FiltersDone

Question type

Essay

Multiple Choice

Short Answer

True False

Matching

Exam 3: Forecasting

Show Answer

Share

---

All types

Filters

Study FlashcardsPractice ExamLearn

Question 51

Multiple Choice

Review LaterAdd Note

Review Later

The president of State University wants to forecast student enrollments for this academic year based on the following historical data: What is the forecast for this year using the naive approach?

A) 18,750
B) 19,500
C) 21,000
D) 22,000
E) 22,800

F) D) and E)
G) A) and B)

Correct Answer

verified

Show Answer

Question 52

Multiple Choice

Review LaterAdd Note

Review Later

The previous trend line had predicted 18,500 for two years ago, and 19,700 for last year.What was the mean absolute deviation (MAD) for these forecasts?

A) 100
B) 200
C) 400
D) 500
E) 800

F) B) and D)
G) All of the above

Correct Answer

verified

Show Answer

Question 53

True/False

Review LaterAdd Note

Simple linear regression applies to linear relationships with no more than three independent variables.

Which of the following helps improve supply chain forecasting performance?

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

Which phrase most closely describes the Delphi technique?

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?

What is the linear regression trend line for these data (t = 0 for spring, three years ago)?

What is this year's forecast using exponential smoothing with alpha = .2, if last year's smoothed forecast was 15,000?

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

Forecasting techniques generally assume an existing causal system that will continue to exist in the future.

What is the forecast for this year using a three-year weighted moving average with weights of .5, .3, and .2?

Forecasting techniques that are based on time series data assume that future values of the series will duplicate past values.

Correlation measures the strength and direction of a relationship between variables.

What is this year's forecast using exponential smoothing with alpha = .4, if last year's smoothed forecast was 2600?

In order to compute seasonal relatives, the trend of past data must be computed or known which means that for brand new products this approach can't be used.

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

Which of the following features would not generally be considered common to all forecasts?

What is this week's forecast using trend adjusted (double) smoothing with alpha = 0.5 and beta = 0.1, if the forecast for last week was 65, the forecast for two weeks ago was 75, and the trend estimate for last week's forecast was -5?

The naive approach to forecasting requires a linear trend line.