Forcating MCQ final PDF

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FORECASTING FILL IN THE BLANKS 1. ____________________ is a gradual long term upward or downward movement of demand. Answer: trend 2. A(n) ____________ forecast typically encompass a period of one or two years. Answer: long range 3. A(n)____________ forecast encompasses anywhere from one or two months to a year. Answer: medium range 4. A(n)________________ forecast encompasses the immediate future, is concerned with daily activities of the firm and does not go beyond one or two months in to the future. Answer: short range 5. A(n) ___________is an up-and-down repetitive movement in demand. Answer: cycle 6. A(n)_______________ is an up-and-down repetitive movement within a trend occurring periodically. Answer: seasonal pattern 7. While the moving average method uses equal weights for each observation, __________________ method assigns different weights to each observation to reflect more recent fluctuations in the data and seasonal effects. Answer: weighted moving average 8. In using simple exponential smoothing the _____________  is to one, the greater the reaction of the forecast to the most recent demand. Answer: closer 9. The ______________ the value of the smoothing constant,  , the more sensitive or reactive the forecasts to the change in demand. Answer: higher 10. The closer the value of  is to zero, the___________ will be the dampening or smoothing effect. Answer: greater 11. The major disadvantage of the _________________ method is that it does not react well to variations that occur for a reason such as trends or seasonal effects. Answer: moving averages 12. _________________ forecasting method uses he actual demand from the current period as the forecasted demand for the next period. 1

Answer: naïve, or Last Value method 13. Longer period moving averages react more _______________to recent demand changes than do shorter period moving averages. Answer: slowly

MULTIPLE CHOICES 1. Managers use _______________ in forecasting. a. judgment b. opinion c. past experience Answer: D 2. A traditional forecasting method is a. time series analysis c. all of the above

d. all of the above

b. regression d. none of the above

Answer: C

3. ___________ methods are the most common type of forecasting method for the long-term strategic planning process. a. Regression b. Qualitative c. Time series d. all of the above Answer: B 4. _____________ is a category of statistical techniques that uses historical data to predict future behavior. a. Qualitative methods b. Regression c. Time series d. Quantitative methods Answer: C 5. ____________ use management judgment, expertise, and opinion to make forecasts. a. Qualitative methods b. Regression c. Time series d. Quantitative methods Answer: A 6. _____________ is a procedure for acquiring informed judgments and opinions from knowledgeable individuals using a series of questionnaires to develop a consensus forecast about what will occur in the future. a. Delphi method b. Quantitative method c. Regression d. Time series Answer: A 7. ____________ moving averages react more slowly to recent demand changes than do ____________ moving averages. a. Longer-period / shorter-period b. Shorter-period / longer-period c. Longer-period / longer-period d. Shorter-period / shorter-period Answer: A 8. ___________ is good for stable demand with no pronounced behavioral patterns. a. longer-period moving average b. shorter-period moving average c. moving average d. weighted moving average Answer: C 9. __________ methods assume that what has occurred in the past will continue to occur in the future. a. Time series b. Regression c. Quantitative d. Qualitative Answer: A 2

10. Time series methods relate the forecast to a. past experience b. place and time

c. place

d. time

Answer: D

11. In a weighted moving average, weights are assigned to most __________ data. a. important b. recent c. long-term d. short-term Answer: B 12. In exponential smoothing, the closer alpha is to _________, the greater the reaction to the most recent demand. a. -1 b. 0 c. 1 d. –1 or 1 Answer: C

13. _____________ is the exponential smoothing forecast with an adjustment for a trend added to it. a. Weighted moving average b. Exponential smoothing c. Adjusted exponential smoothing d. Moving average Answer: C 14. In adjusted exponential smoothing, the closer beta is to ____________, the stronger a trend is reflected. a. –1 / 1 b. -1 c. 0 d. 1 Answer: D 15. __________ is the difference between the forecast and actual demand. a. Forecast mistake b. Forecast error c. MAD d. Forecast accuracy Answer: B 16. __________ is the average, absolute difference between the forecast and demand. a. Forecast accuracy b. Forecast error c. MAD d. Forecast mistake Answer: C 17. The lower the value of the ________, relative to the magnitude of the data, the more accurate the forecast. a. forecast accuracy b. forecast mistake c. MAD d. forecast error Answer: C 18. ___________ is absolute error as a percentage of demand. a. Cumulative error b. MAD c. MAFD d. Average error 19. __________ is the sum of the forecast errors. a. Cumulative error b. MAD c. MAFD

Answer: C

d. Average error

Answer: A

20. The method that considers several variables that are related to the variable being predicted is a. Multiple regression b. Moving Average c. Adjusted smoothing , Answer: a

21. The forecasting time horizon that would typically be easiest to predict for would be the 3

a. Long range b. short range c. medium range d. intermediate range, Answer: b 22. Quantitative methods of forecasting include a. jury of executive opinion. B. sales force composite. C. consumer market survey .d. exponential smoothing.* 23. When using exponential smoothing, the smoothing constant a. b. c. d.

is typically between .75 and .95 for most business applications. indicates the accuracy of the previous forecast. can be determined using MAD*. should be chosen to maximize positive bias.

