Forecasts are more accurate for groups of items rather than for individual items.

Multiple Choice Result 100 % 1. Forecasting is not a function which contributes to: a) deciding which business market to pursue b) deciding which product to produce c) deciding how bonuses should be allocated d) deciding how much inventory to carry e) deciding how many people to hire Ans: Section Ref: Introduction Level: easy 2. When evaluating forecasting models it is accurate to say: a) they all rely on the same data sets b) they will provide the same results c) they are usually accurate d) they differ in their degree of complexity e) they do not differ in their degree of complexity Ans: Section Ref: Principles of Forecasting Level: moderate 3. Which of the following is not a feature common to all forecasting models? a) This period’s forecast error is needed to compute next period’s forecast. b) Forecasts are rarely perfect. c) Forecasts are more accurate for groups of items rather than for individual items. d) Forecasts are more accurate for shorter rather than for longer time horizons. e) All of the above features are common to all forecasting models. Ans: Section Ref: Principles of Forecasting Level: moderate 4. The first step in forecasting is: a) determine what data is available b) decide what to forecast c) evaluate and analyze appropriate data d) select and test the forecast model e) establish the forecast accuracy requirements Ans: Section Ref: Steps in the Forecasting Process Level: moderate 5. Which of the following companies helps businesses use weather data to make their business plans? a) i2 technologies b) Manugistics c) Planalytics d) Algorithmics e) SAP Ans: Section Ref: Types of Forecasting Methods Level: hard 6. Qualitative forecasting methods a) are made objectively by the forecaster b) are made subjectively by the forecaster c) are made using existing data sources d) are based on mathematical models e) are only used in parallel with quantitative models Ans: Section Ref: Types of Forecasting Methods Level: moderate 7. Under which forecasting method does a group of managers meet to generate a forecast? a) Market research b) Executive opinion c) Delphi method d) Naïve method e) Gamma method Ans: Section Ref: Types of Forecasting Methods Level: easy 8. Which forecasting method seeks to develop a consensus among a group of experts? a) Market research b) Executive opinion c) Delphi method d) Naïve method e) Gamma method Ans: Section Ref: Types of Forecasting Methods Level: easy 9. One quantitative forecasting models limitation is a) it is objective b) they are consistent c) they are based on mathematical formulas d) they are limited on the quality of available data e) they can work around bad data Ans: Section Ref: Types of Forecasting Methods Level: moderate 10. Which forecasting method is particular good for predicting technological changes and scientific advances? a) Market research b) Executive opinion c) Delphi method d) Naïve method e) Gamma method Ans: Section Ref: Types of Forecasting Methods Level: moderate 11. Which forecasting method is particularly good for determining customer preferences? a) Market research b) Executive opinion c) Delphi method d) Naïve method e) Gamma method Ans: Section Ref: Types of Forecasting Methods Level: moderate 12. Which forecasting method suffers from the possibility of having one person’s opinion dominate the forecast? a) Market research b) Executive opinion c) Delphi method d) Naïve method e) Gamma method Ans: Section Ref: Types of Forecasting Methods Level: moderate 13. Which of the following forecasting methods is most likely to be implemented to change an existing quantitative forecast to account for a new competitor in the marketplace? a) Market research b) Executive opinion c) Delphi method d) Naïve method e) Gamma method Ans: Section Ref: Types of Forecasting Methods Level: moderate 14. Which of the following forecasting methods is specifically designed to go through several rounds of modification before generating a final forecast? a) Exponential smoothing b) Executive opinion c) Delphi method d) Naïve method e) Gamma method Ans: Section Ref: Types of Forecasting Methods Level: moderate 15. What are the two categories of quantitative models? a) Delphi and non-causal b) Causal and non-causal c) Delphi and time series d) Causal and time series e) Causal and Delphi Ans: Section Ref: Types of Forecasting Methods Level: easy 16. A causal research model is based on the assumption that a) the independent variable is related to the dependent variable b) there is a relationship between the time series and the dependent