Deck 15: Time Series Analysis and Forecasting

Question 1

Trend in a time series must be linear.

Answer 1

False

Question 2

Qualitative forecasting techniques should be applied in situations where time series data exists, but where conditions are expected to change.

Answer 2

True

Question 3

With fewer periods in a moving average, it will take longer to adjust to a new level of data values.

Answer 3

False

Question 4

Smoothing methods are more appropriate for a stable time series than when significant trend or seasonal patterns are present.

Question 5

Exponential smoothing with α = .2 and a moving average with n = 5 put the same weight on the actual value for the current period.

Question 6

If a time series has a significant trend pattern, then one should not use a moving average to forecast.

Question 7

If the random variability in a time series is great and exponential smoothing is being used to forecast, then a high alpha (α) value should be used.

Question 8

A time series model with a seasonal pattern will always involve quarterly data.

Question 9

Time series data can exhibit seasonal patterns of less than one month in duration.

Question 10

All quarterly time series contain seasonality.

Question 11

A four-period moving average forecast for period 10 would be found by averaging the values from periods 10, 9, 8, and 7.

Question 12

​When using a moving average of order k to forecast, a small value for k is preferred if only the most recent values of the time series are considered relevant.

Question 13

An alpha (α) value of .2 will cause an exponential smoothing forecast to react more quickly to a sudden drop in demand than will an α equal to .4.

Question 14

Any recurring sequence of points above and below the trend line lasting less than one year can be attributed to the cyclical component of the time series.

Question 15

​In situations where you need to compare forecasting methods for different time periods, relative measures such as mean absolute error (MAE) are preferred.

Question 16

The exponential smoothing forecast for any period is a weighted average of all the previous actual values for the time series.

Question 17

The mean squared error is influenced much more by large forecast errors than is the mean absolute error.

Question 18

Time series methods base forecasts only on past values of the variables.

Question 19

Quantitative forecasting methods can be used when past information about the variable being forecast is unavailable.

Question 20

If the random variability in a time series is great, a high α value should be used to exponentially smooth out the fluctuations.

Question 21

In situations where you need to compare forecasting methods for different time periods, the most appropriate accuracy measure is

A) MSE
B) MAPE
C) MAE
D) ME

Question 22

Seasonal patterns

A) cannot be predicted.
B) are regular repeated patterns.
C) are multiyear runs of observations above or below the trend line.
D) reflect a shift in the time series over time.

Question 23

If data for a time series analysis is collected on an annual basis only, which pattern does not need to be considered?

A) trend
B) seasonal
C) cyclical
D) horizontal

Question 24

One measure of the accuracy of a forecasting model is the

A) smoothing constant
B) linear trend
C) mean absolute error
D) seasonal index

Question 25

Using a naive forecasting method, the forecast for next week's sales volume equals

A) the most recent week's sales volume
B) the most recent week's forecast
C) the average of the last four weeks' sales volumes
D) next week's production volume

Question 26

Which of the following exponential smoothing constant values puts the same weight on the most recent time series value as does a 5-period moving average?

A) α = .2
B) α = .25
C) α = .75
D) α = .8

Question 27

The trend pattern is easy to identify by using

A) a moving average
B) exponential smoothing
C) regression analysis
D) a weighted moving average

Question 28

Gradual shifting of a time series to relatively higher or lower values over a long period of time is called

A) periodicity.
B) cycles.
C) seasonality.
D) trend.

Question 29

?Whenever a categorical variable such as season has k levels, the number of dummy variables required

A) ?k - 1
B) ?k
C) ?k + 1
D) ?2k

Question 30

All of the following are true about a cyclical pattern except

A) It is often due to multiyear business cycles.
B) It is often combined with long-term trend patterns and called trend-cycle patterns.
C) It usually is easier to forecast than a seasonal pattern due to less variability.
D) It is an alternating sequence of data points above and below the trend line.

Question 31

All of the following are true about time series methods except

A) They discover a pattern in historical data and project it into the future.
B) They involve the use of expert judgment to develop forecasts.
C) They assume that the pattern of the past will continue into the future.
D) Their forecasts are based solely on past values of the variable or past forecast errors.

Question 32

All of the following are true about qualitative forecasting methods except

A) They generally involve the use of expert judgment to develop forecasts.
B) They assume the pattern of the past will continue into the future.
C) They are appropriate when past data on the variable being forecast are not applicable.
D) They are appropriate when past data on the variable being forecast are not available.

Question 33

The forecasting method that is appropriate when the time series has no significant trend, cyclical, or seasonal pattern is

A) moving average
B) mean squared error
C) mean average error
D) qualitative forecasting

Question 34

The focus of smoothing methods is to smooth out

A) the random fluctuations.
B) wide seasonal variations.
C) significant trend effects.
D) long range forecasts.

Question 35

Linear trend is calculated as . The trend projection for period 15 is

A) 11.25
B) 28.50
C) 39.75
D) 44.25

Question 36

Using exponential smoothing, the demand forecast for time period 10 equals the demand forecast for time period 9 plus

A) α times (the demand forecast for time period 8)
B) α times (the error in the demand forecast for time period 9)
C) α times (the observed demand in time period 9)
D) α times (the demand forecast for time period 9)

Question 37

Forecast errors

A) are the difference in successive values of a time series
B) are the differences between actual and forecast values
C) should all be nonnegative
D) should be summed to judge the goodness of a forecasting model

Question 38

All of the following are true about a stationary time series except

A) Its statistical properties are independent of time.
B) A plot of the series will always exhibit a horizontal pattern.
C) The process generating the data has a constant mean
D) There is no variability in the time series over time.

