The Oaklands A’s (A)
Using the data presented in Exhibit 1 (which is available in an Excel file), how would you predict ticket sales to a particular Oakland A's game?
ANS:
The analysis have been made on data given in the case study under Exhibit 1, the ticket sale of Oakland A’s game resulted from the regression analysis using the multi-variable regression model. To calculate the sale, all the available information about the ticketing was used in this Multi-Regression model. From the Exhibit 1 data, the dependent variable is the number of tickets sold and independent variables are: double header, teams, position, behind, week, temperature, percipitation, game, televised, promotions and Nobel. Regression analysis model describes the relationship between the expected variable and reaction variables by generating the equation. The P-value of regression analysis using all the available variables shows the acceptance and rejection of particular variables. The model also used the Durbin Watson D test and from this test the auto-correlation within the dependant variable and independent variables are defined. This test is always between 0 and 4. A 0 value represents positive auto-correlation and a value of 4 indicates the negative auto-correlation. If the value is 2 then, it means that there is no auto-correlation between the dependent and independent variables. The P-value of the regression test explains that how much these independent variables are significant to dependent variable.......................
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