Accounting
Anthropology
Archaeology
Art History
Banking
Biology & Life Science
Business
Business Communication
Business Development
Business Ethics
Business Law
Chemistry
Communication
Computer Science
Counseling
Criminal Law
Curriculum & Instruction
Design
Earth Science
Economic
Education
Engineering
Finance
History & Theory
Humanities
Human Resource
International Business
Investments & Securities
Journalism
Law
Management
Marketing
Medicine
Medicine & Health Science
Nursing
Philosophy
Physic
Psychology
Real Estate
Science
Social Science
Sociology
Special Education
Speech
Visual Arts
Educational Philosophy
Q:
One of the main advantages of standardization is that it increases the potential variety of products.
Q:
Concurrent engineering is another term for sequential development.
Q:
A house of quality is achieved when no department in a single location has more than 15 percent rejects.
Q:
Global teams provide diversity while eliminating conflicts and miscommunication.
Q:
The president of State University wants to forecast student enrollments for this academic year based on the following historical data: What is the forecast for this year using trend-adjusted (double) smoothing with alpha = .05 and beta = .3, if the forecast for last year was 21,000, the forecast for two years ago was 19,000, and the trend estimate for last year's forecast was 1,500? A. 18,750 B. 19,500 C. 21,000 D. 22,650 E. 22,800
Q:
Given forecast errors of -5, -10, and +15, the MAD is: A. 0. B. 10. C. 30. D. 175. E. 225.
Q:
Given the following historical data and weights of .5, .3, and .2, what is the three-period moving average forecast for period 5? A. 144.20 B. 144.80 C. 144.67 D. 143.00 E. 144.00
Q:
Given the following historical data, what is the simple three-period moving average forecast for period 6? A. 67 B. 115 C. 69 D. 68 E. 68.67
Q:
Customer service levels can be improved by better:
A. mission statements.
B. control charting.
C. short-term forecast accuracy.
D. exponential smoothing.
E. customer selection.
Q:
A managerial approach toward forecasting which seeks to actively influence demand is:
A. reactive.
B. proactive.
C. influential.
D. protracted.
E. retroactive.
Q:
Forecasting techniques generally assume:
A. the absence of randomness.
B. continuity of some underlying causal system.
C. a linear relationship between time and demand.
D. accuracy that increases the farther out in time the forecast projects.
E. accuracy that is better when individual items, rather than groups of items, are being considered.
Q:
Which of the following is not necessarily an element of a good forecast?
A. estimate of accuracy
B. timeliness
C. meaningful units
D. low cost
E. written
Q:
The degree of management involvement in short-range forecasts is:
A. none.
B. low.
C. moderate.
D. high.
E. total.
Q:
The two most important factors in choosing a forecasting technique are:
A. cost and time horizon.
B. accuracy and time horizon.
C. cost and accuracy.
D. quantity and quality.
E. objective and subjective components.
Q:
Which of the following is used for constructing a control chart?
A. mean absolute deviation
B. mean squared error
C. tracking signal
D. bias
Q:
Given forecast errors of 5, 0, -4, and 3, what is the bias?
A. -4
B. 4
C. 5
D. 12
E. 6
Q:
Given forecast errors of 5, 0, -4, and 3, what is the mean absolute deviation?
A. 4
B. 3
C. 2.5
D. 2
E. 1
Q:
Given forecast errors of 4, 8, and -3, what is the mean absolute deviation?
A. 4
B. 3
C. 5
D. 6
E. 12
Q:
The mean absolute deviation is used to:
A. estimate the trend line.
B. eliminate forecast errors.
C. measure forecast accuracy.
D. seasonally adjust the forecast.
E. compute periodic forecast errors.
Q:
Which of the following corresponds to the predictor variable in simple linear regression?
A. regression coefficient
B. dependent variable
C. independent variable
D. predicted variable
E. demand coefficient
Q:
Which term most closely relates to associative forecasting techniques?
A. time series data
B. expert opinions
C. Delphi technique
D. consumer survey
E. predictor variables
Q:
The primary method for associative forecasting is:
A. sensitivity analysis.
B. regression analysis.
C. simple moving averages.
D. centered moving averages.
E. exponential smoothing.
Q:
Which of the following might be used to indicate the cyclical component of a forecast?
A. leading variable
B. mean squared error
C. Delphi technique
D. exponential smoothing
E. mean absolute deviation
Q:
A persistent tendency for forecasts to be greater than or less than the actual values is called:
A. bias.
B. tracking.
C. control charting.
D. positive correlation.
E. linear regression.
Q:
Which technique is used in computing seasonal relatives?
A. double smoothing
B. Delphi
C. mean squared error
D. centered moving average
E. exponential smoothing
Q:
In the additive model for seasonality, seasonality is expressed as a ______________ adjustment to the average; in the multiplicative model, seasonality is expressed as a __________ adjustment to the average.
