Q#01: Identify the key variables that are likely to be related to ticket and concession sales.
Answer:
There are always some variables that are going to have an impact upon the tickets sold and the concession sales. Hence, as per the case, the key variables, which are related to the concession sales and the number of single game tickets sold includes the weekday or weekend that simply means day of the week of game.
Moreover, the key variable is going to be the opponent, which is comprised of both non-conference and conference teams. Lastly, the variable that is going to have an impact is the performance, which has been shown by the team players of Men’s basketball.
Q#02: Use multiple linear regression to develop two models: one for predicting the ticket sales and one for predicting concession sales.
Answer:
The evaluation of coefficients has been used in order to make an estimation of the number of tickets sold and the concession sales, respectively. The multiple regression analysis has been used to estimate these variables. However, the coefficient of ticket sales is 27.00% whereas; the coefficient of concession sales is 74.00%.
Despite this, it is worth mentioning that the overall decision is going to be made based on the percentage of Adjusted R Square relatively. Therefore,by taking account of the percentages under both the ticket sales and the concession sales the higher percentages are based related to the concession sales. Moreover, it can be seen by taking into consideration, the percentage of multiple R based on the concession sales, which is almost 97.00% and despite this, the value of multiple R under single game tickets sold is almost 65.00%.
In addition to this, now by looking at the percentage of significance under concession sales and the tickets sold, it is equal to 0%. This means that the sales of the tickets and the concession sales have more impact on the opponents, which includes conference and non-conference.
Hence, if there is a change in concession sales by $1,then it will also result in the change of opponents. In addition, if there is a variation in the ticket sales, then it is also going to impact upon the opponents. Despite this, the change in both of these two variables is presented in percentage terms in order to present a clear picture.
Moreover, the average growth rates based on the ticket sales and the concession sales have also been calculated as per the exhibits. Hence, the average growth rate of ticket sales is 20.1% and the average growth rate of concession revenues is 26.4%. Apart from that, the average growth rate of concession sales is higher than the tickets sold.
It has been calculated by taking into account the various percentages based on single game tickets sold and the concession revenues. The numbers of observations that are taken into account are almost 67 for both of the variables.
Apart from that, under the multiple regression statistics, it can be seen that the Adjusted R Square of concession sales is 94.00% and Adjusted R Square of ticket sales is 41.00%. It is also worth mentioning that if the figure of Adjusted R Square it is a good sign.
However,the value related to the coefficients under multiple regression analysis is better than the values that are obtained in other forecasting methods. Hence, the increase in revenue streams from men’s basketball team will enable the University of Wyoming to overcome the expenses of $9 million that are currently being provided by the university.
Hence, by having increased sales, the University of Wyoming would be able to keep its focus on the key areas, respectively. Previously, it can be seen that most of the expenses were covered by the sporting events. The other reason behind the recovery of high expenses and higher revenues was the increased base of loyal fans.
Moreover, the average sales of the ticket related to the fiscal year 2011 is 3521 and the average growth rate is almost 20.1%. However, the average concession sales in year 2011 were$10843 as per the exhibits and the average growth rate was 26.4%.
Q#03: Develop a simulation model to predict total revenue for a single 16-game season. One variable in your simulation model should be the team’s win percentage. The simulation model should be entered into a spreadsheet to facilitate multiple replications.
Answer:
As per the exhibits, the simulation model has been entered into the spreadsheet, which includes the total revenue of $50709 million. Hence, the net profit and the fixed costs and the unit costs have also been mentioned in the simulation model........................
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