1 Normal 1 No Spac... Heading 1 Heading 2 Title Subtitle Subtle Em... Emphasis I

Question

1 Normal 1 No Spac... Heading 1 Heading 2 Title Subtitle Subtle Em... Emphasis Intense E.s Howard Univensity athletie department wants to develop its budget for the coming year, using a forecast for football attendance. Football attendance accounts for the largest portion of the University revenues. The new President of the university who is also a football fan has asked the athletic director to come up with strategies in promoting the university football team. The athletic director believes that attendance is directly related to the number of wins by the team. Instead of attempting to predict attendance based on only one variable (wins), the athletic department has included a second variable for advertising and promotional expenditures as well. The university president is anxious to know the result of this forecast to determine strategies that improve attendance and boost revenues for the University. The business manager of the BSU football team has accumulated total annual attendance figures for the past 8 years: Wins Promotion Attendance $14500 4070025100 56300 72000 21300 26200 38000 29000 660000 57000 40300 66600 24000 32500 Given the number of returning starters and the strength of the schedule, the athletic director believes the team will win at least seven games next year. He wants to develop a multiple regression equation for these data to forecast attendance for this level of success. Discussion questions 1. Given that Attendance as the dependent variable (Y) and Wins (X1) and Promotion (X2) 2. What is the strength of this relationship? Use the coefficient of determination R squared 3. Is the relationship significant? Use the "Fisher significance" from the excel output to as independent variables, use excel to estimate the relationship between attendance and promotion and wins. to describe this relationship determine this.

Explanation / Answer

1) Ans:

The regression equation is

Y=4647.7737+3560.9964*X1+0.03689*X2

2) Ans:

The coefficient of determination R squared is 0.9009. Hence, 90.09% of Y information can be explained by X1 and X2. It is a strong relationship.

Q3. Ans:

The estimated p-value is less than 0.05 level of significance. Hence, the relationship is significant.

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 4647.77366 4970.647855 0.935044 0.39268957 -8129.68343 17425.2307 X1 3560.9964 1499.981198 2.374027 0.06363417 -294.828018 7416.82082 X2 0.03689 0.101346358 0.363999 0.73074424 -0.22362911 0.29740911

Related Questions

Navigate

• Browse (All)
• Browse 1
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.