41) A medium-term forecast is considered to cover what length of time? A) 2-4 weeks B) 1 month to 1 year C) 2-4 years D) 5-10 years E) 20 years 42) When is the exponential smoothing model equivalent to the naïve forecasting model? A) ? = 0 B) ? = 0.5 C) ? = 1 D) during the first period in which it is used E) never 43) Enrollment in a particular class for the last four semesters has been 120, 126, 110, and 130. Suppose a one-semester moving average was used to forecast enrollment (this is sometimes referred to as a naïve forecast). Thus, the forecast for the second semester would be 120, for the third semester it would be 126, and for the last semester it would be 110. What would the MSE be for this situation? A) 196.00 B) 230.67 C) 100.00 D) 42.00 E) None of the above 44) Which of the following methods tells whether the forecast tends to be too high or too low? A) MAD B) MSE C) MAPE D) decomposition E) bias 45) Assume that you have tried three different forecasting models. For the first, the MAD = 2.5, for the second, the MSE = 10.5, and for the third, the MAPE = 2.7. We can then say: A) the third method is the best. B) the second method is the best. C) methods one and three are preferable to method two. D) method two is least preferred. E) None of the above 46) Which of the following methods gives an indication of the percentage of forecast error? A) MAD B) MSE C) MAPE D) decomposition E) bias 47) Daily demand for newspapers for the last 10 days has been as follows: 12, 13, 16, 15, 12, 18, 14, 12, 13, 15 (listed from oldest to most recent). Forecast sales for the next day using a two-day moving average. A) 14 B) 13 C) 15 D) 28 E) 12.5 48) As one increases the number of periods used in the calculation of a moving average, A) greater emphasis is placed on more recent data. B) less emphasis is placed on more recent data. C) the emphasis placed on more recent data remains the same. D) it requires a computer to automate the calculations. E) one is usually looking for a long-term prediction. 49) Enrollment in a particular class for the last four semesters has been 122, 128, 100, and 155 (listed from oldest to most recent). The best forecast of enrollment next semester, based on a three-semester moving average, would be A) 116.7. B) 126.3. C) 168.3. D) 135.0. E) 127.7. 50) Which of the following methods produces a particularly stiff penalty in periods with large forecast errors? A) MAD B) MSE C) MAPE D) decomposition E) bias 51) The process of isolating linear trend and seasonal factors to develop more accurate forecasts is called A) regression. B) decomposition. C) smoothing. D) monitoring. E) None of the above 52) Sales for boxes of Girl Scout cookies over a 4-month period were forecasted as follows: 100, 120, 115, and 123. The actual results over the 4-month period were as follows: 110, 114, 119, 115. What was the MAD of the 4-month forecast? A) 0 B) 5 C) 7 D) 108 E) None of the above 53) Sales for boxes of Girl Scout cookies over a 4-month period were forecasted as follows: 100, 120, 115, and 123. The actual results over the 4-month period were as follows: 110, 114, 119, 115. What was the MSE of the 4-month forecast? A) 0 B) 5 C) 7 D) 108 E) None of the above 54) Daily demand for newspapers for the last 10 days has been as follows: 12, 13, 16, 15, 12, 18, 14, 12, 13, 15 (listed from oldest to most recent). Forecast sales for the next day using a three-day weighted moving average where the weights are 3, 1, and 1 (the highest weight is for the most recent number). A) 12.8 B) 13.0 C) 70.0 D) 14.0 E) None of the above 55) Daily demand for newspapers for the last 10 days has been as follows: 12, 13, 16, 15, 12, 18, 14, 12, 13, 15 (listed from oldest to most recent). Forecast sales for the next day using a two-day weighted moving average where the weights are 3 and 1. A) 14.5 B) 13.5 C) 14 D) 12.25 E) 12.75 56) Which of the following is not considered to be one of the components of a time series? A) trend B) seasonality C) variance D) cycles E) random variations 57) Which of the following statements about the decomposition method is/are false? A) The process of “deseasonalizing” involves multiplying by a seasonal index. B) Dummy variables are used in a regression model as part of an additive approach to seasonality. C) Computing seasonal indices is the first step of the decomposition method. D) Data is “deseasonalized” after the trend line is found. E) Decomposition can involve additive or multiplicative methods with respect to seasonality. 58) Enrollment in a particular class for the last four semesters has been 120, 126, 110, and 130 (listed from oldest to most recent). Develop a forecast of enrollment next semester using exponential smoothing with an alpha = 0.2. Assume that an initial forecast for the first semester was 120 (so the forecast and the actual were the same). A) 118.96 B) 121.17 C) 130 D) 120 E) None of the above 59) Demand for soccer balls at a new sporting goods store is forecasted using the following regression equation: Y = 98 + 2.2X where X is the number of months that the store has been in existence. Let April be represented by X = 4. April is assumed to have a seasonality index of 1.15. What is the forecast for soccer ball demand for the month of April (rounded to the nearest integer)? A) 123 B) 107 C) 100 D) 115 E) None of the above 60) A TIME SERIES forecasting model in which the forecast for the next period is the actual value for the current period is the A) Delphi model. B) Holt’s model. C) naïve model. D) exponential smoothing model. E) weighted moving average. 