Page 1 of 2 > | Module 7 Home Work Problems Q1: Cost Estimation Rock n' Roll Heaven is an outdoor pavilion that presents musical performers throughout a 6-month season, from late spring to early fall. Rock n' Roll presents a diverse venue of artists in a set of approximately 40 events each season. In order to better project its costs and expected attendance, Rock n' Roll uses regression analysis to project expected ticket sales for upcoming events for each performer. The regression results shown below are derived from the three most recent seasons. The dependent variable for Rock n' Roll is the number of paying tickets holders for each event, and the independent variables are: 1. whether or not this particular performer appeared at Rock n' Roll previously (a dummy variable, 0 if no and 1 if yes) 2. the spending on advertising targeted to the performer's appearance 3. the performer's local sales of CDs in the most recent year prior to their appearance 4. the number of television appearances for the performer in the most recent year 5. the number of public appearances in the U.S. by the performer in the recent year Independent Variables Results Regression intercept 1,224 Attendance at prior concert Coefficient 3,445 t-value 4.11 Spending on advertising Coefficient 0.113 t-value 1.88 Performer's CD sales Coefficient 0.00044 t-value 1.22 Television appearances Coefficient 898 t-value 2.4 Other Public performances Coefficient 1,233 t-value 3.7 R-squared 0.88 Standard error of the estimate 2,447 Required: 1. Using the above regression, what attendance would be predicted for a performer who had appeared at Rock n' Roll previously, had 6 other public appearances but no Page 2 of 2 > | TV appearances, CD sales of $10 million, and Rock n' Roll planned to spend $35,000 on advertising? (Hint: y = a + v1x1+v2x2+v3x3+v4x4+v5x5) 2. Evaluate the precision and reliability of the regression results shown above. What changes if any, do Which variables should be deleted, and which do you think should be added, and why? you propose for the regression? Q2: Cost Estimation, High-Low Method, Regression Analysis Lexcon, Inc is a large manufacturer of affordable DVD players. Management recently became aware of rising costs resulting from returns of malfunctioning products. As a starting point for further analysis, Paige Jennings, the controller, wants to test different forecasting methods and then use the best one to forecast quarterly expenses for 2013. The relevant data for the previous three years is as follows: 2010 Quarter 1 23 Return 2011 Expenses Quarter $12,500 1 $11,300 Return 2012 Expenses Quarter $12,900 1 Return Expenses $13,300 2 $12,100 2 $12,300 4 $11,600 $13,700 3 $11,700 3 $12,100 4 $14,000 4 $14,600 The result of a simple regression analysis using all 12 data points yielded the following: Intercept term Coefficient estimate R-squared t-statistic SE Required: $11,855 $126.22 0.44 1.94 975 1. Calculate the quarterly forecast for 2013 using the high-low method and show graphical representation. Also, use simple and multiple regression analysis. For multiple regression, add a dummy variable of seasonality based on a visual representation of the data. Recommend which method Paige should use (Hint: quarters must be numbered sequentially like 1,2,3,4,5,6 ...11,12. 13...without repeating any numbers). 2. How does your analysis in requirement one above change if Lexon manufactures its products in multiple global production facilities to serve the global market?