B4payroll + B5state + B6earnspop

In order to explain the effect that winnings percentage has on attendance, I have created an adjusted economic model that I have specified above. In order to test my economic model, I have compiled data for each of the variables specified in the model from the years 2003 to 2005.
The question that I will be answering in my regression analysis is whether or not wins have an affect on attendance in Major League Baseball (MLB). I want to know whether or not wins and other variables associated with attendance have a positive impact on a team 's record. The y variable in my analysis is going to be attendance for each baseball team. I collected the data for each team 's average attendance for 2003-2005 from an internet site entitled www.baseballreference.com. The summary statistics for this variable show that the mean winning percentage for all MLB teams is 50.4 percent with a standard deviation of 7.6 percent. There is a minimum and maximum of 27 percent and 65 percent respectively. I am taking the log of attendance in order to explain relationships with the independent variables in the form of percent changes in our dependent variable.
The main independent variable that I am going to be looking at, as stated above is winning percentage, and its effects on a team 's attendance. I feel that winning percentage is positively related to attendance as a team with a higher winning percentage will be more likely to attract fans than a team with a low winning percentage. Fans want to see their teams perform well during the season and are therefore more likely to attend games when their team does so. I obtained my data for attendance from a site entitled www.baseballreference.com. The total attendance over the time period of 2003-2005 was 2,395,300 with a standard error of 686,650. There was a minimum attendance of 749,550 and a maximum total attendance of 4,090,700.

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