Deck 7: Forecasting

Question 1

All four measures of forecast error, MSE, MAD, MAPE, and LAD,
consider the sum of forecast errors in their calculations.

Answer 1

False

Question 2

In the multiple regression approach to forecasting models with trend and seasonal effects, there are as many dummy variables required as there are seasons.

Answer 2

False

Question 3

Time series analysis:

A)attempts to use historic values to forecast future values.
B)does not involve regression analysis.
C)eliminates autocorrelation.
D)assumes random variation is zero.

Answer 3

A

Question 4

If positive autocorrelation exists, the exponential smoothing constant should be close to zero to track changes in the time series mean.

Question 5

If a time series is believed to exhibit non-linear trend, one should use Holt's exponential smoothing technique on the original time series data.

Question 6

If one uses a stationary linear forecasting model, the forecast for period t + 1 will not necessarily be the same as the forecast for period t + 2.

Question 7

In exponential smoothing, if the smoothing constant, alpha, is 1, you will get the same forecast as obtainable using the last period technique.

Question 8

For a moving average, the more past data used, the better.

Question 9

The "weights" in the weighted moving average method are unequal and typically decrease with the age of the observation.

Question 10

Autocorrelation measures only how the value in one time period
affects the value in the next time period.

Question 11

A business experiencing stationary demand does not need forecasting.

Question 12

The "weights" in the weighted moving average need not:

A)be non-negative.
B)sum to 1.
C)give the most recent value the least weight.
D)all be unequal.

Question 13

In a stationary forecasting model, the value of the time series for a specific period equals the unchanging mean value of the time series plus a random error term for that period.

Question 14

In exponential smoothing, the initial forecast must be derived by some other method.

Question 15

In exponential smoothing, if the smoothing constant, alpha, is 0, the forecast will never change.

Question 16

Multiple regression can be used for models built on multiple time series.

Question 17

A stationary forecasting model is appropriate for a time series which exhibits primarily:

A)trend.
B)cyclical influences.
C)seasonal components.
D)random variation.

Question 18

If the value of a variable at time t + 1 is partly determined by its value at time t, this is called:

A)collinearity.
B)time series.
C)autocorrelation.
D)covariance.

Question 19

Linear trend forecasting models cannot be applied to a time series with nonlinear trend.

Question 20

Suppose that sales of a certain item for the months of January through April were as follows: January - 50, February - 80, March -
70, and April - 60.Using a three month simple moving average, the
Forecast for May would be:

A)60.
B)65.
C)70.
D)80.

Question 21

What are the three steps in the time series forecasting process?

Question 22

In January, Phil Johnston's newspaper route added two customers who used to subscribe to the evening paper.In February, Phil lost a customer who decided to get his news off the internet.This is an example of:

A)long term trend.
B)seasonal variation.
C)cyclical variation.
D)random effects.

Question 23

In situations where forecast errors are to be weighed in proportion to their magnitude, the preferred performance evaluator would most likely be:

A)MSE.
B)MAD.
C)MAPE.
D)LAD.

Question 24

What is not involved in the initial form hypothesis step of the time series forecasting process?

A)Graphing.
B)Statistical verification of the hypothesis.
C)Calculating the value of parameters.
D)Gathering data.

Question 25

How can cyclical components of a time series be identified?

A)Autocorrelation test.
B)Graphically.
C)Linear regression.
D)Cyclical effects cannot be detected.

Question 26

Which of the following is a qualitative technique in which a forecast is selected based on the likelihood of the assumptions used?

A)Scenario writing.
B)Delphi technique.
C)Multiple regression.
D)Box-Jenkins method.

Question 27

In the exponential smoothing (ES) technique, the value of alpha, the smoothing constant:

A)may assume any non-negative value.
B)determines the forecasting model's responsiveness to abrupt changes.
C)typically is at the higher end in the range of possible values.
D)is preset by the analyst and not subject to validity testing.

Question 28

One of the measures for evaluating forecast errors is the Mean Squared Error (MSE), in which differences between forecasted and actual values are squared.Why is this a desirable trait?

Question 29

Given below are the monthly actual sales of Wangdoodles for December of one year and the first six months of the following year.Also given are three sets of forecast numbers:F(1): the last period technique.
F(2): a three-month weighted moving average, with weights of: 50%
for the most recent month; 35% for the previous month; and 15%
for the month before that.
F(3): an exponentially smoothed average with $\alpha$ = 0.20.
$\begin{array}{lcccc}\text { Month}&\text { Actual } & F(1) & F(2) & F(3)\\\text { Dec } & 251\\\text { Jan } & 255 & 251 & 259 & 260 \\\text { Feb } & 279 & 255 & 257 & 259 \\\text { Mar } & 267 & 279 & 262 & 262 \\\text { Apr } & 287 & 267 & 267 & 263 \\\text { May } & 263 & 287 & 278 & 267 \\\text { Jun } & 270 & 263 & 272 & 266\end{array}$

A.Fill in July's forecasted sales, using each of the three forecasting techniques.
B.Which of the three forecasting methods do you prefer? Why?

