Test Bank Chapter 8

Assume that a time-series forecast is generated for future demand and subsequently it is observed that the forecast method did not accurately predict the actual demand. Specifically, the forecast errors were found to be: Mean absolute percent error = 10% Cumulative sum of forecast errors = 0 Which one of the statements concerning this forecast is TRUE? A) The forecast has no bias but has a positive standard deviation of errors. B) The forecast has a positive bias and a standard deviation of errors equal to zero. C) The forecast has no bias and has a standard deviation of errors equal to zero. D) The forecast has a positive bias and a positive standard deviation of errors

A

The electricity bill at Padco was driven solely by the lights throughout the office; everything else was driven by alternative energy sources. The office was open roughly 8 hours a day, five days a week and the cleaning crew spent about the same amount of time in the offices each week night. The kilowatt hour usage for the office was best described as a: A) horizontal demand pattern. B) random demand pattern. C) seasonal demand pattern. D) cyclical demand pattern.

A

The judgment methods of forecasting are to be used for purposes of: A) making adjustments to quantitative forecasts due to unusual circumstances B) forecasting seasonal demands in lieu of time-series approaches C) avoiding the calculations necessary for quantitative forecasts D) making forecasts more variable

A

The local building supply store experienced what they considered to be irregular demands for lumber after the devastating hurricane season. These unusual data points were considered: A) nonbase data. B) outliers. C) residuals. D) erroneous.

A

When the underlying mean of a time series is very stable and there are no trend, cyclical, or seasonal influences: A) a simple moving-average forecast with n = 20 should outperform a simple moving-average forecast with n = 3. B) a simple moving-average forecast with n = 3 should outperform a simple moving-average forecast with n = 15. C) a simple moving-average forecast with n = 20 should perform about the same as a simple moving-average forecast with n = 3. D) an exponential smoothing forecast with a = 0.30 should outperform a simple moving-average forecast with α = 0.01.

A

Which one of the following statements about forecasting is FALSE? A) The method for incorporating a trend into an exponentially smoothed forecast requires the estimation of three smoothing constants: one for the mean, one for the trend, and one for the error. B) The cumulative sum of forecast errors (CFE) is useful in measuring the bias in a forecast. C) The standard deviation and the mean absolute deviation measure the dispersion of forecast errors. D) A tracking signal is a measure that indicates whether a method of forecasting has any built-in biases over a period of time.

A

Which one of the following statements about forecasting is FALSE? A) You should use the simple moving-average method to estimate the mean demand of a time series that has a pronounced trend and seasonal influences. B) The weighted moving-average method allows forecasters to emphasize recent demand over earlier demand. The forecast will be more responsive to change in the underlying average of the demand series. C) The most frequently used time-series forecasting method is exponential smoothing because of its simplicity and the small amount of data needed to support it. D) In exponential smoothing, higher values of alpha place greater weight on recent demands in computing the average.

A

Which statement about forecast accuracy is TRUE? A) A manager must be careful not to "overfit" past data. B) The ultimate test of forecasting power is how well a model fits past data. C) The ultimate test of forecasting power is how a model fits holdout samples. D) The best technique in explaining past data is the best technique to predict the future

A

A linear regression model is developed that has a slope of -2.5 and an intercept of 10. The sample coefficient of determination is 0.50. Which of the following statements is TRUE? A) The sample correlation coefficient must be 0.250. B) The sample correlation coefficient must be -0.707. C) The sample correlation coefficient must be -0.250. D) The sample correlation coefficient must be 1.00.

B

When forecasting total demand for all their services or products, few companies err by more than: A) one to four percent. B) five to eight percent. C) nine to twelve percent. D) thirteen to sixteen percent

B

Which one of the following is an example of causal forecasting technique? A) weighted moving average B) linear regression C) exponential smoothing D) Delphi method

B

Which one of the following statements about forecasting is TRUE? A) The five basic patterns of demand are the horizontal, trend, seasonal, cyclical, and the subjective judgment of forecasters. B) Judgment methods are particularly appropriate for situations in which historical data are lacking. C) Casual methods are used when historical data are available and the relationship between the factor to be forecast and other external and internal factors cannot be identified. D) Focused forecasting is a technique that focuses on one particular component of demand and develops a forecast from it.