Question 39

To select a value for α for exponential smoothing

A) use a small α when the series varies substantially.
B) use a large α when the series has little random variability.
C) use a value between 0 and 1
D) All of the alternatives are true.

Question 40

Which of the following forecasting methods puts the least weight on the most recent time series value?

A) exponential smoothing with α = .3
B) exponential smoothing with α = .2
C) moving average using the most recent 4 periods
D) moving average using the most recent 3 periods

Question 41

Monthly sales at a coffee shop have been analyzed. The seasonal index values are and the trend line is 74123 + 26.9(t). Assume there is no cyclical component and forecast sales for year 8 (months 97 - 108).

Question 42

The number of plumbing repair jobs performed by Auger's Plumbing Service in each of the last nine months are listed below. ​
a.Assuming a linear trend function, forecast the number of repair jobs Auger's will perform in December using the least squares method.
b.What is your forecast for December using a three-period weighted moving average with weights of .6, .3, and .1? How does it compare with your forecast from part (a)?

Question 43

A trend line for the weekly attendance at a restaurant's Sunday brunch is given by
​ ​
How many guests would you expect in week 20?

Question 44

A hospital records the number of floral deliveries its patients receive each day. For a two-week period, the records show
15, 27, 26, 24, 18, 21, 26, 19, 15, 28, 25, 26, 17, 23
Use exponential smoothing with a smoothing constant of .4 to forecast the number of deliveries.

Question 45

Business at Terry's Tie Shop can be viewed as falling into three distinct seasons: (1) Christmas (November-December); (2) Father's Day (late May - mid-June); and (3) all other times. Average weekly sales (in $'s) during each of these three seasons during the past four years has been as follows: ​
Determine a forecast for the average weekly sales in years 5 and 6 for each of the three seasons.

Question 46

The number of properties newly listed with a real estate agency in each quarter over the last four years is given below. Assume the time series has seasonality without trend.
​​ ​
a. Develop the optimization model that finds the estimated regression equation that minimize the sum of squared error.
b. Solve for the estimated regression equation.
c. Forecast the four quarters of Year 5.

Question 47

The average SAT verbal score for students from one high school over the last ten exams is
​
508, 490, 502, 505, 493, 506, 492, 490, 503, 501
​
Do the scores support an increasing or a decreasing trend?

Question 48

The number of new contributors to a public radio station's annual fund drive over the last ten years is
​
63, 58, 61, 72, 98, 103, 121, 147, 163, 198
​
Develop a trend equation for this information, and use it to predict next year's number of new contributors.

Question 49

How can error measures be used to determine the number of periods to use in a moving average? What are you
assuming about the future when you make this choice?​

Question 50

A 24-hour coffee/donut shop makes donuts every eight hours. The manager must forecast donut demand so that the bakers have the fresh ingredients they need. Listed below is the actual number of glazed donuts (in dozens) sold in each of the preceding 13 eight-hour shifts. ​
a. Develop the optimization model that finds the estimated regression equation that minimize the sum of squared error.
b. Solve for the estimated regression equation.
c. Forecast the demand for glazed donuts for the Day, Evening, and Night shifts of June 8.

Question 51

A customer comment phone line is staffed from 8:00
a.Develop the optimization model that finds the estimated regression equation that minimize the sum of squared error.
a.m. to 4:30 p.m. five days a week. Records are available that show the number of calls received every day for the last five weeks. ​
b.Solve for the estimated regression equation.
c.Forecast the five days of week 6.

Question 52

The number of girls who attend a summer basketball camp has been recorded for the seven years the camp has been offered. Use exponential smoothing with a smoothing constant of .8 to forecast attendance for the eighth year.
47, 68, 65, 92, 98, 121, 146

Question 53

Sales (in thousands) of the new Thorton Model 506 convection oven over the eight-week period since its introduction have been as follows: ​
a.
Which exponential smoothing model provides better forecasts, one using α = .6 or α = .2? Compare them using mean squared error.
b.
Using the two forecast models in part (a), what are the forecasts for week 9?

Question 54

Quarterly billing for water usage is shown below.
​ ​
a.
Solve for the forecast equation that minimizes the sum of squared error.
b.
Forecast the summer of year 5 and spring of year 6.

Question 55

Explain what conditions make quantitative forecasting methods appropriate.​

Question 56

The number of cans of soft drinks sold in a machine each week is recorded below. Develop forecasts using a three-period moving average.
338, 219, 278, 265, 314, 323, 299, 259, 287, 302

Question 57

The number of pizzas ordered on Friday evenings between 5:30 and 6:30 at a pizza delivery location for the last 10 weeks is shown below. Use exponential smoothing with smoothing constants of .2 and .8 to forecast a value for week 11. Compare your forecasts using MSE. Which smoothing constant would you prefer?
58, 46, 55, 39, 42, 63, 54, 55, 61, 52

Question 58

What is a stable time series, and what forecasting methods are appropriate for one?​

Question 59

Use a four-period moving average to forecast attendance at baseball games. Historical records show
5346, 7812, 6513, 5783, 5982, 6519, 6283, 5577, 6712, 7345

Question 60

Quarterly revenues (in $1,000,000's) for a national restaurant chain for a five-year period were as follows: ​
a.Solve for the forecast equation that minimizes the sum of squared error.
b.Forecast the four quarters of year 6.

Question 61

Describe a time series plot and discuss its purpose and when in the forecasting process it should be constructed.​

Question 62

Explain and contrast three measures of forecast accuracy.​

Question 63

Discuss the effects of using a small smoothing constant value and when it is most appropriate to use. Then, do the
same for a large smoothing constant value.​