Chapter 4 SCMA 331
One advantage of exponential smoothing is the limited amount of record keeping involved.
True
__________ expresses the error as a percent of the actual values, undistorted by a single large value. A) MAD B) MSE C) MAPE D) FIT E) The smoothing constant
C
__________ forecasting tries a variety of computer models and selects the best one for a particular application.
Focus
If a forecast is consistently greater than (or less than) actual values, the forecast is said to be biased.
True
In trend projection, the trend component is the slope of the regression equation.
True
Linear-regression analysis is a straight-line mathematical model to describe the functional relationships between independent and dependent variables.
True
Many service firms use point-of-sale computers to collect detailed records needed for accurate short-term forecasts.
True
Most forecasting techniques assume that there is some underlying stability in the system.
True
A naïve forecast for September sales of a product would be equal to the forecast for August.
False
Demand cycles for individual products can be driven by product life cycles.
True
Focus forecasting tries a variety of computer models and selects the best one for a particular application.
True
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
Forecasts are usually classified by time horizon into three categories A) short-range, medium-range, and long-range B) finance/accounting, marketing, and operations C) strategic, tactical, and operational D) exponential smoothing, regression, and time series E) departmental, organizational, and industrial
A
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 a naïve approach D) use a simple moving average E) change to a qualitative approach
A
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
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
What two numbers are contained in the daily report to the CEO of Walt Disney Parks & Resorts regarding the six Orlando parks? A) yesterday's forecasted attendance and yesterday's actual attendance B) yesterday's actual attendance and today's forecasted attendance C) yesterday's forecasted attendance and today's forecasted attendance D) yesterday's actual attendance and last year's actual attendance E) yesterday's forecasted attendance and the year-to-date average daily forecast error
A
Which of the following techniques uses variables such as price and promotional expenditures, which are related to product demand, to predict demand? A) associative models B) exponential smoothing C) weighted moving average D) simple moving average E) time series
A
Which of the following values of alpha would cause exponential smoothing to respond the most slowly to forecast errors? A) 0.10 B) 0.20 C) 0.40 D) 0.80 E) cannot be determined
A
Which time-series model below assumes that demand in the next period will be equal to the most recent period's demand? A) naive approach B) moving average approach C) weighted moving average approach D) exponential smoothing approach E) none of the above
A
An approach to exponential smoothing in which the smoothing constant is automatically changed to keep errors to a minimum is called __________.
Adaptive smoothing
A skeptical manager asks what long-range forecasts can be used for. Give her three possible uses/purposes.
Any three of: planning new products, capital expenditures, facility location or expansion, research and development.
A skeptical manager asks what short-range forecasts can be used for. Give her three possible uses/purposes.
Any three of: planning purchasing, job scheduling, work force levels, job assignments, production levels.
Linear regression is known as a(n) __________ because it incorporates variables or factors that might influence the quantity being forecast.
Associative model
A forecast with a time horizon of about 3 months to 3 years is typically called a A) long-range forecast B) medium-range forecast C) short-range forecast D) weather forecast E) strategic forecast
B
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 over all months is 190. The approximate seasonal index for July is A) 0.487 B) 0.684 C) 1.462 D) 2.053 E) cannot be calculated with the information given
B
Computer monitoring of tracking signals and self-adjustment if a signal passes a preset limit is characteristic of A) exponential smoothing including trend B) adaptive smoothing C) trend projection D) focus forecasting E) multiple regression analysis
B
Forecasts A) become more accurate with longer time horizons B) are rarely perfect C) are more accurate for individual items than for groups of items D) all of the above E) none of the above
B
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
Organizations use which three major types of forecasts, including two that may fall outside the role of the operations manager? 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
Which of the following is not present in a time series? A) seasonality B) operational variations C) trend D) cycles E) random variations
B
Yamaha manufactures which set of products with complementary demands to address seasonal fluctuations? 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