A. quantity; percentage
B. percentage; quantity
C. quantity; quantity
D. percentage; percentage
E. qualitative; quantitative
Q:
In trend-adjusted exponential smoothing, the trend-adjusted forecast consists of:
A. an exponentially smoothed forecast and a smoothed trend factor.
B. an exponentially smoothed forecast and an estimated trend value.
C. the old forecast adjusted by a trend factor.
D. the old forecast and a smoothed trend factor.
E. a moving average and a trend factor.
Q:
A manager uses the following equation to predict monthly receipts: Yt = 40,000 + 150t. What is the forecast for July if t = 0 in April of this year? A. 40,450 B. 40,600 C. 42,100 D. 42,250 E. 42,400
Q:
Given an actual demand of 105, a forecasted value of 97, and an alpha of .4, the simple exponential smoothing forecast for the next period would be:
A. 80.8.
B. 93.8.
C. 100.2.
D. 101.8.
E. 108.2.
Q:
Given an actual demand of 59, a previous forecast of 64, and an alpha of .3, what would the forecast for the next period be using simple exponential smoothing?
A. 36.9
B. 57.5
C. 60.5
D. 62.5
E. 65.5
Q:
Simple exponential smoothing is being used to forecast demand. The previous forecast of 66 turned out to be four units less than actual demand. The next forecast is 66.6, implying a smoothing constant, alpha, equal to:
A. .01.
B. .10.
C. .15.
D. .20.
E. .60.
Q:
Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast?
A. 0
B. .01
C. .1
D. .5
E. 1.0
Q:
Which is not a characteristic of exponential smoothing?
A. smoothes random variations in the data
B. weights each historical value equally
C. has an easily altered weighting scheme
D. has minimal data storage requirements
E. smoothes real variations in the data
Q:
A forecast based on the previous forecast plus a percentage of the forecast error is:
A. a naive forecast.
B. a simple moving average forecast.
C. a centered moving average forecast.
D. an exponentially smoothed forecast.
E. an associative forecast.
Q:
In order to increase the responsiveness of a forecast made using the moving average technique, the number of data points in the average should be:
A. decreased.
B. increased.
C. multiplied by a larger alpha.
D. multiplied by a smaller alpha.
E. eliminated if the MAD is greater than the MSE.
Q:
Which is not a characteristic of simple moving averages applied to time series data?
A. smoothes random variations in the data
B. weights each historical value equally
C. lags changes in the data
D. requires only last period's forecast and actual data
E. smoothes real variations in the data
Q:
Moving average forecasting techniques do the following:
A. Immediately reflect changing patterns in the data.
B. Lead changes in the data.
C. Smooth variations in the data.
D. Operate independently of recent data.
E. Assist when organizations are relocating.
Q:
For the data given below, what would the naive forecast be for period 5? A. 58 B. 62 C. 59.5 D. 61 E. cannot tell from the data given
Q:
Using the latest observation in a sequence of data to forecast the next period is:
A. a moving average forecast.
B. a naive forecast.
C. an exponentially smoothed forecast.
D. an associative forecast.
E. regression analysis.
Q:
Putting forecast errors into perspective is best done using
A. exponential smoothing.
B. MAPE.
C. linear decision rules.
D. MAD.
E. hindsight.
Q:
Averaging techniques are useful for:
A. distinguishing between random and nonrandom variations.
B. smoothing out fluctuations in time series.
C. eliminating historical data.
D. providing accuracy in forecasts.
E. average people.
Q:
The primary difference between seasonality and cycles is:
A. the duration of the repeating patterns.
B. the magnitude of the variation.
C. the ability to attribute the pattern to a cause.
D. the direction of the movement.
E. there are only four seasons but 30 cycles.
Q:
Gradual, long-term movement in time series data is called:
A. seasonal variation.
B. cycles.
C. irregular variation.
D. trend.
E. random variation.
Q:
Detecting nonrandomness in errors can be done using:
A. MSEs.
B. MAPs.
C. control charts.
D. correlation coefficients.
E. strategies.
Q:
One reason for using the Delphi method in forecasting is to:
A. avoid premature consensus (bandwagon effect).
B. achieve a high degree of accuracy.
C. maintain accountability and responsibility.
D. be able to replicate results.
E. prevent hurt feelings.
Q:
The forecasting method which uses anonymous questionnaires to achieve a consensus forecast is:
A. sales force opinions.
B. consumer surveys.
C. the Delphi method.
D. time series analysis.
E. executive opinions.
Q:
Which phrase most closely describes the Delphi technique?
A. associative forecast
B. consumer survey
C. series of questionnaires
D. developed in India
E. historical data
Q:
Which of the following would be an advantage of using a sales force composite to develop a demand forecast?
A. The sales staff is least affected by changing customer needs.
B. The sales force can easily distinguish between customer desires and probable actions.
C. The sales staff is often aware of customers' future plans.
D. Salespeople are least likely to be influenced by recent events.
E. Salespeople are least likely to be biased by sales quotas.
Q:
Accuracy in forecasting can be measured by:
A. MSE.
B. MRP.
C. MPS.
D. MTM.
E. MTE.
Q:
Which of the following is not a type of judgmental forecasting?