variable c) the variable being forecast is related to other variables in the environment d) there is a relationship between the time series and the independent variable e) the information is contained in a time series of data Ans: Section Ref: Types of Forecasting Methods Level: moderate 17. Which of the following is a causal forecasting method? a) Naïve b) Moving average c) Weighted moving average d) Trend adjusted exponential smoothing e) Linear regression Ans: Section Ref: Types of Forecasting Methods Level: easy 18. Which of the following is the least useful sales forecasting model to use when sales are increasing? a) Trend adjusted exponential smoothing b) Simple mean c) Exponential smoothing d) Weighted moving average e) Naïve Ans: Section Ref: Types of Forecasting Methods Level: hard 19. Over the long term, which of the following forecasting models will likely require carrying the least amount of data? a) Naïve b) Simple mean c) Exponential smoothing d) Weighted moving average e) Moving average Ans: Section Ref: Types of Forecasting Methods Level: moderate 20. In looking at seasonal indexes one weakness to watch for is a) use of the wrong alpha b) incorrect selection of weights c) a clear lack of linear relationship d) seasonality is not present e) significant increase in computational requirements Ans: Section Ref: Types of Forecasting Methods Level: easy 21. Which of the following is not considered to be one of the four basic patterns of time series data? a) Horizontal b) Trend c) Vertical d) Seasonality e) Cycle Ans: Response: See pages 259-260 Level: easy 22. Which is typically the most difficult data pattern to predict? a) Horizontal b) Trend c) Level d) Seasonality e) Cycle Ans: Section Ref: Time Series Models Level: moderate 23. Which forecasting method assumes that next period’s forecast is equal to this period’s actual value? a) Simple mean b) Ignorant c) Basic d) Naïve e) Nescient Ans: Section Ref: Time Series Models Level: easy 24. The OM supervisor informs you, the researcher, that the data has a large standard deviation. What data pattern would you expect to observe once you generated a time series trend? a) horizontal b) seasonal c) positive/negative trend d) cycle e) insufficient information to derive a valid response Ans: Section Ref: Time Series Models Level: moderate 25. Suppose that you are using the naïve forecasting method with trend to forecast sales. If sales have been declining by 20% per week, and this week’s sales amounted to $200, what would your forecast be for next week? a) $200 b) $ 40 c) $240 d. $180 e) $160 Ans: Section Ref: Time Series Models Level: moderate 26. Suppose that you are using the simple mean to make a forecast. This period’s forecast was equal to 100 units, and it was based on 6 periods of demand. This period’s actual demand was 86 units. What is your forecast for next period? a) 98 b) 100 c) 93 d) 86 e) Not enough information is given to answer the question. Ans: Section Ref: Time Series Models Level: hard 27. Suppose that you are using the four-period simple moving average method to forecast sales, and sales have been decreasing by 10% every period. How will your forecasts perform? a) Forecasts will be lower than actual. b) Forecasts will be higher than actual. c) Forecasts will equal actual. d) Forecasts will be increasing. e) Forecasts will be decreasing by 2.5% every period. Ans: Section Ref: Time Series Models Level: hard 28. Suppose that you are using the four-period weighted moving average forecasting method to forecast sales and you know that sales will be increasing every period for the foreseeable future. What of the following would be the best set of weights to use (listed in order from the most recent period to four periods ago, respectively)? a) 0.25, 0.25, 0.25, 0.25 b) 0.40, 0.30, 0.20, 0.10 c) 1.00, 0.00, 0.00, 0.00 d) 0.10, 0.20, 0.30, 0.40 e) 0.00, 0.00, 0.00, 1.00 Ans: Section Ref: Time Series Models Level: hard 29. The following sales figures show actual sales over the identified time period. What can be determined by comparing a simple mean forecast and a six month moving average forecast December 4,000 January 5,000 February 4,000 March 4,500 April 5,500 May 5,000 a) moving average develops a smoother forecast b) 4.7, 5 c) 4.7, 4 d) 4,4 e) 4, 4.7 Ans: Section Ref: Time Series Models Level: moderate 30. What are the most frequently used forecasting techniques? a) Linear regression b) Simple mean c) Exponential smoothing d) Weighted moving average e) Econometric models Ans: Section Ref: Time Series Models Level: moderate 31. In exponential smoothing, what values can the smoothing