Deck 10: Forecasting

Question 1

The mean square error is the square of the mean of the absolute deviations.

Answer 1

False

Question 2

If significant changes in conditions are occurring relatively frequently, then a smaller smoothing constant is needed.

Answer 2

False

Question 3

A moving-average forecast tends to be more responsive to changes in the time-series data when more values are included in the average.

Answer 3

False

Question 4

Once accepted by managers, forecasts should not be overridden.

Question 5

Exponential smoothing with trend was designed for time-series that have great variability both up and down.

Question 6

Forecasts are rarely perfect.

Question 7

The last-value forecasting method requires a linear trend line.

Question 8

The moving-average forecasting method assigns equal weights to each value that is represented by the average.

Question 9

A smoothing constant of 0.1 will cause an exponential smoothing forecast to react more quickly to a sudden change than a value of 0.3 will.

Question 10

The mean absolute deviation is the sum of the absolute value of forecasting errors divided by the number of forecasts.

Question 11

When no historical sales data is available, it is best to use statistical forecasting methods.

Question 12

The averaging method uses all the data points in the time-series.

Question 13

The difference between a forecast and what turns out to be the true value is called the mean absolute deviation.

Question 14

The mean absolute deviation is more sensitive to large deviations than the mean square error.

Question 15

Removing the seasonal component from a time-series can be accomplished by dividing each value by its appropriate seasonal factor.

Question 16

The seasonal factor for any period of a year measures how that period compares to the same period last year.

Question 17

The moving-average forecasting method is a very good one when conditions remain pretty much the same over the time period being considered.

Question 18

Exponential smoothing with trend requires selection of two smoothing constants.

Question 19

An advantage of the exponential smoothing forecasting method is that more recent experience is given more weight than less recent experience.

Question 20

The last-value forecasting method is most useful when conditions are stable over time.

Question 21

The Delphi method involves the use of a series of questionnaires to achieve a consensus forecast.

Question 22

Forecasting techniques such as moving-average, exponential smoothing, and the last-value method all represent averaged values of time-series data.

Question 23

If a time-series has exactly the same distribution for each and every time period, then the averaging forecasting method provides the best estimate of the mean.

Question 24

Judgmental forecasting methods have been developed to interpret statistical data.

Question 25

The sales force composite method is a top-down approach to forecasting.

Question 26

Causal forecasting obtains a forecast for a dependent variable by relating it directly to one or more independent variables.

Question 27

Linear regression can be used to approximate the relationship between independent and dependent variables.

Question 28

In business, forecasts are the basis for:

A) sales planning.
B) inventory planning.
C) production planning.
D) budgeting.
E) All of the answers choices are correct.

Question 29

A time-series is said to be smooth if its underlying probability distribution usually remains the same from one period to the next.

Question 30

Gradual, long-term movement in time-series values is called:

A) seasonal variation.
B) trend.
C) cycles.
D) irregular variation.
E) random variation.

Question 31

Using the latest value in a sequence of data to forecast the next period is:

A) a moving-average forecast.
B) a last-value forecast.
C) an exponentially smoothed forecast.
D) a causal forecast.
E) None of the answer choices is correct.

Question 32

Refer to the following data:
$$\begin{array} { | c | c | } \hline \text { Perind } & \text { Demand } \\\hline 1 & 58 \\\hline 2 & 59 \\\hline 3 & 60 \\\hline 4 & 61 \\\hline\end{array}$$
What is the moving-average forecast for the next period based on the last three periods?

A) 58
B) 62
C) 60
D) 61
E) None of the answer choices is correct.

Question 33

The goal of time-series forecasting methods is to estimate the mean of the underlying probability distribution of the next value of the time-series as closely as possible.

Question 34

Refer to the following data:
$$\begin{array} { | c | c | } \hline \text { Perind } & \text { Demand } \\\hline 1 & 58 \\\hline 2 & 59 \\\hline 3 & 60 \\\hline 4 & 61 \\\hline\end{array}$$
What is the last-value forecast for the next period?

A) 58
B) 62
C) 60
D) 61
E) None of the answer choices is correct.

Question 35

When statistical forecasting methods are used, it is no longer necessary to use judgmental methods as well.

Question 36

Time-series data may exhibit which of the following behaviors?

A) Trend
B) Seasonality
C) Cycles
D) Irregularities
E) All of the answers choices are correct

Question 37

Forecasts can help a manager to:

A) anticipate the future.
B) develop strategies.
C) make staffing decisions.
D) All of the answers choices are correct.
E) None of the answer choices is correct.

Question 38

Which of the following are costs of an inaccurate forecast?

