Operations Management Forecasting - Exam 2

26) A time-series trend equation is 25.3 + 2.1x. What is your forecast for period 7? A) 23.2 B) 25.3 C) 27.4 D) 40.0 E) 179.2

D) 40.0

21) Which of the following values of alpha would cause exponential smoothing to respond the SLOWEST to forecast errors? A) 0.10 B) 0.2246 C) 0.50 D) 0.90 E) cannot be determined

A) 0.10

8) The fundamental difference between cycles and seasonality is the: A) duration of the repeating patterns. B) magnitude of the variation. C) ability to attribute the pattern to a cause. D) all of the above E) none of the above

A) duration of the repeating patterns.

13) A six-month moving average forecast is generally better than a three-month moving average forecast if demand: A) is rather stable. B) has been changing due to recent promotional efforts. C) follows a downward trend. D) exceeds one million units per year. E) follows an upward trend.

A) is rather stable.

11) Which time-series model below assumes that demand in the next period will be equal to the most recent period's demand? A) naïve approach B) moving average approach C) weighted moving average approach D) exponential smoothing approach E) trend projection

A) naïve approach

33) If Brandon Edward were working to develop a forecast using a moving averages approach, but he noticed a detectable trend in the historical data, he should: A) use weights to place more emphasis on recent data. B) use weights to minimize the importance of the trend. C) change to an associative multiple regression approach. D) use a simple moving average. E) change to a qualitative approach.

A) use weights to place more emphasis on recent data.

The two general approaches to forecasting are: A) qualitative and quantitative. B) mathematical and statistical. C) judgmental and qualitative. D) historical and associative. E) judgmental and associative.

A. Qualitative and Quantitative

34) What is the forecast for May based on a weighted moving average applied to the following past demand data and using the weights: 4, 3, 2 (largest weight is for most recent data)?

Answer: 2×42+3×47+4×43= 84+141+172 = 397; 397/9=44.1

36) Demand for a certain product is forecast to be 8,000 units per month, averaged over all 12 months of the year. The product follows a seasonal pattern, for which the January monthly index is 1.25. What is the seasonally-adjusted sales forecast for January?

Answer: 8,000 × 1.25 = 10,000

30) A seasonal index for a monthly series is about to be calculated on the basis of three years' accumulation of data. The three previous July values were 110, 150, and 130. The average demand over all months during the three-year time period was 190. What is the approximate seasonal index for July? A) 0.487 B) 0.684 C) 1.462 D) 2.053 E) cannot be calculated with the information given

B) 0.684

12) John's House of Pancakes uses a weighted moving average method to forecast pancake sales. It assigns a weight of 5 to the previous month's demand, 3 to demand two months ago, and 1 to demand three months ago. If sales amounted to 1000 pancakes in May, 2200 pancakes in June, and 3000 pancakes in July, what should be the forecast for August? A) 2400 B) 2511 C) 2067 D) 3767 E) 1622

B) 2511

7) Which of the following is not present in a time series? A) seasonality B) operational variations C) trend D) cycles E) random variations

B) operational variations

1) The three major types of forecasts used by organizations in planning future operations are: A) strategic, tactical, and operational. B) economic, technological, and demand. C) exponential smoothing, Delphi, and regression. D) causal, time-series, and seasonal. E) departmental, organizational, and territorial.

B. Economic, technological, and demand

18) Given an actual demand this period of 103, a forecast value for this period of 99, and an alpha of .4, what is the exponential smoothing forecast for next period? A) 94.6 B) 97.4 C) 100.6 D) 101.6 E) 103.0

C) 100.6

25) Suppose that the last four months of sales were 8, 10, 15, and 9 units, respectively. Suppose further that the last four forecasts were 5, 6, 11, and 12 units, respectively. What is the Mean Absolute Deviation (MAD) of these forecasts? A) 2 B) -10 C) 3.5 D) 9 E) 10.5

C) 3.5

24) Given forecast errors of -1, 4, 8, and -3, what is the mean absolute deviation? A) 2 B) 3 C) 4 D) 8 E) 16

C) 4

20) Given an actual demand this period of 61, a forecast for this period of 58, and an alpha of 0.3, what would the forecast for the next period be using exponential smoothing? A) 45.5 B) 57.1 C) 58.9 D) 61.0 E) 65.5

C) 58.9

32) ________ expresses the error as a percent of the actual values. A) MAD B) MSE C) MAPE D) FIT E) The smoothing constant

C) MAPE

6) Gradual upward or downward movement of data over time is called: A) seasonality. B) a cycle. C) a trend. D) exponential variation. E) random variation.