Question 30

For a month following a presidential illness, very few homes were sold.Afterwards, the realty business returned to normal levels.This is an example of:

A)long term trend.
B)seasonal variation.
C)cyclical variation.
D)random effects.

Question 31

Selecting a forecasting technique for which the largest absolute deviation is minimized is similar to which decision analysis approach?

A)Maximin.
B)Minimax.
C)Minimax regret.
D)Maximax.

Question 32

June forecast: 71.June actual: 68.Alpha = 1.0.July's exponentially smoothed forecast is:

A)68.
B)71.
C)70.7.
D)68.3.

Question 33

Holt's linear exponential smoothing technique for forecasting time series with trend:

A)results in separate forecasts for level (L) and trend (T).
B)is relevant only for non-linear trend cases.
C)gives equal weight to all data points employed.
D)requires the retention of a large number of data points.

Question 34

Phil Johnston rides his bicycle to deliver newspapers to his neighborhood.Some customers take weekend trips and put their news delivery on hold.This is an example of:

A)long term trend.
B)seasonal variation.
C)cyclical variation.
D)random effects.

Question 35

When a stationary model is used, the forecast for the next time period is also the forecast for all future time periods.If the model is accurate, what could cause future forecasts to change?

Question 36

If it is suspected that the major influence in a stationary time series is random variation, the preferable forecasting technique would be the:

A)classical decomposition.
B)moving average method.
C)Holt's linear exponential smoothing technique.
D)linear regression.

Question 37

Phil Johnston's newspaper route includes a new housing development.As families move in, his business increases.This is an example of:

A)long term trend.
B)seasonal variation.
C)cyclical variation.
D)random effects.

Question 38

RDN's sales of cable modem in San Mateo, California, for the months of January through April were as follows: January - 50, February - 80, March - 70, and April - 60.Suppose exponential smoothing is used with a smoothing constant, alpha, of .20.If the forecast for January was 50, the forecast for May would be approximately:

A)58.
B)59.
C)60.
D)63.

Question 39

As the smoothing constant, alpha, is reduced:

A)the forecasts are more sensitive to trend influences.
B)the weights given to prior periods' data become more uniform.
C)cyclical/seasonal factors are more easily discernible.
D)the computational complexity of forecasting increases.

Question 40

How do you use the p-value and the significance (or confidence) level to check for trend in a time series?

Question 41

What are the advantages of the Last Period technique for a stationary time series?

Question 42

Define classical decomposition.

Question 43

Identify four key issues in the selection of a forecasting technique for a stationary time series.

Question 44

What is the Box-Jenkins method?

Question 45

Below is a chart of potholes repaired in Sunnyside Township. $\begin{array}{ccc}\text{Year}&\text{Potholes}&\text{Year}&\text{Potholes}\\1990 & 27 & 1996 & 35 \\1991 & 29 & 1997 & 37 \\1992 & 35 & 1998 & 39 \\1993 & 28 & 1999 & 38 \\1994 & 32 & 2000 & 41 \\1995 & 37 & 2001 & 44\end{array}$
A.Using a three period weighted moving average with weights of .5, .3, and .2, compute what would have been forecast for 1993-2002.
B.Compute MSE, MAD, MAPE, and LAD.

Question 46

What value of $\alpha$ makes exponential smoothing equivalent to a moving average based on 4 periods of data?

Question 47

Consider the following time series representing home satellite dish installations by Big Boys Appliances over the past twelve months: $\begin{array}{lccccc}\text { Month }&\text { Installations }&\text { Month }&\text { Installations }&\text { Month }&\text { Installations }\\\text { January } & 14 & \text { May } & 22 & \text { Sept. } & 38 \\\text { February } & 19 & \text { June } & 29 & \text { October } & 30 \\\text { March } & 22 & \text { July } & 33 & \text { November } & 29 \\\text { April } & 25 & \text { August } & 35 & \text { December } & 42\end{array}$

A.Using linear regression, determine the forecast for the upcoming six months.
B.Using Holt's method, determine the forecast for the upcoming six months.Assume that a smoothing constant of .40 is used for the time series level and a smoothing constant of .20 is used for the
time series trend.
C..Which technique, linear regression or Holt's using the smoothing constants given in part B, gives the lower mean squared error?
D.Why should the result you found in part C not surprise you?

Question 48

What parameters does the modeler have to select for a moving average, a weighted moving average, and exponential smoothing?

Question 49

Below is a record of the number of individuals signed up by the Army recruiting office in the Hyde Park section of Chicago. $$\begin{array} { l l l l l l } \text { January } & 1 & \text { May } & 17 & \text { September } & 13 \\\text { February } & 12 & \text { June } & 16 & \text { Ortaber } & 16 \\\text { Marrh } & 15 & \text { July } & 21 & \text { November } & 12 \\\text { April } & 11 & \text { nugugt } & 7 & \text { Derember } & 11\end{array}$$ A.Using Excel's linear regression, forecast the expected total for the next two months and generate Excel's summary output.