Forecasting

Question 1

Forecast

Answer 1

A statement about the future value of a variable of interest, such as demand.

Question 2

Common Features of Forecasts

Answer 2

Assumes same causal system.
Rarely perferct because of randomness
More accurate for groups vs. individuals
Accuracy decreases as time horizon increases.

Question 3

Forecasting Approaches

Answer 3

Qualitative Methods

Quantitative Methods

Question 4

Qualitative Methods

Answer 4

Used when situation is vague and little data exist.
Invovles intuition, experience.
Judgmental Forecasts
Delphi Method

Question 5

Quantitative Methods

Answer 5

Used when situation is ‘stable’ and historical data exists.
Involves mathematical techniques
Time series forecasts and Associative models

Question 6

Time Series

Answer 6

Time-ordered sequence of observations taken at regular internvals over a period of time.

Question 7

Time Series Assumption:

Answer 7

Future will be like the past.

Question 8

Time Series Behaviors

Answer 8

Trend
Seasonality
Cycle
Irregular Variations
Random Variations

Question 9

Types of Time Series Methods

Answer 9

Naive Method
Moving Average
Weighted Moving Average
Exponential Smoothing
Trend
Exponential Smoothing With Trend
Seasonality

Question 10

Exponential Smoothing

Answer 10

Current Forecast = Previous forecast + a(Previous Actual - Previous Forecast)
The most recent observations might have the highest predicitive value.
More smooth as alpha is increased.

Question 11

Picking a Smoothing Constant a

Answer 11

Using judgement or trial and error
Balancing smoothness and responsiveness
Low a when stable
High a when susceptible to change

Question 12

Techniques for Trend

Answer 12

Linear Trend

Nonlinear Trend

Question 13

Seasonality

Answer 13

Holidays, Weather, Manufacturing year, Fashion year, academic year, sports year
Expressed as variation from average or trend line.

Question 14

Models of Seasonality

Answer 14

Additive Model

Multiplication Model

Question 15

Additive Model

Answer 15

Seasonality factor is expressed as a quantity. Simply add or subtract from the series average.

Question 16

Multiplicative Model

Answer 16

Seasonality is expressed as a percentage of the average amount

Question 17

Seasonal Relative

Answer 17

Amount by which overall average is multiplied to generate forecast for this season.

Question 18

Deseasonalize

Answer 18

Historical observations to get nonseasonal components.

Question 19

Associative Forecasting

Answer 19

Rely on identification of related variable that can be used to predict of the variable of interest.

Question 20

Associative Techniques

Answer 20

Predictor Variables

Regression

Question 21

Predictor Variable

Answer 21

Used to predict values of variable interest

Question 22

Regression

Answer 22

Technique for fitting a line to a set of points.

Question 23

Choosing a Forecasting Technique

Answer 23

Cost and Accuracy
Short-Term Techniques
Long-Term Techniques

Question 24

Short-Term Techniques

Answer 24

Moving Average

Exponential Smoothing

Question 25

Long-Term Techniques

Answer 25

Trend

Delphi

Question 26

Good indicator of Economy

Answer 26

Sales of Semiconductors

Question 27

Error:

Answer 27

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

Question 28

Types of Measures of Forecast Accuracy:

Answer 28

Mean Absolute Deviation (MAD)
Mean Square Error (MSE)
Mean Absolute Percentage Error (MAPE)

Question 29

To find the Seasonal Relative

Answer 29

Find Length
Find the average for the length
If odd, use middle number & divide by average.
Take the seasonal relatives for the time asked for and average them.

Question 30

Which term most clearly relate to associative forecasing techniques:

Answer 30

Predictor Variables

Question 31

A simple moving average assigns equal weight to each data point that is represented by the average.

Answer 31

True

Question 32

Removing the seasonal component from a data series (deseasonalizing) can be accomplished by dividing each data point by its appropriate seasonal relative.

Answer 32

True

Question 33

Accuracy in forecasting can be measured by

Answer 33

MSE
MAPE
MAD

Question 34

In trend-adjusted exponential smoothing, the trend adjusted forecast consists of:

Answer 34

An exponentially smoothed forecast and a smoothed trend factor.