# Introduction

At university of Wyoming, the home games has been played by basketball team containing men, the team has tremendously generated revenues for the university’s athletic department. The issue arises when the department had to forecast the revenues for the upcoming basketball season, this is due to the ending of session between 2009 and 2010. Though, the department has set the prices of ticket, it has been creating trouble for the department in estimating the revenues, nonetheless for the year between 2010 and 2011, the schedule of home games had not known.  Another problem had arisen due to the uncertain and unsure estimation of ticket and concession sales.

# Question No: 1

The variables that are equitably important for the ticket and concession sales is the weekend and weekdays which means week days of game.

Another variable is both non-conference and conference teams, by associating with the opponents would most likely act as a determinant for the university to avoid extra investment or financing on expanding new groups, however this might leverage the business revenue.

Moreover, it is significantly important for each member of team to put out all the stops for increasing revenues. Factually, the revenues are highly based on how the team members are performing and carrying out, the exceptional performance is required to better project revenues.

University of Wyoming Men’s Basketball Harvard Case Solution & Analysis.

# Question No. 02

Prediction of ticket sales

The statistical tool i.e. regression is used in order to predict ticket sales and concession sales, it is being analyzed that the 27 percent is the coefficient of ticket sales which indicates that the value of ticket sales which is independent variable tends to be increases because the coefficient of predicting ticket sales is positive. If ticket sales increases by one unit, there would be 27% change in revenue. On the other hand, the multiple R value for the ticket sales is comparatively lower than concession sales i.e. 65 percent which means that the data is 65% fitted to the regression line. It can be seen below;

 Regression Statistics Multiple R 0.650444088 R Square 0.423077512 Adjusted R Square 0.414201781 Standard Error 611.7027183 Observations 67

Prediction of concession sales

On contrary, the coefficient of concession sales is 74 percent which means that if concession sales increases by one unit, there would be 74% change in revenue. Also, the linear relationship is strong for the concession sales as it can be analyzed from the Multiple R value i.e. 97 percent or it can be said that the data is 97% fitted to the regression line.It can be seen in below;

 Regression Statistics Multiple R 0.970766 R Square 0.942387 Adjusted R Square 0.941501 Standard Error 468.0865 Observations 67

Regardless of this, it is mentioned in the case that the budget of approximately \$9 million is being provided by the university which can be reduced through increasing revenues, the best predictor of the revenues for upcoming session might be the statistical analysis rather than any other forecasting tool...................

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