C) a trend.

27) For a given product demand, the time-series trend equation is 53 - 4x. The negative sign on the slope of the equation: A) is a mathematical impossibility. B) is an indication that the forecast is biased, with forecast values lower than actual values. C) is an indication that product demand is declining. D) implies that the coefficient of determination will also be negative. E) implies that the cumulative error will be negative.

C) is an indication that product demand is declining.

28) Yamaha manufactures which set of products with complementary demands to address seasonal variations? A) golf clubs and skis B) swimming suits and winter jackets C) jet skis and snowmobiles D) pianos and guitars E) ice skates and water skis

C) jet skis and snowmobiles

23) The primary purpose of the mean absolute deviation (MAD) in forecasting is to: A) estimate the trend line. B) eliminate forecast errors. C) measure forecast accuracy. D) seasonally adjust the forecast. E) remove random variations.

C) measure forecast accuracy.

16) Which of the following is NOT a characteristic of exponential smoothing? A) smoothes random variations in the data B) uses an easily altered weighting scheme C) weights each historical value equally D) has minimal data storage requirements E) uses the previous period's forecast

C) weights each historical value equally

The forecasting technique that pools the opinions of a group of experts or managers is known as: A) the expert judgment model. B) multiple regression. C) jury of executive opinion. D) market survey. E) management coefficients.

C. Jury of executive opinion

17) Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast? A) 0 B) 1 divided by the number of periods C) 0.5 D) 1.0 E) cannot be determined

D) 1.0

22) A forecasting method has produced the following over the past five months. What is the mean absolute deviation? A) -0.2 B) -1.0 C) 0.0 D) 1.2 E) 8.6

D) 1.2

29) Demand for a certain product is forecast to be 800 units per month, averaged over all 12 months of the year. The product follows a seasonal pattern, for which the January monthly index is 1.25. What is the seasonally-adjusted sales forecast for January? A) 640 units B) 798.75 units C) 801.25 units D) 1000 units E) 83.33 units

D) 1000 units

10) What is the forecast for May using a four-month moving average? A) 38 B) 42 C) 43 D) 44 E) 47

D) 44

14) Which of the following statements comparing exponential smoothing to the weighted moving average technique is TRUE? A) Exponential smoothing is more easily used in combination with the Delphi method. B) More emphasis can be placed on recent values using the weighted moving average. C) Exponential smoothing is considerably more difficult to implement on a computer. D) Exponential smoothing typically requires less record keeping of past data. E) Exponential smoothing allows one to develop forecasts for multiple periods, whereas the weighted moving average technique does not.

D) Exponential smoothing typically requires less record keeping of past data.

38) The degree or strength of a relationship between two variables is shown by the: A) alpha. B) mean. C) mean absolute deviation. D) coefficient of correlation. E) cumulative error.

D) coefficient of correlation.

15) Which time-series model uses BOTH past forecasts and past demand data to generate a new forecast? A) naïve B) moving average C) weighted moving average D) exponential smoothing E) trend projection

D) exponential smoothing

9) In time series, which of the following cannot be predicted? A) large increases in demand B) cycles C) seasonal fluctuations D) random variations E) large decreases in demand

D) random variations

31) Suppose that the demand in period 1 was 7 units and the demand in period 2 was 9 units. Assume that the forecast for period 1 was for 5 units. If the firm uses exponential smoothing with an alpha value of .20, what should be the forecast for period 3? (Round answers to two decimal places.) A) 9.00 B) 3.72 C) 9.48 D) 5.00 E) 6.12

E) 6.12

5) Time-series data may exhibit which of the following behaviors? A) trend B) random variations C) seasonality D) cycles E) They may exhibit all of the above.

E) They may exhibit all of the above.

19) A forecast based on the previous forecast plus a percentage of the forecast error is a(n): A) qualitative forecast. B) naive forecast. C) moving average forecast. D) weighted moving average forecast. E) exponential smoothing forecast.

E) exponential smoothing

4) Which of the following is not a type of qualitative forecasting? A) jury of executive opinion B) sales force composite C) market survey D) Delphi method E) moving average

E) moving average