B

Which word best describes forecasting? A) quantitative B) process C) resource D) managerial

B

With the multiplicative seasonal method of forecasting: A) the times series cannot exhibit a trend. B) seasonal factors are multiplied by an estimate of average demand to arrive at a seasonal forecast. C) the seasonal amplitude is a constant, regardless of the magnitude of average demand. D) there can be only four seasons in the time-series data.

B

Barney took what he liked to call "the shotgun approach" to forecasting. Every period he tried a number of different forecasting approaches and at the end of the period he reviewed all of the forecasts to see which was the most accurate. The winner would be used for next period's forecast (but he still made forecasts all possible ways so he could use the system again for the following period). The more formal name for this technique is: A) combination forecasting. B) post-hoc forecasting. C) focus forecasting. D) shotgun forecasting. He is using the correct terminology.

C

It would be most appropriate to combine a judgment approach to forecasting with a quantitative approach by: A) having a group of experts examine each historical data point to determine whether it should be included in the model. B) combining opinions about the quantitative models to form one forecasting approach. C) adjusting a forecast up or down to compensate for specific events not included in the quantitative technique. D) developing a trend model to predict the outcomes of judgmental techniques in order to avoid the cost of employing the experts.

C

Professor Willis noted that the popularity of his office hours mysteriously rose in the middle and the end of each semester, falling off to virtually no visitors throughout the rest of the year. The demand pattern at work is: A) cyclical. B) random. C) seasonal. D) trend.

C

Using salesforce estimates for forecasting has the advantage that: A) no biases exist in the forecasts. B) statistical estimates of seasonal factors are more precise than any other approach. C) forecasts of individual sales force members can be easily combined to get regional or national sales totals. D) confusion between customer "wants" (wish list) and customer "needs" (necessary purchases) is eliminated.

C

Which one of the following statements about forecasting is FALSE? A) Causal methods of forecasting use historical data on independent variables (promotional campaigns, competitors' actions, etc.) to predict demand. B) Three general types of forecasting techniques are used for demand forecasting: time-series analysis, causal methods, and judgment methods. C) Time series express the relationship between the factor to be forecast and related factors such as promotional campaigns, economic conditions, and competitor actions. D) A time series is a list of repeated observations of a phenomenon, such as demand, arranged in the order in which they actually occurred.

C

Which one of the following statements about the patterns of a demand series is FALSE? A) The five basic patterns of most business demand series are the horizontal, trend, seasonal, cyclical, and random patterns. B) Estimating cyclical movement is difficult. Forecasters do not know the duration of the cycle because they cannot predict the events that cause it. C) The trend, over an extended period of time, always increases the average level of the series. D) Every demand series has at least two components: horizontal and random.

C

The dispersion of forecast errors is measured by both MAD and MSE, which behave differently in the way they emphasize errors. ________ gives larger weight to errors and ________ gives smaller weight to errors.

mse mad

The ________ measures the amount of variation in the dependent variable about its mean that is explained by the regression line

sample coefficient of determination, r-squared

A(n) ________ measures the direction and strength between the independent variable and the dependent variable.

sample correlation coefficient or R

________ is a time-series method used to estimate the average of a demand time series by averaging the demand for the n most recent time periods

simple moving average

A regression equation with a coefficient of determination near one would be most likely to occur when the data demonstrated a: A) seasonal demand pattern. B) trend demand pattern. C) cyclical demand pattern. D) random demand pattern.

B

Salesforce estimates are extremely useful for technological forecasting

False

One aspect of demand that makes every forecast inaccurate is: A) trend variation. B) random variation. C) cyclical variation. D) seasonal variation.

B

________ methods use historical data on independent variables to predict demand.

Casual

A forecasting system that brings the manufacturer and its customers together to provide input for forecasting is a(n): A) nested system. B) harmonically balanced supply chain. C) iterative Delphi method system for the supply chain. D) collaborative planning, forecasting, and replenishment system

D

Andy took what he liked to call "the sheriff without a gun" approach to forecasting. Every period he tried a number of different forecasting approaches and simply averaged the predictions for all of the techniques. This overall average was the official forecast for the period. The more formal name for this technique is: A) grand averaging. B) focus forecasting. C) simple average. D) combination forecasting.

