# Time Series

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16. Given this frequency distribution, the random number 0.61 would be interpreted as a demand of:

a) 0

b) 1

c) 2

d) 3

17. A graduate research assistant "moonlights" at the short order counter in the student union snack bar in the evenings. He is considering asking for help taking orders, but needs to convince the management that they should hire another student. Because he is taking a simulation class, he thinks it may be the perfect way to convince management to hire more help if he can show that customers have to wait a long time. When a customer arrives, he takes their order and their payment, prepares the food, gives it to the customer, and then takes the order from the next person in line. If someone arrives while he's cooking an order, they have to wait until he's completed the current order. He has simulated 5 orders.

Average customer waiting time is:

a) 1 minute

b) 2 minutes

c) 2.5 minutes

d) 3.0 minutes

18. The __________ method is the most common type of forecasting method for the long-term strategic planning process.

a) time series

b) regression

c) qualitative

19. Given the following data on the number of pints of ice cream sold at a local ice cream store for a 6-period time frame:

Compute a 3-period moving average for period 6.

a) 246.67

b) 247.50

c) 283.33

d) 300

20. Use the table of data provided in question 19.

Compute a 5-period moving average for period 6.

a) 237.0

b) 247.5

c) 257.0

d) 300.0

21. The following data summarizes the historical demand for a product

Determine the average forecast error when using the 4-month moving average method.

a) 5.25

b) 5.75

c) 6.25

d) 6.75

22. Use the table of data from problem 21 to answer this question.

Use a weighted moving average method with weights w1 = .2, w2 = .3 and w3 = .5 and determine the forecasted demand for September.

a) 33.5

b) 35.5

c) 37.5

d) 38.5

23. Robert wants to know if there is a relation between money spent on gambling and winnings:

If he spends $20, how much can he expect to win if he uses regression analysis?

a) 320

b) 370

c) 410

d) 450

24. __________ is an up-and-down repetitive movement within a trend occurring periodically.

Prediction

Seasonal pattern

Trend

Cycle

25. __________ attempt to develop a mathematical relationship between the item being forecast and factors that cause it to behave the way it does.

Qualitative methods

Regression

Time series

Quantitative methods

26. Consider the following graph of sales.

Which of the following characteristics is exhibited by the data?

a) Trend only

b) Trend plus seasonal

c) Trend plus random

d) Seasonal only

27. __________ is an averaging method that reacts more strongly to recent changes in demand.

a) Weighted moving average

b) Exponential smoothing

c) Adjusted exponential smoothing

d) Moving average

28. Given an actual demand of 59, a previous forecast of 64, and an alpha of .3, what would the forecast for the next period be using simple exponential smoothing?

a) 57.5

b) 60.5

c) 62.5

d) 65.6

29. Consider the following annual sales data for 1996-2003, use the linear regression method and determine the estimated sales equation,

NOTE: This question was taken from a test bank and the test publisher did not use the actual year as the x-value. You should replace 1996 with 1, 1997 with 2, 1998 with 3, and so on. These x-values will lead you to the correct answer. This technique is also commonly used in real world examples.

a) y = 2.63 + 0.21x

b) y = 2.63 - 0.21x

c) y = -0.21 + 2.63x

d) y = 0.21 - 2.63x

30. Consider the following annual sales data from problem 29. Again, please replace 1996 with 1, 1997 with 2, 1998 with 3, etc.

Using year values of 1 through 8 instead of 1996 through 2003 to represent the year, determine the percent of variation of sales that is caused by the year number (1-8). The answers below are rounded to the nearest tenth, but are far enough apart so your correct answer will be close to only one answer below.

a) 91.54%

b) 93.22%

c) 95.34%

d) 96.55%

#### Solution Summary

Multiple choice questions from time series analysis and regression analysis.