A fundamental distinction between trend projection and linear regression is that A) trend projection uses least squares while linear regression does not B) only linear regression can have a negative slope C) in trend projection the independent variable is time; in linear regression the independent variable need not be time, but can be any variable with explanatory power D) trend projection can be a function of several variables, while linear regression can only be a function of one variable E) trend projection uses two smoothing constants, not just one
C
For a given product demand, the time series trend equation is 53 - 4 X. 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
Forecasts used for new product planning, capital expenditures, facility location or expansion, and R&D typically utilize a A) short-range time horizon B) medium-range time horizon C) long-range time horizon D) naive method, because there is no data history E) all of the above
C
Given an actual demand of 103, a previous forecast value of 99, and an alpha of .4, the exponential smoothing forecast for the next period would be A) 94.6 B) 97.4 C) 100.6 D) 101.6 E) 103.0
C
Given an actual demand of 61, a previous forecast of 58, and an alpha of .3, what would the forecast for the next period be using simple exponential smoothing? A) 45.5 B) 57.1 C) 58.9 D) 61.0 E) 65.5
C
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
Gradual movement in time-series data over time is called A) seasonal variation B) a cycle C) a trend D) exponential variation E) random variation
C
The forecasting model that pools the opinions of a group of experts or managers is known as the A) expert judgment model B) multiple regression model C) jury of executive opinion model D) consumer market survey model E) management coefficients model
C
The last four months of sales were 8, 10, 15, and 9 units. The last four forecasts were 5, 6, 11, and 12 units. The Mean Absolute Deviation (MAD) is A) 2 B) -10 C) 3.5 D) 9 E) 10.5
C
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) all of the above
C
Which is not a characteristic of exponential smoothing? A) smoothes random variations in the data B) easily altered weighting scheme C) weights each historical value equally D) has minimal data storage requirements E) None of the above; they are all characteristics of exponential smoothing.
C
Which of the following statements about time-series forecasting is true? A) It is based on the assumption that future demand will be the same as past demand. B) It makes extensive use of the data collected in the qualitative approach. C) It is based on the assumption that the analysis of past demand helps predict future demand. D) Because it accounts for trends, cycles, and seasonal patterns, it is always more powerful than associative forecasting. E) All of the above are true.
C
Which of the following uses three types of participants: decision makers, staff personnel, and respondents? A) executive opinions B) sales force composites C) the Delphi method D) associative models E) time series analysis
C
The smoothing constant is a weighting factor used in __________.
Exponential smoothing
A forecasting method has produced the following over the past five months. What is the mean absolute deviation? Actual; Forecast; Error; |Error| 10; 11; -1; 1 8; 10; -2; 2 10; 8; 2; 2 6; 6; 0; 0 9; 8; 1; 1 A) -0.2 B) -1.0 C) 0.0 D) 1.2 E) 8.6
D
A time series trend equation is 25.3 + 2.1 X. What is your forecast for period 7? A) 23.2 B) 25.3 C) 27.4 D) 40.0 E) cannot be determined
D
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) 88.33 units
D
If two variables were perfectly correlated, the correlation coefficient r would equal A) 0 B) -1 C) 1 D) B or C E) none of the above
D
In time series, which of the following cannot be predicted? A) large increases in demand B) cycles C) seasonal fluctuations D) random fluctuations E) large decreases in demand
D
Increasing the number of periods in a moving average will accomplish greater smoothing, but at the expense of A) manager understanding B) accuracy C) stability D) responsiveness to changes E) All of the above are diminished when the number of periods increases.
D
The degree or strength of a relationship between two variables is shown by the A) alpha B) mean C) mean absolute deviation D) correlation coefficient E) cumulative error
D
The last four weekly values of sales were 80, 100, 105, and 90 units. The last four forecasts were 60, 80, 95, and 75 units. These forecasts illustrate A) qualitative methods B) adaptive smoothing C) slope D) bias E) trend projection
D
The tracking signal is the A) standard error of the estimate B) absolute deviation of the last period's forecast C) mean absolute deviation (MAD) D) ratio of cumulative error/MAD E) mean absolute percentage error (MAPE)
D
What is the approximate forecast for May using a four-month moving average? Nov.; 39 Dec.; 36 Jan.; 40 Feb.; 42 Mar.; 48 April; 46 A) 38 B) 42 C) 43 D) 44 E) 47
D
Which of the following most requires long-range forecasting (as opposed to short-range or medium-range forecasting) for its planning purposes? A) job scheduling B) production levels C) cash budgeting D) capital expenditures E) purchasing
D
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
Which of the following statements comparing the weighted moving average technique and exponential smoothing 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 weighted moving averages does not.
