25 May Question 81) The following table represents the number o
Question
81) The following table represents the number of applicants at a popular private college in the last four years.
| Month | New members |
| 2007 | 10,067 |
| 2008 | 10,940 |
| 2009 | 11,116 |
| 2010 | 10,999 |
Assuming ? = 0.2, ? = 0.3, an initial forecast of 10,000 for 2007, and an initial trend adjustment of 0 for 2007, use exponential smoothing with trend adjustment to come up with a forecast for 2011 on the number of applicants.
82) Given the following data, if MAD = 1.25, determine what the actual demand must have been in period 2 (A2).
| Time Period | Actual (A) | Forecast (F) |  |
| 1 | 2 | 3 | 1 |
| 2 | A2 = ? | 4 | – |
| 3 | 6 | 5 | 1 |
| 4 | 4 | 6 | 2 |
83) Calculate (a) MAD, (b) MSE, and (c) MAPE for the following forecast versus actual sales figures. (Please round to four decimal places for MAPE.)
| Forecast | Actual |
| 100 | 95 |
| 110 | 108 |
| 120 | 123 |
| 130 | 130 |
84) Use the sales data given below to determine:
| Year | Sales (units) | Year | Sales (units) |
| 1995 | 130 | 1999 | 169 |
| 1996 | 140 | 2000 | 182 |
| 1997 | 152 | 2001 | 194 |
| 1998 | 160 | 2002 | ? |
(a) The least squares trend line.
(b) The predicted value for 2002 sales.
(c) The MAD.
(d) The unadjusted forecasting MSE.
85) For the data below:
| Year | Automobile Sales | Year | Automobile Sales |
| 1990 | 116 | 1977 | 119 |
| 1991 | 105 | 1998 | 34 |
| 1992 | 29 | 1999 | 34 |
| 1993 | 59 | 2000 | 48 |
| 1994 | 108 | 2001 | 53 |
| 1995 | 94 | 2002 | 65 |
| 1996 | 27 | 2003 | 111 |
(a) Determine the least squares regression line.
(b) Determine the predicted value for 2004.
(c) Determine the MAD.
(d) Determine the unadjusted forecasting MSE.
86) Given the following gasoline data:
| Quarter | Year 1 | Year 2 |
| 1 | 150 | 156 |
| 2 | 140 | 148 |
| 3 | 185 | 201 |
| 4 | 160 | 174 |
(a) Compute the seasonal index for each quarter.
(b) Suppose we expect year 3 to have annual demand of 800. What is the forecast value for each quarter in year 3?
87) Given the following data and seasonal index:
(a) Compute the seasonal index using only year 1 data.
(b) Determine the deseasonalized demand values using year 2 data and year 1’s seasonal indices.
(c) Determine the trend line on year 2’s deseasonalized data.
(d) Forecast the sales for the first 3 months of year 3, adjusting for seasonality.
88) Wick’s Ski Shop is looking to forecast ski sales on a quarterly basis based on the historical data listed in the table below:
Use the steps to develop a forecast using the decomposition method to answer the following questions:
(a) Using the CMAs, calculate the seasonal indices for Q1, Q2, Q3, and Q4.
(b) Find the equation for the trend line using deseasonalized data.
(c) Find the year 5 quarterly forecasts.
89) The following table represents the actual vs. forecasted amount of new customers acquired by a major credit card company:
| Month | Actual | Forecast |
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