24. If demand is 106 during January, 120 in February, 134 in March, and 142 in April, what is the 3-month simple moving average for May? a. 132* Answer:(106+120+134)/3 b. 126 c. 142 d.138 25. Given last period's forecast of 65, and last period's demand of 62, what is the simple exponential smoothing forecast with an alpha of 0.4 for the next period? a. 62

b. 65

c.63.2

d.63.8*

26. A forecasting technique consistently produces a negative tracking signal. This means that a) the MSE will also consistently be negative. b) the MAPE will also consistently be negative. c) the forecasting technique consistently under predicts. d) the forecast technique consistently over predicts.* 27. Time series patterns that repeat themselves after a period of days or weeks are called a) cycles. b) seasonality.* c) random variation. d) trend. 28. Which of the following is NOT a time-series model? a) exponential smoothing b) naïve approach c) linear regression* d) moving averages 29. Dave’s Bar-B-Q operated a mobile kitchen that serviced construction sites, office buildings, and public parks. Beginning in June, snow cones were added to the menu. The weekly sales figures for the previous year are given below. Assuming a weighting of 3,2,1, determine the three-period weighted moving average forecast for the second week in July. WEEK June 2 3 4 July 2 3 4 5 1 1 SALES 4 6 4 5 10 8 7 9 12 a. 6.3

b.7.3*

c. 8.2

d.5.3

4

30. Dave’s Bar-B-Q operated a mobile kitchen that serviced construction sites, office buildings, and public parks. Beginning in June, snow cones were added to the menu. The weekly sales figures for the previous year are given below. Use exponential smoothing, a smoothing coefficient of 0.3, to forecast demand for the third week of June. WEEK June 1 2 3 4 SALES 4 6 4 5 FORECAST 5.0 4.7 Alpha=0.3 a. 4.0 b. 4.7

c. 5.1*

d.6.4

F t+1 = 0.3 Dt + o.7 Ft = 0.3(6) + .7 (4.7) = 5.09 Given the following information solve the following information complete the following questions Item Number of Actual Absolute Error sum Error Error periods Demand sum squared Total 11 520 49.31 23.41 376.04 31. Mean absolute deviation = 4.85 32. Mean absolute percent deviation = 9% 33. Cumulative error = 23.41 34. Average error = 2.13 35. Mean squared error = 34.19

PROBLEMS Q1: Given the following data on hotel check-ins for a 6-month period: July: 70 rooms, August: 105 rooms, September: 90 rooms, October: 120 rooms, November: 110 rooms, December: 115 rooms. What is the 3-month moving average for January? Answer: 115 = (120+110+115)/3 Q2: Given the following data on the number of pints of ice cream sold at a local ice cream store for a 6-period time frame: Period Demand 1 200 2 245 3 190 4 270 5 280 6 300 Compute a 3-period moving average for period 4. Answer: 211.67 Compute a 3-period moving average for period 5.

Answer: 235

Compute a 3-period moving average for period 7.

Answer: 283.33

Compute a 5-period moving average for period 6.

Answer: 237

5

Q:3 Given the following data on hotel check-ins for a 6-month period: July: 10 rooms, August: 15 rooms, September: 12 rooms, October: 20 rooms, November: 18 rooms, December: 24 rooms With alpha = 0.2, what is the simple exponential smoothing forecast for October? Answer: 11.2

Month

July

August

Septemper October

demand

10 ---

15

12

20

10

11

11.2

Forecast

Q4: The following data summarizes the historical demand for a product Month Actual demand March 20 April 25 May 40 June 35 July 30 August 45 Use exponential smoothing with  = .2 and the smoothed forecast for July is 32 and determine August and September’s smoothed forecasts. Answer: FAugust = 31.6, FSeptember = 34.28 Q5: Recent past demand for product ZXT is given in the following table. Month Actual Demand F T Adjusted February 20 0 0 0 March 22 20 20 April 33 20.4 0 20.4 May 35 22.92 0.756 23.676 June 31 25.336 1.254 26.59 July 48 26.4688 1.21764 27.68644 August 41 30.77504 2.14422 32.91926 Determine the forecasted demand for April and May based on adjusted exponential smoothing with  = .2,  = .3 .

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