61) In picking the smoothing constant for an exponential smoothing model, we should look for a value that A) produces a nice-looking curve. B) equals the utility level that matches with our degree of risk aversion. C) produces values which compare well with actual values based on a standard measure of error. D) causes the least computational effort. E) None of the above 62) Which of the following is not considered one of the steps to developing the decomposition method? A) compute seasonal indices using CMAs B) deseasonalize the data by dividing each number by its seasonal index C) find the equation of the trend line using the deseasonlized data D) forecast for future periods using the trend line E) add the seasonal index to the trend forecast 63) A method to measure how well predictions fit actual data is A) decomposition B) smoothing C) tracking signal D) regression E) moving average 64) If the Q1 demand for a particular year is 200 and the seasonal index is 0.85, what is the deseasonalized demand value for Q1? A) 170 B) 185 C) 215 D) 235.29 E) 250 65) In the exponential smoothing with trend adjustment forecasting method, ? is the A) slope of the trend line. B) new forecast. C) Y-axis intercept. D) independent variable. E) trend smoothing constant. 66) Using the additive decomposition model, what would be the period 2, Q3 forecast using the following equation:.jpg”> = 20 + 3.2X1+ 1.5X2 + 0.8X3 + 0.6X4? A) 23.2 B) 25 C) 27 D) 27.2 E) 27.9 67) The computer monitoring of tracking signals and self-adjustment is referred to as A) exponential smoothing. B) adaptive smoothing. C) trend projections. D) trend smoothing. E) running sum of forecast errors (RFSE). 68) Which of the following is not a characteristic of trend projections? A) The variable being predicted is the Y variable. B) Time is the X variable. C) It is useful for predicting the value of one variable based on time trend. D) A negative intercept term always implies that the dependent variable is decreasing over time. E) They are often developed using linear regression. 69) A tracking signal was calculated for a particular set of demand forecasts. This tracking signal was positive. This would indicate that A) demand is greater than the forecast. B) demand is less than the forecast. C) demand is equal to the forecast. D) the MAD is negative. E) None of the above 70) A seasonal index of ________ indicates that the season is average. A) 10 B) 100 C) 0.5 D) 0 E) 1 71) The errors in a particular forecast are as follows: 4, -3, 2, 5, -1. What is the tracking signal of the forecast? A) 0.4286 B) 2.3333 C) 5 D) 1.4 E) 2.5 72) Demand for a particular type of battery fluctuates from one week to the next. A study of the last six weeks provides the following demands (in dozens): 4, 5, 3, 2, 8, 10 (last week). (a) Forecast demand for the next week using a two-week moving average. (b) Forecast demand for the next week using a three-week moving average. 73) Daily high temperatures in the city of Houston for the last week have been: 93, 94, 93, 95, 92, 86, 98 (yesterday). (a) Forecast the high temperature today using a three-day moving average. (b) Forecast the high temperature today using a two-day moving average. (c) Calculate the mean absolute deviation based on a two-day moving average, covering all days in which you can have a forecast and an actual temperature. 74) For the data below: Month Automobile Battery Sales Month Automobile Battery Sales January 20 July 17 February 21 August 18 March 15 September 20 April 14 October 20 May 13 November 21 June 16 December 23 (a) Develop a scatter diagram. (b) Develop a three-month moving average. (c) Compute MAD. 75) For the data below: Month Automobile Tire Sales Month Automobile Tire Sales January 80 July 68 February 84 August 100 March 60 September 80 April 56 October 80 May 52 November 84 June 64 December 92 (a) Develop a scatter diagram. (b) Compute a three-month moving average. (c) Compute the MSE. 76) For the data below: Year Automobile Sales Year Automobile Sales 1990 116 1997 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) Develop a scatter diagram. (b) Develop a six-year moving average forecast. (c) Find MAPE. 77) Use simple exponential smoothing with ? = 0.3 to forecast battery sales for February through May. Assume that the forecast for January was for 22 batteries. Month Automobile Battery Sales January 42 February 33 March 28 April 59 78) Average starting salaries for students using a placement service at a university have been steadily increasing. A study of the last four graduating classes indicates the following average salaries: $30,000, $32,000, $34,500, and $36,000 (last graduating class). Predict the starting salary for the next graduating class using a simple exponential smoothing model with ? = 0.25. Assume that the initial forecast was $30,000 (so that the forecast and the actual were the same). 79) Use simple exponential smoothing with ? = 0.33 to forecast the tire sales for February through May. Assume that the forecast for January was for 22 sets of tires. Month Automobile Battery Sales January 28 February 21 March 39 April 34 80) The following table represents the new members that have been acquired by a fitness center. Month New members Jan 45 Feb 60 March 57 April 65 Assuming ? = 0.3, ? = 0.4, an initial forecast of 40 for January, and an initial trend adjustment of 0 for January, use exponential smoothing with trend adjustment to come up with a