constant, a, have? a) [-1, 1] b) [1, ¥] c) [0, ¥] d) [0, 1] e) [-¥, ¥] Ans: Section Ref: Time Series Models Level: easy 32. In exponential smoothing, which of the following values for a would generate the most stable forecast? a) 0.10 b) 0.25 c) 0.50 d) 0.75 e) 1.00 Ans: Section Ref: Time Series Models Level: moderate 33. Suppose that you are interested in trend-adjusted exponential smoothing. Which of the following values of the trend smoothing constant, b, would most likely be seen in practice? a) 0.10 b) 0.50 c) 0.75 d) 0.90 e) 1.00 Ans: Section Ref: Time Series Models Level: moderate 34. In linear regression, what are we trying to forecast? a) Beta parameter b) Dependent variable c) Independent variable d) Y-intercept of the line e) Slope of the line Ans: Section Ref: Causal Models Level: moderate 35. What does the linear regression line do? a) Minimizes sum of errors b) Minimizes product of squared errors c) Minimizes sum of squared errors d) Minimizes product of errors e) Minimizes sum of absolute value of errors Ans: Section Ref: CausalCausal Models Level: moderate 36. What value of the correlation coefficient implies that there is a perfect positive linear relationship between the two variables of a linear regression model? a) -1 b) 0 c) 0.5 d) 1 e) ¥ Ans: Section Ref: CausalCausal Models Level: easy 37. In linear regression, an r2 of .984 implies what? a) 98.4% of the variability of the independent variable is explained by the dependent variable b) 98.4% of the variability of the dependent variable is explained by the independent variable c) 1.6% of the variability of the independent variable is explained by the dependent variable d) 1.6% of the variability of the dependent variable is explained by the independent variable e) 99.2% of the variability of the dependent variable is explained by the independent variable Ans: Section Ref: CausalCausal Models Level: moderate 38. What value of the correlation coefficient implies that there is no relationship between the two variables of a linear regression model? a) -1 b) 0 c) 0.5 d) 1 e) ¥ Ans: Section Ref: CausalCausal Models Level: easy 39. What is the statistic that measures the direction and strength of the linear relationship between two variables? a) r2 b) Coefficient of variation c) Variance d) Coefficient of kurtosis e) Correlation coefficient Ans: Section Ref: CausalCausal Models Level: moderate 40. Which of the following is true with respect to the correlation coefficient r? a) r2 £ r b) r2 £ | r | c) r2 ³ r d) r2 ³ | r | e) r2 can never equal r Ans: Section Ref: CausalCausal Models Level: moderate 41. Which of the following values of the correlation coefficient implies that the value of the dependent variable decreases as the value of the independent variable increases? a) -0.2 b) 0 c) 0.2 d) 1 e) 0.5 Ans: Section Ref: CausalCausal Models Level: easy 42. The following correlation coefficient values come from five different linear regression models. Which model “fits” the data the best? a) 0.99 b) 0.5 c) 0 d) -0.8 e) -1 Ans: Section Ref: CausalCausal Models Level: moderate 43. For what is a tracking signal used? a) To identify trends in actual data b) To identify seasonality in actual data c) To identify the effect of business cycles on actual data d) To compute the value of the smoothing constant, a, for exponential smoothing e) To identify forecast bias Ans: Section Ref: Selecting The Right Forecasting Model Level: moderate 44. Suppose that Sally’s company uses exponential smoothing to make forecasts. Further suppose that last period’s demand forecast was for 20,000 units, and last period’s actual demand was 21,000 units. Sally’s company uses a smoothing constant (α) equal to 40%. What should be the forecast for this period? a) 20,000 b) 21,000 c) 20,600 d) 20,400 e) 19,600 Ans: Section Ref: Time Series Models Level: moderate 45. Suppose that Jane’s company uses exponential smoothing to make forecasts. Further suppose that last period’s demand forecast was for 500 units, and last period’s actual demand was 480 units. In addition, yesterday Jane found out that this period’s actual demand will be for 550 units. Jane’s company uses an α value of .20. Today Jane’s boss asked her to prepare a forecast for this period. What should that forecast be? a) 504 b) 496 c) 510 d) 484 e) 550 Ans: Section Ref: Time Series Models Level: hard 46. A firm has the following order history over the last 6 months. January 120 February 95 March 100 April 75 May 100 June 50 What would be a 3-month weighted moving average forecast for July, using weights of 40% for the most recent month, 30% for the month preceding