Exam 10: Forecasting

Models that predict demand based upon some independent factor(s)other than time are ________ forecasting models.

Multiple regression was used to forecast success in college (GPA)based upon SAT score,high school GPA,and hours spent online.Use the regression output shown and comment on the overall fit of the model,the usefulness of each independent variable,and the value to an admissions department of using the model to make admission decisions.What is the model's forecast for an applicant having a high school GPA of 2.5 and an SAT score of 1000 that spends 20 hours a week on-line? What other variables do you feel would make good indicators of college GPA?

A video game publishing company needs to predict the total sales in the European market for the next year.This is an example of a(n):

A drive-in restaurant has experienced the following customer loads on the past 8 Friday nights.If their forecast for period 7 was 59 customers,then what is their forecast for period number 9 using a smoothing constant of 0.7?

Two time series techniques that are appropriate when the data display a strong upward or downward trend are ________ and ________.

A model with a positive mean forecast error suggests that,on average,the model underforecasts.

A qualitative forecasting technique well-suited for demand forecasts of a new product or service is the:

Using the data shown in the table,develop a trend line that can be used to predict the demand for time period number 20.What is the prediction equation and what is your forecast for period 20?

The greater the randomness in the data,the ________ the value of the alpha in an exponential smoothing forecast.

The panel consensus forecasting approach requires that the forecasting team discuss their forecast as a team but the ________ requires that each member of the team develop a separate forecast initially.

The forecast data matches the actual data perfectly if the mean absolute deviation is 0.0.

The greater the randomness in the model,the greater the number of periods should be used in a moving average forecast.

Which of these quantitative techniques is a causal model?

Which of these forecasts is the BEST?

Examine these two graphs and based on the demand pattern and axis scaling,recommend a forecasting technique (and the required parameters)that would work best for each one.Justify your recommendations.