1. The president of State University wants to forecast student enrollment for Year 3. Using exponential smoothing with trend, the forecast for the current year (Year 1) is 20,000. Assume the estimated trend is 1,500. What is the forecast for Year 3?
- 18,500.
- 20,000.
- 21,500.
- 23,000.
- 24,500.
2. Which of the following statements are true?
- Exponential smoothing with trend requires selection of two smoothing constants.
- Judgmental forecasting methods have been developed to interpret statistical data.
- The sales force composite method is a top-down approach to forecasting.
- The moving-average forecasting method assigns unequal weights to each value in the average.
- None of the above
3. Which of the following are features of a normal distribution?
- Symmetric shape
- Considerable skewness
- Cannot be used to represent sample means
- Cannot be used to describe a random variable
- All of the above
4. Which of the following statements is true with regard to linear regression?
- It is used to predict the value of an independent variable.
- It can be used to calculate a trend line.
- The slope must be less than or equal to 1.
- A y-intercept value is not necessary.
- All of the above
5. Gradual, long-term movement in time-series values is called:
- temporal variation.
- cyclical movement.
- exponential smoothing.
- linear regression.
- None of the above.
6. In exponential smoothing with trend, the forecast consists of:
- an exponentially smoothed forecast and a smoothed trend factor.
- the old forecast adjusted by a trend factor.
- the old forecast and a smoothed trend factor.
- a moving-average and a trend factor.
- None of the above
7. The president of State University wants to forecast student enrollment 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 18,000 Last year 16,000
8. What is the forecast for this year using exponential smoothing with alpha = 0.5, if the forecast for two years ago was 16,000?
- 16,500
- 17,000
- 17,500
- 18,000
- None of the above
9. Two different forecasting methods are applied to the same data set. If the Mean absolute deviation is higher for the second method and the Mean square error is higher for the first method, what does this indicate?
- Both methods produce acceptable error rates.
- The second method is more accurate than the first method.
- The first method produces more extreme errors than the second method.
- The error measure for the first method is more difficult to interpret.
- None of the above
10. Which of the following statements is true regarding the Mean absolute deviation measure and the Mean square error measure?:
- The values for both measures are unchanged if the forecasting method is changed.
- Both are measures of seasonal variation.
- Lower values of these measures reflect more accurate forecasting methods.
- The Mean absolute deviation measure places greater weight on large errors.
- None of the above.
11. Which of the following is an example of a seasonal pattern in data?
- The data values are continually increasing with time.
- The data exhibits an exponentially smoothed pattern.
- The average sales on Monday is higher than the average daily sales.
- The volume of calls is dependent upon the product release schedule.
- None of the above
12. In order to increase the responsiveness of a forecast made using the moving-average method, the number of values in the average should be:
- multiplied.
- increased.
- decreased.
- held stable.
- None of the above
Using the following data, what is the moving-average forecast for the next period using a three period model?
Period Demand
1 75
2 80
3 85
4 90
80
85
90
95
None of the above