the most recent month, and 30% for the month preceding that one? a) 75 b) 72.5 c) 50 d) 90 e) 106.5 Answer: b Section Ref: Time Series Models Level: moderate 47. What is the mean absolute deviation of the following forecasts? Month Actual Sales Forecast Jan. 614 600 Feb. 480 480 Mar. 500 550 Apr. 500 600 a) 3174 b) 164 c) 41 d) 136 e) -34 Ans: Section Ref: Measuring Forecast Accuracy Level: moderate 48. What is the mean absolute deviation and mean squared error of the following forecast Day Sales Sale Forecast 24 37 31 41 27 46 29 47 25 50 a) 13, 157 b) 14, 321 c) 16, 312 d) 17, 313 e) 18, 321 Ans: Section Ref: Measuring Forecast Accuracy Level: moderate 49. When is exponential smoothing equivalent to the “naïve” approach to forecasting? a) When the smoothing constant is chosen randomly b) α = 0 c) α = 1 d) α = .5 e) When next month’s forecast equals this month’s forecast Ans: Section Ref: Time Series Models Level: hard 50. Consider the demand data listed below. What is the 4-month moving average forecast for June? Month Actual Demand Jan. 10,000 Feb. 12,000 Mar. 24,000 Apr. 8,000 May 14,000 a) 14,000 b) Not enough information is given to answer the question. c) 14,500 d) 13,500 e) 15,333 Ans: Section Ref: Time Series Models Level: moderate 51. Suppose that you want to set up a 3-month weighted moving average forecasting system. You want the weights to be percentages (that add to 100%). Furthermore, you want weights for the most recent two months to be equal but you want each of those weights to be twice as large as the weight for the oldest month. What should the weight be for the oldest month? a) 33% b) 25% c) 80% d) 50% e) 20% Ans: Section Ref: Time Series Models Level: hard 52. Given the following data, use exponential smoothing (α = .2) to develop a demand forecast for period 3. Assume the forecast for the initial period is 5. What is the forecast? Period Demand 1 7 2 9 a) 9.00 b) 3.72 c) 9.48 d) 5.00 e) 6.12 Ans: Section Ref: Time Series Models Level: moderate 53. Which of the following forecasting methods would be best (most accurate) if demand were rapidly decreasing? a) 3-month moving average b) 6-month moving average c) 12-month moving average d) Simple mean e) Exponential smoothing with a = 0.001 Ans: Section Ref: Types of Forecasting Methods Level: hard 54. Suppose that you are using the exponential smoothing forecasting method, and this period’s forecast (Ft) was 100% accurate (i.e., no error). If α = .5, which of the following is definitely true? a) Next period’s forecast will also be 100% accurate. b) Next period’s forecast equals this period’s actual. c) This period’s forecast must be thrown out, and next period’s forecast equals Ft-1 α (At-1 − Ft-1). d) Next period’s forecast equals 50% of this period’s forecast. e) Next period’s forecast equals 50% more than this period’s forecast. Ans: Section Ref: Time Series Models Level: hard 55. A firm has had the following order history over the last 4 months: November 140 December 80 January 100 February 150 What is the weighted moving average forecast for March, assuming a weight of 60% for the most recent month, 30% for the month preceding the most recent month, and 10% for the month preceding that one? a) 117.5 b) 228.1 c) 118.0 d) 128.0 e) 132.4 Ans: Section Ref: Time Series Models Level: moderate 56. What is the mean absolute deviation of the following forecasts? Month Actual Sales Forecast January 68 60 February 48 50 March 50 60 April 30 30 a) -1 b) 5 c) 20 d) 1 e) 42 Ans: Section Ref: Selecting the Right Forecasting Model Level: moderate 57. What is the mean squared error of the following forecasts? Month Actual Sales Forecast Jan. 614 600 Feb. 480 480 Mar. 500 450 Apr. 500 600 a) 3174 b) 164 c) 41 d) 136 e) 12,696 Ans: Section Ref: Selecting the Right Forecasting Model Level: moderate 58. What is the mean squared error of the following forecasts? Month Actual Sales Forecast Jan. 68 60 Feb. 48 50 Mar. 50 60 Apr. 30 30 a) 168 b) 5 c) 20 d) 1 e) 42 Ans: Section Ref: Selecting the Right Forecasting Model Level: moderate 59. Suppose that you are using exponential smoothing with a = 0.5, and your initial forecast 5 months ago was for 100 units. If the actual demand last month was 0 units, which of the following is definitely true? a) The forecast for this month should be 0. b) The model blew up. You can’t use exponential smoothing anymore. c) The forecast for last month was 0. d) The forecast for this month should be 50. e) We need more information to determine this month’s forecast. Ans: Section Ref: Time Series Models Level: hard 60. Suppose that you are using the four-period simple moving