A) Lost sales
B) Inventory
C) An understaffed office
D) Lower profits
E) All of the answers choices are correct.

Question 39

In exponential smoothing, an α of 0.3 will cause a forecast to react more quickly to a large error than will an α of 0.2.

Question 40

The last-value forecasting method:

A) is quick and easy to prepare.
B) is easy for users to understand.
C) ignores all values except one.
D) All of the answers choices are correct.
E) None of the answer choices is correct.

Question 41

Given the following historical data, what is the moving-average forecast for period 6 based on the last three periods?
$$\begin{array} { | c | c | } \hline \text { Periud } & \text { Value } \\\hline 1 & 73 \\\hline 2 & 68 \\\hline 3 & 65 \\\hline 4 & 72 \\\hline 5 & 67 \\\hline\end{array}$$

A) 67
B) 68
C) 69
D) 100
E) 115

Question 42

The business analyst for Ace Business Machines, Inc. wants to forecast this year's demand for manual typewriters based on the following historical data:
$$\begin{array} { | c | c | } \hline \text { Time Periad } & \text { Demand } \\\hline 5 \text { years ago } & 900 \\\hline 4 \text { years ago } & 700 \\\hline 3 \text { years ago } & 600 \\\hline 2 \text { years ago } & 500 \\\hline \text { Last year } & 300 \\\hline\end{array}$$
What is the forecast for this year using a moving-average forecast based on the last three years?

A) 163
B) 180
C) 300
D) 467
E) 510

Question 43

In order to increase the responsiveness of a forecast made using the moving-average method, the number of values in the average should be:

A) decreased.
B) increased.
C) multiplied by a larger α.
D) multiplied by a smaller α.
E) None of the answer choices is correct.

Question 44

Given forecast errors of 5, 0, −4, and 3, what is the mean absolute deviation?

A) 1
B) 2
C) 2.5
D) 3
E) 12

Question 45

Given the following historical data, what is the moving-average forecast for period 6 based on the last three periods?
$$\begin{array} { | c | c | } \hline \text { Periud } & \text { Value } \\\hline 1 & 19 \\\hline 2 & 20 \\\hline 3 & 18 \\\hline 4 & 19 \\\hline 5 & 17 \\\hline\end{array}$$

A) 17
B) 18
C) 19
D) 20
E) 18.5

Question 46

Given an actual latest demand of 59, a previous forecast of 64, and α = 0.3, what would be the forecast for the next period using the exponential smoothing method?

A) 36.9
B) 57.5
C) 60.5
D) 62.5
E) 65.5

Question 47

The president of State University wants to forecast student enrollment for this academic year based on the following historical data:
$$\begin{array} { | c | c | } \hline \text { Year } & \text { Enrollnents } \\\hline 5 \text { years ago } & 15,000 \\\hline 4 \text { years ago } & 16,000 \\\hline 3 \text { years ago } & 18,000 \\\hline \text { 2 years ago } & 20,000 \\\hline \text { Luast year } & 21,000 \\\hline\end{array}$$
What is the forecast for this year using a moving-average forecast based on the last four years?

A) 18,750
B) 19,500
C) 21,000
D) 22,650
E) 22,800

Question 48

In exponential smoothing with trend, the forecast consists of:

A) an exponentially smoothed forecast and a smoothed trend factor.
B) the old forecast adjusted by a trend factor.
C) the old forecast and a smoothed trend factor.
D) a moving-average and a trend factor.
E) None of the answer choices is correct.

Question 49

Given forecast errors of 4, 8, and −3, what is the mean square error?

A) 5
B) 9
C) 25
D) 29.67
E) 89

Question 50

Given an actual latest demand of 105, a previous forecast of 97, and α = 0.4, what would be the forecast for the next period using the exponential smoothing method?

A) 80.8
B) 93.8
C) 100.2
D) 101.8
E) 108.2

Question 51

Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a last-value forecast?

A) 0
B) 0.01
C) 0.1
D) 0.5
E) 1

Question 52

The mean absolute deviation is used to:

A) estimate the trend line.
B) eliminate forecast errors.
C) measure forecast accuracy.
D) seasonally adjust the forecast.
E) All of the answers choices are correct.

Question 53

The president of State University wants to forecast student enrollment for this academic year based on the following historical data:
$$\begin{array} { | c | c | } \hline \text { Year } & \text { Enrollnents } \\\hline 5 \text { years ago } & 15,000 \\\hline 4 \text { years ago } & 16,000 \\\hline 3 \text { years ago } & 18,000 \\\hline \text { 2 years ago } & 20,000 \\\hline \text { Luast year } & 21,000 \\\hline\end{array}$$
What is the forecast for this year using exponential smoothing with trend if ? = 0.5 and ? = 0.3? Assume the forecast for last year was 21,000 and the forecast for two years ago was 19,000, and that the trend estimate for last year's forecast was 1,500.