D
Which time-series model uses past forecasts and past demand data to generate a new forecast? A) naive B) moving average C) weighted moving average D) exponential smoothing E) regression analysis
D
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) exponentially smoothed forecast
E
Many services maintain records of sales noting A) the day of the week B) unusual events C) weather D) holidays E) all of the above
E
One use of short-range forecasts is to determine A) planning for new products B) capital expenditures C) research and development plans D) facility location E) job assignments
E
Suppose that 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
Taco Bell's unique employee scheduling practices are partly the result of using A) point-of-sale computers to track food sales in 15 minute intervals B) focus forecasting C) a six-week moving average forecasting technique D) multiple regression E) A and C are both correct.
E
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
Which of the following is not a type of qualitative forecasting? A) executive opinions B) sales force composites C) consumer surveys D) the Delphi method E) moving average
E
Which of the following is true regarding the two smoothing constants of the Forecast Including Trend (FIT) model? A) One constant is positive, while the other is negative. B) They are called MAD and cumulative error. C) Alpha is always smaller than beta. D) One constant smoothes the regression intercept, whereas the other smoothes the regression slope. E) Their values are determined independently.
E
__________ forecasts address the business cycle by predicting inflation rates, money supplies, housing starts, and other planning indicators.
Economic
Forecasts of individual products tend to be more accurate than forecasts of product families.
False
In a regression equation where Y is demand and X is advertising, a coefficient of determination (R2) of .70 means that 70% of the variance in advertising is explained by demand.
False
In trend projection, a negative regression slope is mathematically impossible.
False
Mean Squared Error and Coefficient of Correlation are two measures of the overall error of a forecasting model.
False
Patterns in the data that occur every several years are called circuits.
False
Regression lines graphically depict "cause-and-effect" relationships.
False
Technological forecasts address the business cycle by predicting inflation rates, money supplies, housing starts, and other planning indicators.
False
The larger the number of periods in the simple moving average forecasting method, the greater the method's responsiveness to changes in demand.
False
The larger the standard error of the estimate, the more accurate the forecasting model.
False
__________ is a measure of overall forecast error for a model.
MAD or Mean Absolute Deviation
__________ are useful if we can assume that market demands will stay fairly steady over time.
Moving averages
__________ forecasts employ one or more mathematical models that rely on historical data and/or associative variables to forecast demand.
Quantitative
Demand forecasts, also called __________ forecasts, are projections of demand for a company's products or services.
Sales
__________ is a forecasting technique based upon salespersons' estimates of expected sales.
Sales force composite
__________ forecasts are concerned with rates of technological progress, which can result in the birth of exciting new products, requiring new plants and equipment.
Technological
__________ forecasts use a series of past data points to make a forecast.
Time-series
__________ is a time-series forecasting method that fits a trend line to a series of historical data points and then projects the line into the future for forecasts.
Trend projection
A naive forecast for September sales of a product would be equal to the sales in August.
True
A time-series model uses a series of past data points to make the forecast.
True
A trend projection equation with a slope of 0.78 means that there is a 0.78 unit rise in Y for every unit of time that passes.
True
Cycles and random variations are both components of time series.
True
Demand (sales) forecasts serve as inputs to financial, marketing, and personnel planning.
True
Seasonal indices adjust raw data for patterns that repeat at regular time intervals.
True
The forecasting time horizon and the forecasting techniques used tend to vary over the life cycle of a product.
True
The quarterly "make meeting" of Lexus dealers is an example of a sales force composite forecast.
True
The sales force composite forecasting method relies on salespersons' estimates of expected sales.
True
The __________ measures the strength of the relationship between two variables.
coefficient of correlation
When one constant is used to smooth the forecast average and a second constant is used to smooth the trend, the forecasting method is __________.
exponential smoothing with trend adjustment or trend-adjusted smoothing or second-order smoothing or double smoothing
A measure of forecast error that does not depend on the magnitude of the item being forecast is the __________.
mean absolute percent error or MAPE
A(n) __________ forecast uses an average of the most recent periods of data to forecast the next period.
moving average
If a barbershop operator noted that Tuesday's business was typically twice as heavy as Wednesday's, and that Friday's business was typically the busiest of the week, business at the barbershop is subject to __________.
seasonal variations