Final Exam - Exam III Review Questions/Terms

Step 5

At what level and for what time horizon is the most accurate forecasting done in the company?

What criteria are used to evaluate a forecasting technique? Which criteria have been judged by practitioners to be the most important?

What is a self-fulfilling prophecy as it relates to forecasting?

What are the major components that would go into the cost of forecasting?

What are the characteristics of complex versus simple methods of forecasting?

Why is corporate forecasting more accurate than lower level forecasting?

Step 6

What things might alter the basic forecast?

Step 7

What questions should we ask before we consider a different approach to forecasting?

What is the difference between a bottom-up approach and a top-down approach to forecasting?

What is cumulative forecasting? Why would we want to do this?

Case

Why did Edsel have forecasting problems?

Regression Analysis

What is a transformation? Why do we use it?

What do we mean by “linear" and "nonlinear"? Can you draw a graph to illustrate?

What is a correlation coefficient? What does it tell us?

What is the F-value? What is it used for? How does it work? What do the terms mean in its equation? Can you illustrate by drawing a diagram?

What is the coefficient of determination (R2)? What does it tell you?

In Causal Regression, how would you test the following to see if they were significant at a certain level of confidence: intercept, regression coefficients, and the regression equation?

How would you generate forecasts with Multiple Regression (assuming you had the forecasting equation)?

What is the general forecasting equation for Simple Regression? For Multiple Regression? What do the terms mean in the equations?

What is the difference between Trendline (least squares) Regression and Causal Regression? How do their equations differ? Why is Trendline Regression also called "Least Squares" Regression? Does this same reasoning hold for Causal Regression?

What is a leading indicator? What are lagged variables?

How would you interpret multiple regression spreadsheet (computer) output?

What is the forecasting equation?

Is the overall equation significant?

Are the regression coefficients significantly different from zero?

Is the y-intercept (constant) significantly different from zero?

How much of the variation in the data is explained by the regression equation?

What is the Mean Squared Error (MSE) for the forecasts?

Qualitative Methods

Can you identify qualitative methods if given a description of the method?

What are some advantages and disadvantages of using User Expectation, Sales Force Composite, and the Jury of Executive Opinion methods of forecasting?

How can salespeople's forecasts be improved?

What is the best way to combine executive forecasts?

What is benchmarking? What types of forecasts can it generate?

What is technological forecasting?

What is the difference between exploratory versus normative technological forecasting?

How is the Delphi Technique performed? What are its advantages and disadvantages?

Exam 1

How would you generate forecasts for the Single Moving Average Method?

What is a percentage change? How would you calculate it? How would you generate forecasts for the Average Percent Change Method?

What is Single Exponential Smoothing and what is its forecasting equation? What do the terms in its equation mean? How would you generate forecasts using Single Exponential Smoothing?

What are the steps of the forecasting process?

What data patterns are handled best in forecasting by using each technique?

Review Terms

Can you explain the following terms? You will be asked to explain ten of these on the final exam. (short answer)

self-fulfilling prophecy

automatic

accuracy

supplementary information provided

information storage required

data collection

cost to develop

time to develop

ease of understanding

ability to incorporate special conditions

turning point identification

stability

politics in forecasting

hypotheses

forecast revision

cumulative forecasting

top-down forecasting

bottom-up forecasting

factors that alter forecast

sales potential

market potential

market share

market index

market factor

sales forecast

causal

Coefficient of Determination (R2)

confidence interval

correlation coefficient (r)

degrees of freedom

deviation

F value

hold out sample (cross validation)

intercept

lagged variable

leading indicator

linear

Single Regression

Multiple Regression

nonlinear

R2

significance level

slope

t value

transformation

variance

variation

Decision Analysis

Test Market

User Expectations

Sales Force Composite

Jury of Executive Opinion

benchmarking

Scenario writing

Gaming

Role Playing

Science Fiction

Cross-Impact Analysis

S-Curve

Growth Analogy

Historical Analogy

Social Physics

Morphological Research

Catastrophe Theory

Brainstorming

Technological forecasting

normative

exploratory

Relevance Trees

Systems Analysis

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