average method to forecast sales, and sales have been increasing by 20% every period. How will your forecasts perform? a) Forecasts will be lower than actual. b) Forecasts will be higher than actual. c) Forecasts will equal actual. d) Forecasts will be decreasing. e) Forecasts will be increasing by 5.0% every period. Ans: Section Ref: Time Series Models Level: hard 61. Suppose that you are using the four-period simple moving average method to forecast sales, and sales have been increasing by 40% every period. How will your forecasts perform? a) Forecasts will be increasing by 40.0% every period. b) Forecasts will be higher than actual. c) Forecasts will equal actual. d) Forecasts will be decreasing. e) Forecasts will be increasing by 10.0% every period. Ans: Section Ref: Time Series Models Level: hard 62. Suppose that you are using the naïve forecasting method with trend to forecast sales. If sales have been increasing by 40% per month, and this month’s sales amounted to $1200, what would your forecast be for next month? a) $1200 b) $ 480 c) $1680 d. $ 720 e) $1600 Ans: Section Ref: Time Series Models Level: moderate 63. Suppose that you are using the naïve forecasting method with trend to forecast sales. Sales have been increasing by 10% per week. Two weeks ago, sales amounted to $100. What should your forecast be for this week? a) $100 b) $ 10 c) $110 d. $121 e) $120 Ans: Section Ref: Time Series Models Level: moderate 64. Suppose that you are using the simple mean to make a forecast. This period’s forecast was equal to 200 units, and it was based on 5 periods of demand. This period’s actual demand was 300 units. What is your forecast for next period? a) 217 b) 250 c) 260 d) 300 e) 200 Ans: Section Ref: Time Series Models Level: hard 65. Suppose that you are using the simple mean to make a forecast. This period’s forecast was equal to 1000 units, and it was based on 99 periods of demand. This period’s actual demand was 0 units. What is your forecast for next period? a) 1000 b) 990 c) 0 d) 1010 e) 999 Ans: Section Ref: Time Series Models Level: hard 66. A firm has the following order history over the last 6 months. January 120 February 95 March 100 April 75 May 100 June 50 67. What would be the 4-month simple moving average forecast for July? a) 97.5 b) 325 c) 90 d) 81.25 e) 50 Ans: Section Ref: Time Series Models Level: moderate 68. Given the following data, use exponential smoothing (α = .1) to develop a demand forecast for period 3. Assume the forecast for the initial period is 500. What is the forecast? Period Demand 1 600 2 200 a) 569 b) 470 c) 541 d) 551 e) 479 Ans: Section Ref: Time Series Models Level: moderate 69. Which of the following is the simplest forecasting method? a) Naïve b) Moving average c) Weighted moving average d) Trend adjusted exponential smoothing e) Linear regression Ans: Section Ref: Types of Forecasting Methods Level: easy 70. Which of the following would NOT be a consideration for selecting a forecasting software package? a) How easy is the package to learn b) Is it possible to implement new methods c) Do you require repetitive forecasting d) Does the supplier support a local conference e) Is there any local support Ans: Section Ref: Forecasting Software Level: moderate 71. Combined forecasting involves a rule that a) you must work with different vendors b) you need different forecasters c) you must always use a quantitative and qualitative method d) the results are not comparable to a single forecast e) the forecasting methods should be different Ans: Section Ref: Combining Forecasts Level: easy 72. Which of the following is not typically done jointly by CPFR trading partners? a) set forecasts b) plan production c) replenish inventories d) raise capital e) evaluate their success in the marketplace Ans: Section Ref: Collaborative Planning, Forecasting, and Replenishment (CPFR) Level: hard 73. ___________________________ is a collaborative process between two trading partners that establishes formal guidelines for joint forecasting and planning. a) Collaborative Planning Forecasting and Replenishment (CPFR) b) Supply Chain Planning Forecasting and Replenishment (SCPFR) c) Supply Chain Optimization (SCO) d) Collaborative Creation of Guidelines (CCG) e) Joint Planning and Forecasting (JPP) Ans: Section Ref: Collaborative Planning, Forecasting, and Replenishment (CPFR) Level: moderate 74. “Inside information” is most likely garnered through which of the following forecasting methods? a) exponential smoothing b) seasonal indexes c) naïve d) Delphi e) multiple regression Ans: Section Ref: Types of Forecasting Methods Level: hard