Chapter 12 - Forecasting

Question 1

Adjusted Exponential Smoothing

Answer 1

an exponential smoothing forecast adjusted for trend.

Question 2

Average Error

Answer 2

the cumulative error averaged over the number of time periods.

Question 3

Coefficient of Determination

Answer 3

the correlation coefficient squared; it measures the portion of the variation in the dependent variable that can be attributed to the independent variable.

Question 4

Correlation

Answer 4

a measure of the strength of the causal relationship between the independent and dependent variables in a linear regression equation.

Question 5

Cumulative Error

Answer 5

a sum of the forecast errors; also known as bias.

Question 6

Cycle

Answer 6

an up-and-down movement in demand over time.

Question 7

Delphi Method

Answer 7

a procedure for acquiring informed judgements and opinions from knowledgeable individuals to use as a subjective forecast.

Question 8

Exponential Smoothing

Answer 8

an averaging method that weights the most recent data more strongly than more distant data.

Question 9

Forecast Error

Answer 9

the difference between actual and forecasted demand.

Question 10

Linear Regression

Answer 10

a mathematical technique that relates a dependent variable to an independent variable in the form of a linear equation. y=mx +b

Question 11

Linear Trend Line

Answer 11

A forecast using the linear regression equation to relate demand to time.

Question 12

Long-Range Forecast

Answer 12

a forecast encompassing a period longer than two years into the future.

Question 13

Mean Absolute Deviation (MAD)

Answer 13

the per-period average of the absolute difference between actual and forecasted demand.

Question 14

Mean Absolute Percent Deviation (MAPD)

Answer 14

The absolute forecast error measured as a percentage of demand.

Question 15

Mean Squared Error (MSE)

Answer 15

The average of the squared forecast errors.

Question 16

Moving Average

Answer 16

average demand for a fixed sequence of periods including the most recent period.

Question 17

Multiple Regression

Answer 17

A mathematical relationship that relates a dependent variable to two or more independent variables.

Question 18

Qualitative Forecast Methods

Answer 18

non-quantitative, subjective forecasts based on judgement, opinion, experience, and expert opinion.

Question 19

Quantitative Forecast Methods

Answer 19

Forecasts derived from a mathematical formula.

Question 20

Random Variations

Answer 20

Movements in demand that are not predictable and follow no pattern.

Question 21

Regression Forecasting Methods

Answer 21

a class of mathematical techniques that relate demand to factors that cause demand behavior.

Question 22

Seasonal Factor

Answer 22

A numerical value that is multiplied be the normal forecast to get a seasonally adjusted forecast.

Question 23

Seasonal Pattern

Answer 23

An oscillating movement in demand that occurs periodically in the short run and is repetitive.

Question 24

Short to Mid-Range Forecast

Answer 24

a forecast encompassing the immediate future, usually days or weeks, but up to two years.

Question 25

Smoothing Constant

Answer 25

The weighting factor given to the most recent data in exponential smoothing forecasts.

Question 26

Time Frame

Answer 26

how far into the future something is forecasted.

Question 27

Time Series Methods

Answer 27

A class of statistical methods that uses historical demand data over a period of time to predict future demand.

Question 28

Tracking Signal

Answer 28

a measure computed by dividing the cumulative error by MAD;

used for monitoring bias in the forecast.

Question 29

Trend

Answer 29

a gradual, long-term up or down movement of demand.

Question 30

Weighted Moving Average

Answer 30

a moving average with more recent data demand values adjusted with weights.