Chapter 3: Forecasting

Question 1

A statement about the future value of a variable of interest.

Answer 1

Forecast

Question 2

The first basic step in the forecasting process

Answer 2

Determine the Purpose of the Forecast

Question 3

The second basic step in the forecasting process.

Answer 3

Establish a Time Horizon

Question 4

The third basic step in the forecasting process.

Answer 4

Obtain, clean, and analyze appropriate data

Question 5

The fourth basic step in the forecasting process

Answer 5

Select a forecasting technique

Question 6

The fifth basic step in the forecasting process

Answer 6

Make the forecast

Question 7

The sixth basic step in the forecasting process

Answer 7

Monitor the forecast errors

Question 8

Difference between the actual value and the value that was predicted for a given period.

Answer 8

Error

Question 9

The average absolute forecast error.

Answer 9

Mean Absolute Deviation

Question 10

The average of squared forecast errors.

Answer 10

Mean Squared Error

Question 11

The average absolute percentage error.

Answer 11

Mean Absolute Percent Error

Question 12

Approach to forecasting that consists mainly of subjective inputs.

Answer 12

Qualitative

Question 13

Approach to forecasting that involves either the projection of historical data or the development of associative models that attempt to use causal variables to make a forecast.

Answer 13

Quantitative

Question 14

Type of information which includes human factors, personal opinions, and hunches.

Answer 14

Soft Information

Question 15

Type of data that is objective information.

Answer 15

Hard Data

Question 16

Forecasts that use subjective inputs such as opinions to form consumer surveys, sales staff, managers, executives, and experts.

Answer 16

Judgmental Forecasts

Question 17

Forecasts that project patterns identified in recent time-series observations.

Answer 17

Time-Series Forecasts

Question 18

Forecasting technique that uses explanatory variables to predict future demand.

Answer 18

Associative Model

Question 19

An iterative process in which managers and staff complete a series of questionnaires, each developed from the previous one, to achieve a consensus forecast.

Answer 19

Delphi Method

Question 20

A time-ordered sequence of observations taken at regular intervals.

Answer 20

Time Series

Question 21

A long-term upward or downward movement in data.

Answer 21

Trend

Question 22

Short-term regular variations related to the calendar or time of day.

Answer 22

Seasonality

Question 23

Wavelike variations lasting more than one year.

Answer 23

Cycle

Question 24

Caused by unusual circumstances, not reflective of typical behavior.

Answer 24

Random Variations

Question 25

A forecast for any period that equals the previous period's actual value.

Answer 25

Naive Forecast

Question 26

Technique that averages a number of recent actual values, updated as new values become available.

Answer 26

Moving Average

Question 27

More recent values in a series are given more weight in computing a forecast.

Answer 27

Weighted Average

Question 28

A weighted averaging method based on previous forecast plus a percentage of the forecast error.

Answer 28

Exponential Smoothing

Question 29

Using the forecasting method that demonstrates the best recent success.

Answer 29

Focus Forecasting

Question 30

Used to develop forecasts when trend is present.

Answer 30

Linear Trend Equation

Question 31

Linear Trend Equation

Answer 31

Ft = a + bt

Question 32

Variation of exponential smoothing used when a time series exhibits a linear trend.

Answer 32

Trend-Adjusted Exponential Smoothing

Question 33

Regularly repeating movements in series values that can be tied to recurring events.

Answer 33

Seasonal Variations

Question 34

The seasonal percentage applied in the multiplicative model.

Answer 34

Seasonal Relative

Question 35

Variables that can be used to predict values of the variable of interest.

Answer 35

Predictor Variables

Question 36

Technique for fitting a line to a set of points.

Answer 36

Regression

Question 37

Minimizes the sum of the squared vertical deviations around the line.

Answer 37

Least Squares Line

Question 38

A measure of the scatter of points around a regression line.

Answer 38

Standard Error of Estimate

Question 39

A measure of the strength and direction of relationship between two variables.

Answer 39

Correlation

Question 40

A visual tool for monitoring forecast errors.

Answer 40

Control Chart

Question 41

The ratio of cumulative forecast error to the corresponding value of MAD, used to monitor a forecast.

Answer 41

Tracking Signal

Question 42

Persistent tendency for forecasts to be greater or less than the actual values of a time series.

Answer 42

Bias

Question 43

Type of error that occurs when the forecast is too low.

Answer 43

Positive Error

Question 44

Type of error that is the difference between the actual and predicted values in a given period.

Answer 44

Forecast Error

Question 45

Type of error that occurs when the forecast is too high.

Answer 45

Negative Error

Question 46

Alternate name for seasonal relative.

Answer 46

Seasonal Index

Question 47

The essence of associative techniques is the development of an equation that summarizes the effects of _____

Answer 47

Predictor Variables

Question 48

In time-series data, _____ are regularly repeating upward or downward movements in series values that can be tied to recurring events.

Answer 48

Seasonal Variations

Question 49

_____ forecasts pertain to ongoing operations.

Answer 49

Short-term

Question 50

_____ forecasts are an important strategic planning tool.

Answer 50

Long-term

Question 51

Represents an error of zero on a control chart.

Answer 51

The Center Line

Question 52

Linear Trend Equation

Answer 52

F=a+bt

Question 53

Exponential Smoothing Forecast

Answer 53

Ft = Ft-1 + a(At-1 - Ft-1)

Question 54

Formula for error in period t

Answer 54

et = At-Ft

Question 55

A value of 0.25 or less of r^2 indicates a _____ predictor.

Answer 55

Poor

Question 56

A value between 0.25 and 0.8 of r^2 indicates a _____ predictor.

Answer 56

Moderate

Question 57

Formula for trend-adjusted exponential smoothing forecast.

Answer 57

TAFt+1 = St + Tt

Question 58

Represents the absolute forecast error.

Answer 58

MAD

Question 59

Measures the percentage of variation in the values of the dependent variable that is "explained" by the independent variable.

Answer 59

R^2

Question 60

Model in which predictions are made on demand for an established product.

Answer 60

Diffusion Model

Question 61

Often used to develop long-range plans and new product development.

Answer 61

Executive Opinions

Question 62

A tracking signal compares the cumulative forecast error to the MAD in order to detect any _____ over time.

Answer 62

Bias

Question 63

In the equations for the coefficients of a line, what is the a term?

Answer 63

Intercept

Question 64

In the equations for the coefficient of a line, what is the b term?

Answer 64

Slope

Question 65

In the equations for the coefficients of a line, what is the y term?

Answer 65

Value of the time series