D

Combination forecasting is a method of forecasting that selects the best from a group of forecasts generated by simple techniques.

False

________ is a systematic approach to determine consumer interest in a product or service by creating and testing hypotheses through data-gathering surveys.

Market Research

A(n) ________ is a measure that indicates whether a method of forecasting is accurately predicting actual changes in demand

Tracking signal

A systematic increase or decrease in the mean of the series over time is a(n) ________.

Trend

One of the basic time series patterns is random.

True

Some analysts prefer to use a holdout set as the final test of a forecasting procedure.

True

Time-series forecasts require information about only the dependent variable.

True

Forecasting is a(n) ________ that should continually be reviewed for improvements.

process

A(n) ________ forecast is a time-series method whereby the forecast for the next period equals the demand for the current period.

naive

A history file of past demand will often be separated into two parts; the ________ part will reflect irregular demands.

nonbase

The larger the slope of the regression line, the more accurate the regression forecast.

False

Focus forecasting selects the best forecast from a group of forecasts generated by individual techniques.

True

Forecasts almost always contain errors.

True

Technological forecasting is an application of executive opinion in light of the difficulties in keeping abreast of the latest advances in technology.

True

The causal method of forecasting uses historical data on independent variables (such as promotional campaigns and economic conditions) to predict the demand of dependent variables (such as sales volume).

True

The repeated observations of demand for a product or service in their order of occurrence form a pattern known as a time series.

True

The trend projection with regression model can forecast demand well into the future.

True

Time-series analysis is a statistical approach that relies heavily on historical demand data to project the future size of demand.

True

Polly Prognosticator was the greatest quantitative forecaster in recorded history. A skillful user of all techniques in your chapter on forecasting, she knew better than to try and develop a forecast for data that exhibited a: A) random pattern. B) horizontal pattern. C) seasonal pattern. D) cyclical pattern.

A

The Delphi method of forecasting is useful when: A) judgment and opinion are the only bases for making informed projections B) a systematic approach to creating and testing hypotheses is needed and the data are usually gathered by sending a questionnaire to consumers C) historical data are available and the relationship between the factor to be forecast and other external or internal factors can be identified D) historical data is available and the best basis for making projections is to use past demand patterns

A

Which one of the following is most useful for measuring the bias in a forecast? A) cumulative sum of forecast errors B) standard deviation of forecast errors C) mean absolute deviation of forecast errors D) percentage forecast error in period t

A

A forecaster that uses a holdout set approach as a final test for forecast accuracy typically uses: A) the entire data set available to develop the forecast. B) the older observations in the data set to develop the forecast and more recent to check accuracy. C) the newer observations in the data set to develop the forecast and older observations to check accuracy. D) every other observation to develop the forecast and the remaining observations to check the accuracy.

B

A tracking signal greater than zero and a mean absolute deviation greater than zero imply that the forecast has: A) no bias and no variability of forecast error. B) a nonzero amount of bias and a nonzero amount of forecast error variability. C) no bias and a nonzero amount of forecast error variability. D) a nonzero amount of bias and no variability of forecast error.

B

The manufacturer developed and tested a questionnaire, designed to assist them in gauging the level of acceptance for their new product, and identified a representative sample as part of their: A) salesforce estimate. B) market research. C) executive opinion. D) Delphi method.

B

Which one of the following statements is TRUE? A) The ideal of zero bias and zero MAD can be accomplished by systematically searching for the best values of the smoothing constants. B) Bias is always less than MAD. C) For projections of more stable demand patterns without trends, seasonal influences, or cyclical influences, use larger values of n in the simple moving-average approach. D) One disadvantage of a weighted moving average forecast is that it does not allow you to emphasize recent demand over earlier demand.

C

The number of #2 pencils the bookstore sells appears to be highly correlated with the number of student credit hours each semester. The bookstore manager wants to create a linear regression model to assist her in placing an appropriate order. In this scenario: A) the dependent variable is student credit hours B) there are two independent variables C) there are two dependent variables D) the independent variable is student credit hours

D

There are historically three 32-month periods of generally rising prices in the stock market for every one 9-month period of falling prices. This observation leads you to conclude that the stock market exhibits a: A) random pattern. B) trend pattern C) seasonal pattern. D) cyclical pattern.