A. executive opinions
B. sales force opinions
C. consumer surveys
D. the Delphi method
E. time series analysis
Q:
The two general approaches to forecasting are:
A. mathematical and statistical.
B. qualitative and quantitative.
C. judgmental and qualitative.
D. historical and associative.
E. precise and approximation.
Q:
Minimizing the sum of the squared deviations around the line is called:
A. mean squared error technique.
B. mean absolute deviation.
C. double smoothing.
D. least squares estimation.
E. predictor regression.
Q:
Which of the following is not a step in the forecasting process?
A. Determine the purpose and level of detail required.
B. Eliminate all assumptions.
C. Establish a time horizon.
D. Select a forecasting model.
E. Monitor the forecast.
Q:
Which of the following features would not generally be considered common to all forecasts?
A. Assumption of a stable underlying causal system.
B. Actual results will differ somewhat from predicted values.
C. Historical data is available on which to base the forecast.
D. Forecasts for groups of items tend to be more accurate than forecasts for individual items.
E. Accuracy decreases as the time horizon increases.
Q:
Which of the following is/are a primary input into capacity, sales, and production planning?
A. product design
B. market share
C. ethics
D. globalization
E. demand forecasts
Q:
Forecasts based on judgment and opinion do not include:
A. executive opinion.
B. salesperson opinion.
C. second opinions.
D. customer surveys.
E. Delphi methods.
Q:
The more novel a new product or service design is, the more forecasters have to rely on:
A. subjective estimates.
B. seasonality.
C. cyclicality.
D. historical data.
E. smoothed variation.
Q:
When choosing a forecasting technique, a critical trade-off that must be considered is that between:
A. time series and associative.
B. seasonality and cyclicality.
C. length and duration.
D. simplicity and complexity.
E. cost and accuracy.
Q:
Suppose a three-period weighted average is being used to forecast demand. Weights for the periods are as follows: wt-3 = 0.2, wt-2 = 0.3 and wt-1 = 0.5. Demand observed in the previous three periods was as follows: At-3 = 2,200, At-2 = 1,950, At-1 = 2,050. What will be the demand forecast for period t?
A. 2,000
B. 2,095
C. 1,980
D. 2,050
E. 1,875
Q:
Suppose a four-period weighted average is being used to forecast demand. Weights for the periods are as follows: wt-4 = 0.1, wt-3 = 0.2, wt-2 = 0.3 and wt-1 = 0.4. Demand observed in the previous four periods was as follows: At-4 = 380, At-3 = 410, At-2 = 390, At-1 = 400. What will be the demand forecast for period t?
A. 402
B. 397
C. 399
D. 393
E. 403
Q:
Which of the following is a potential shortcoming of using sales force opinions in demand forecasting?
A. Members of the sales force often have substantial histories of working with and understanding their customers.
B. Members of the sales force often are well aware of customers' future plans.
C. Members of the sales force have direct contact with consumers.
D. Members of the sales force can have difficulty distinguishing between what customers would like to do and what they actually will do.
E. Customers often are quite open with members of the sales force with regard to future plans.
Q:
The best forecast is not necessarily the most accurate.
Q:
Seasonal relatives can be used to deseasonalize data or incorporate seasonality in a forecast.
Q:
Bias is measured by the cumulative sum of forecast errors.
Q:
Bias exists when forecasts tend to be greater or less than the actual values of time series.
Q:
The use of a control chart assumes that errors are normally distributed about a mean of zero.
Q:
A tracking signal focuses on the ratio of cumulative forecast error to the corresponding value of MAD.
Q:
A control chart involves setting action limits for cumulative forecast error.
Q:
A forecast method is generally deemed to perform adequately when the errors exhibit an identifiable pattern.
Q:
In exponential smoothing, an alpha of 1.0 will generate the same forecast that a naive forecast would yield.
Q:
MAD is equal to the square root of MSE, which is why we calculate the easier MSE and then calculate the more difficult MAD.
Q:
Correlation measures the strength and direction of a relationship between variables.
Q:
The sample standard deviation of forecast error is equal to the square root of MSE.
Q:
Curvilinear and multiple regression procedures permit us to extend associative models to relationships that are nonlinear or involve more than one predictor variable.
Q:
If a pattern appears when a dependent variable is plotted against time, one should use time series analysis instead of regression analysis.
Q:
Removing the seasonal component from a data series (deseasonalizing) can be accomplished by dividing each data point by its appropriate seasonal relative.
Q:
In order to compute seasonal relatives, the trend of past data must be computed or known, which means that for brand-new products this approach cannot be used.
Q:
A seasonal relative (or seasonal indexes) is expressed as a percentage of average or trend.
Q:
An advantage of trend-adjusted exponential smoothing over the linear trend equation is its ability to adjust over time to changes in the trend.
Q:
Trend-adjusted exponential smoothing requires selection of two smoothing constants.