Chapter 4

Question 1

T/F: A naive forecast for September sales of a product would be equal to the forecast for August.

Answer 1

False. A naive forecast would be equal to last period’s ACTUAL, not forecasted.

Question 2

T/F: The forecasting time horizon and the forecasting techniques used tend to vary over the life cycle of a product.

Answer 2

True

Question 3

T/F: Demand (sales) forecasts serve as inputs to financial, marketing, and personnel planning.

Answer 3

True

Question 4

T/F: Forecasts of individual products tend to be more accurate than forecasts of product families.

Answer 4

False

Question 5

T/F: Most forecasting techniques assume that there is some underlying stability in the system.

Answer 5

True

Question 6

T/F: The sales force composite forecasting method relies on salespersons’ estimates of expected sales.

Answer 6

True

Question 7

T/F: A time-series model uses a series of past data points to make the forecast.

Answer 7

True

Question 8

T/F: The quarterly “make meeting” of Lexus dealers is an example of a sales force composite forecast.

Answer 8

True

Question 9

T/F: Cycles and random variations are both components of time series.

Answer 9

True

Question 10

T/F: A naive forecast for September sales of a product would be equal to the sales in August.

Answer 10

True

Question 11

T/F: One advantage of exponential smoothing is the limited amount of record keeping involved.

Answer 11

True

Question 12

T/F: The larger the number of periods in the simple moving average forecasting method, the greater the method’s responsiveness to changes in demand.

Answer 12

False

Question 13

T/F: Forecast including trend is an exponential smoothing technique that utilizes two smoothing constants: one for the average level of the forecast and one for its trend.

Answer 13

True

Question 14

T/F: Mean Squared Error and Coefficient of Correlation are two measures of the overall error of a forecasting model.

Answer 14

False. MSE and MAD are two measures, Coefficient of Correlation is a measure of the strength of relationship between two variables.

Question 15

T/F: In trend projection, the trend component is the slope of the regression line.

Answer 15

True

Question 16

T/F: In trend projection, a negative regression slope is mathematically impossible.

Answer 16

False

Question 17

T/F: Seasonal indexes adjust raw data for patterns that repeat at regular time intervals.

Answer 17

True

Question 18

T/F: If quarterly seasonal index has been calculated at 1.55 for the Oct-Dec quarter, then raw data for that quarter must be multiplied by 1.55 so that the quarter can be fairly compared to other quarters.

Answer 18

False. You don’t multiply to fairly compare to other quarters, you multiply to get a more accurate forecast.

Question 19

T/F: The best way to forecast a business cycle is by finding a leading variable.

Answer 19

True

Question 20

T/F: Linear-regression analysis is a straight-line mathematical model to describe the functional relationships between independent and dependent variables.

Answer 20

True

Question 21

T/F: The larger the standard error of the estimate, the more accurate the forecasting model.

Answer 21

False, duh

Question 22

T/F: 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.

Answer 22

True

Question 23

T/F: In a regression equation where Y is demand and X is advertising, a coefficient of determination (R^2) of .70 means that 70% of the variance in advertising is explained by demand.

Answer 23

False. It means that 70% of the variation can be determined by the regression equation.

Question 24

T/F: Demand cycles for individual products can be driven by product life cycles.

Answer 24

True

Question 25

T/F: If a forecast is consistently greater than (or less than) actual values, the forecast is said to be biased.

Answer 25

True

Question 26

T/F: Focus forecasting tries a variety of computer models and selects the best one for a particular application.

Answer 26

True

Question 27

T/F: Many service firms use point-of-sale computers to collect detailed records needed for accurate short-term forecasts.

Answer 27

True

Question 28

What two numbers are contained in the daily report to the CEO of Walt Disney Parks & Resorts regarding the six Orlando parks?

Answer 28

Yesterday’s forecasted attendance and yesterday’s actual attendance

Question 29

Using an exponential smoothing with smoothing constant alpha=.20, how much weight would be assigned to the 2nd most recent period?

Answer 29

.16

Question 30

What are forecasts more accurate for, groups of items or individual items?

Answer 30

Forecasts are more accurate for groups of items

Question 31

T/F: Forecasts become more accurate with a longer time horizon.

Answer 31

False

Question 32

One use of short-range forecasts is to determine…

Answer 32

job assignments

Question 33

Forecasts are usually classified by time horizon into what three categories?

Answer 33

Short-range, medium-range, and long-range

Question 34

The three major types of forecasts used by business organizations are?

Answer 34

Economic, Technological, and Demand

Question 35

A forecast with a time horizon of about 3 months to 3 years is typically called a _____-range forecast?

Answer 35

Medium-range

Question 36

Forecasts used for new product planning, capital expenditures, facility location or expansion, and R&D typically utilize a _____-range forecast.

Answer 36

Long-range

Question 37

Which of the following is NOT a step in the forecasting process?

Answer 37

Eliminate any assumptions

Question 38

What are the two general approaches to forecasting?

Answer 38

Qualitative and Quantitative

Question 39

Which forecasting method uses three types of participants: decision makers, staff personnel, and respondents?

Answer 39

the Delphi method

Question 40

Is moving average a qualitative or quantitative forecasting method?

Answer 40

Quantitative

Question 41

What forecasting model pools the opinions of a group of experts or managers?

Answer 41

Jury of executive opinion model

Question 42

What behaviors may time series data exhibit?

Answer 42

Trend, random variations, seasonality, cycles

Question 43

Gradual, long-term movement in time series data is called…

Answer 43

trends

Question 44

T/F: The analysis of past demand helps predict future demand.

Answer 44

True

Question 45

Which forecasting technique uses variables such as price and promotional expenditures, which are related to product demand, to predict demand?

Answer 45

Associative models

Question 46

The fundamental difference between cycles and seasonality is the

Answer 46

duration of repeating patterns

Question 47

In time series, which of the following cannot be predicted?

Answer 47

Random Fluctuations

Question 48

What time series model assumes that demand in the next period will be equal to the most recent period’s demand?

Answer 48

Naive Approach

Question 49

A six-month moving average forecast is better than a three-month moving average forecast if demand…

Answer 49

Is rather stable

Question 50

Increasing the number of periods in a moving average will accomplish greater smoothing, but at the expense of

Answer 50

responsiveness to changes

Question 51

Which time series model uses past forecasts and past demand data to generate a new forecast?

Answer 51

Exponential Smoothing

Question 52

What are the characteristics of exponential smoothing?

Answer 52

Smoothes random variations, easily altered weighting scheme, and minimal data storage requirements

Question 53

What smoothing constant would make an exponential smoothing forecast equivalent to a naive forecast?

Answer 53

1.0

Question 54

A forecast based on the previous forecast plus a percentage of the forecast error is an….

Answer 54

exponentially smoothed forecast