D

Which of the following statements regarding time-series methods is FALSE? A) A naive forecast is identical to a simple moving average of one period. B) Exponential smoothing with an alpha equal to 1.00 is identical to a naive forecast. C) A weighted moving average with weights of 0.5 and 0.5 is identical to a simple moving average of two periods. D) A simple moving average of three periods is identical to exponential smoothing with an alpha equal to 0.33.

D

The ________ is a process of gaining consensus from a group of experts while maintaining their anonymity.

Delphi

The ________ variable is the variable that one wants to forecast.

Dependent

A bias error results from unpredictable factors that cause the forecast to deviate from actual demand.

False

Aggregating products or services together generally decreases the forecast accuracy.

False

Judgment methods of forecasting should never be used with quantitative forecasting methods.

False

Market research is a systematic approach to determine consumer interest by gaining consensus from a group of experts while maintaining their anonymity.

False

Random variation is an aspect of demand that increases the accuracy of the forecast.

False

Regression equations with a coefficient of determination close to zero are extremely accurate because they have little forecast error.

False

The Delphi method is a process of gaining consensus from a group of experts by debate and voting throughout several rounds of group discussion led by a moderator.

False

The closer the value of the sample correlation coefficient is to -1.00, the worse the predictive ability of the independent variable for the dependent variable.

False

The standard error of the estimate measures how closely the data on the independent variable cluster around the regression line.

False

The trend projection with regression model is highly adaptive.

False

________ methods of forecasting translate the opinions of management, experts, consumers, or salesforce into quantitative estimates.

Judgement

In an exponential smoothing model a ________ value for alpha results in greater emphasis being placed on more recent periods.

Larger

________ is a causal method of forecasting in which one variable is related to one or more variables by a linear equation.

Linear Regression

Variations in demand that cannot be predicted are said to be a(n) ________ pattern.

Random

________ analysis is a statistical approach that relies heavily on historical demand data to project the future size of demand, and it recognizes trends and seasonal patterns.

Time-series

A linear regression model results in the equation Y = 15 - 23X. If the coefficient of determination is a perfect 1.0, the correlation coefficient must be -1.

True

A naive forecast is a time-series method whereby the forecast for the next period equals the demand for the current period.

True

A simple moving average of one period will yield identical results to a naive forecast.

True

Aggregation is the act of clustering several similar products or services.

True

An exponential smoothing model with an alpha equal to 1.00 is the same as a naive forecasting model.

True

Better forecasting processes yield better forecasts.

True

Bias is the worst kind of forecasting error.

True

Combination forecasting is most effective when the techniques being combined contribute different kinds of information to the forecasting process.

True

Judgment methods of forecasting are quantitative methods that use historical data on independent variables to predict demand

False

________ is the prediction of future events used for planning purposes.

Forcasting

________ are assumed to "cause" the results that a forecaster wishes to predict.

Independent variables

Forecast error is found by subtracting the forecast from the actual demand for a given period.

True

When a significant trend is present, exponential smoothing forecasts can be below or above the actual demand, and must therefore be modified.

True

________ are produced by averaging independent forecasts based on different methods or different data, or both.

combination forecasts

________ selects the best forecast from a group of forecasts generated by individual techniques.

focus forecasting

________ is the difference found by subtracting the forecast from actual demand for a given period.

forecast error

A(n) ________ is a portion of data from more recent time periods that is used to test different models developed from earlier time period data.

holdout set

________ are often the result of neglecting or not accurately estimating patterns of demand such as a trend, seasonal, or cyclical pattern.

Bias errors

Cyclical patterns arise from ________ and ________.

Business and Product cycle

Which one of the following basic patterns of demand is difficult to predict because it is affected by national or international events or because of a lack of demand history reflecting the stages of demand from product development to decline? A) horizontal B) seasonal C) random D) cyclical

D

The ________ measure of forecast errors puts the size of the error in appropriate context by forming the ratio of the average forecast error to the average ________.

mape demand