Forecasting Ticket Revenue for Orlando Magic Basketball Games
1)
Based on the data set, the regression model obtained from the regression analysis is shown below.
Revenue = -15944 + 24334x
Where,
Revenue is the dependent variable and (x) day of the week as independent variable.
2)
Model with rating of the opponent as the sole independent variable is computed below:
The forecasting can be obtained based on the linear regression equation
y = a +bx
x = Independent variable (rating of the opponent)
y = additional potential sale
Values of a and b can be found
a = y - bx
b =
= 28/12 =2.33
= 855022/12 =71252
b = [3516679 - (12*2.33*71252)]/[134 - (12*2.33)^2)]
b = 22141
And
a = 71252 - 22141*2.33 = 19663
The regression equation
y = 19663 + 22141x
Where,
y = sales potential
x = rating of the opponent
3)
The first year Perez built his multiple-regression model,
y = 14,996 + 10,801x1 + 23,397x2 + 10,784x3
Where,
y =Additional sale potential
x1 =The day of the week
x2 =The rating of the opponent
x3 =The time of the year
Thursday MH games played during the Christmas.
x1 = The day of the week = Thursday = 3
x2 = The rating of the opponent = Rating of MH = 3
x3 = The time of the year = Games during Christmas Holiday = 3
Now,
y = 14,996 + 10801x1 + 23,397x2 + 10,784x3 or
y = 14,996 + 10,801*4 + 23,397*3 + 10,784*3 or
y = 160,743
Therefore, the additional sales potential of a Thursday MH game played during Christmas holiday is $160,743.
4)
The respective additional independent variable that can be included in the Perez’s model is highlighted below:
Forecasting Ticket Revenue for Orlando Magic Basketball Games Forecasting Ticket Revenue for Orlando Magic Basketball Games...
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