Exam 3: Forecasting

The business analyst for Video Sales, Inc. wants to forecast this year's demand for DVD decoders based on the following historical data: Year Demand 5 years ago 900 4 years ago 700 3 years ago 600 2 years ago 500 Last year 300 What is the forecast for this year using exponential smoothing with alpha = .4, if the forecast for two years ago was 750?

The T in the model TAF = S + T represents the time dimension (which is usually expressed in weeks or months).

A CPA firm has been using the following equation to predict annual demand for tax audits: Y_t = 55 + 4t. Demand for the past few years is shown below. Is the forecast performing as well as it might? Explain. Year 2 3 4 5 6 7 Demand 60 65 69 76 85 85 Demand Forecast - 2 60 63 \ -3 9 3 65 67 -2 4 4 69 71 -2 2 5 76 75 +1 1 6 85 79 +6 36 7 85 83 +2 4

A smoothing constant of .1 will cause an exponential smoothing forecast to react more quickly to a sudden change than a smoothing constant value of .3.

Curvilinear and multiple regression procedures permit us to extend associative models to relationships that are nonlinear or involve more than one predictor variable.

In order to update a moving average forecast, the values of each data point in the average must be known.

Trend-adjusted exponential smoothing requires selection of two smoothing constants.

The president of State University wants to forecast student enrollments for this academic year based on the following historical data: Year Enrollments 5 years ago 15,000 4 years ago 16,000 3 years ago 18,000 2 years ago 20,000 Last year 21,000 What is the forecast for this year using the naive approach?

Forecasts of future demand are used by operations people to plan capacity.

The dean of a school of business is forecasting total student enrollment for this year's summer session classes based on the following historical data: Year Enrollment Four years ago 2000 Three years ago 2200 Two years ago 2800 Last year 3000 What is this year's forecast using a three-year simple moving average?

Which of the following is not a type of judgmental forecasting?

A manager has been using a certain technique to forecast demand for gallons of ice cream for the past six periods. Actual and predicted amounts are shown below. Would a naive forecast have produced better results? Period Demand Forecast 1 90 87 2 85 88 3 91 87 4 92 89 5 95 90 6 88 92

Given the following data, develop a linear regression model for y as a function of x. x y 8 10 4 5 10 15 15 20 7 10

The primary difference between seasonality and cycles is:

Customer service levels can be improved by better:

A managerial approach toward forecasting which seeks to actively influence demand is:

A persistent tendency for forecasts to be greater than or less than the actual values is called:

Forecasts based on an average tend to exhibit less variability than the original data.

When new products or services are introduced, focus forecasting models are an attractive option.

Demand for the last four months was: Month March April May June Demand 6 8 10 8 A) Predict demand for July using each of these methods: 1) a three-period moving average 2) exponential smoothing with alpha equal to .20 (use a naive forecast for April for your first forecast) B) If the naive approach had been used to predict demand for April through June, what would MAD have been for those months?