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

Question 54

Which of the following possible values of α would cause exponential smoothing to respond the most quickly to forecast errors?

A) 0
B) 0.01
C) 0.05
D) 0.1
E) 0.15

Question 55

The business analyst for Ace Business Machines, Inc. wants to forecast this year's demand for manual typewriters based on the following historical data:
$$\begin{array} { | c | c | } \hline \text { Time Periad } & \text { Demand } \\\hline 5 \text { years ago } & 900 \\\hline 4 \text { years ago } & 700 \\\hline 3 \text { years ago } & 600 \\\hline 2 \text { years ago } & 500 \\\hline \text { Last year } & 300 \\\hline\end{array}$$
What is the forecast for this year using the last-value forecasting method?

A) 163
B) 180
C) 300
D) 467
E) 510

Question 56

Given forecast errors of 4, 8, and −3, what is the mean absolute deviation?

A) 3
B) 4
C) 5
D) 6
E) 9

Question 57

The president of State University wants to forecast student enrollment for this academic year based on the following historical data:
$$\begin{array} { | c | c | } \hline \text { Year } & \text { Enrollnents } \\\hline 5 \text { years ago } & 15,000 \\\hline 4 \text { years ago } & 16,000 \\\hline 3 \text { years ago } & 18,000 \\\hline \text { 2 years ago } & 20,000 \\\hline \text { Luast year } & 21,000 \\\hline\end{array}$$
What is the forecast for this year using exponential smoothing with ? = 0.5, if the forecast for two years ago was 16,000?

A) 18,750
B) 19,500
C) 21,000
D) 22,650
E) 22,800

Question 58

Given forecast errors of −5, -10, and 15, what is the mean absolute deviation?

A) 0
B) 5
C) 10
D) 30
E) None of the answer choices is correct.

Question 59

The president of State University wants to forecast student enrollment for this academic year based on the following historical data:
$$\begin{array} { | c | c | } \hline \text { Year } & \text { Enrollnents } \\\hline 5 \text { years ago } & 15,000 \\\hline 4 \text { years ago } & 16,000 \\\hline 3 \text { years ago } & 18,000 \\\hline \text { 2 years ago } & 20,000 \\\hline \text { Luast year } & 21,000 \\\hline\end{array}$$
What is the forecast for this year using the last-value forecasting method?

A) 18,750
B) 19,500
C) 21,000
D) 22,650
E) 22,800

Question 60

Given forecast errors of 5, 0, −4, and 3, what is the mean square error?

A) 3
B) 4
C) 12
D) 12.5
E) 50

Question 61

Professor Z needs to allocate time among several tasks next week to include time for students' appointments. Thus, he needs to forecast the number of students who will seek appointments. He has gathered the following data:
$$\begin{array} { | c | c | } \hline \text { Week } & { \text { \# of students } } \\\hline 6 \text { weeks ago } & 85 \\\hline 5 \text { weeks ago } & 110 \\\hline 4 \text { weeks ago } & 95 \\\hline 3 \text { weeks ago } & 80 \\\hline 2 \text { weeks ago } & 65 \\\hline \text { Last week } & 50 \\\hline\end{array}$$
What is the forecast for this year using exponential smoothing with ? = 0.2, if the forecast for two weeks ago was 90?

A) 49
B) 50
C) 52
D) 65
E) 78

Question 62

The forecasting method which uses anonymous questionnaires to achieve a consensus forecast is:

A) sales force composites.
B) consumer surveys.
C) the Delphi method.
D) time-series analysis.
E) executive opinions.

Question 63

Which of the following would be considered a possible drawback of using executive opinions to develop a forecast?

A) It is difficult to interpret the results.
B) Responsibility is diffused for the forecast.
C) Extensive use of computers is needed.
D) It brings together the knowledge of top managers.
E) Forecasters are sometimes overly influenced by recent events.

Question 64

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

A) Managerial opinion
B) Sales force composite
C) Time-series analysis
D) The Delphi method
E) Consumer market survey

Question 65

An operation analyst is forecasting this year's demand for one of his company's products based on the following historical data:
$$\begin{array} { | c | c | } \hline \text { Year } & \text { \# Sald } \\\hline 4 \text { years ago } & 10,000 \\\hline 3 \text { years ago } & 12,000 \\\hline \text { 2 years ago } & 18,000 \\\hline \text { Last year } & 20,000 \\\hline\end{array}$$
What is the forecast for this year using the last-value forecasting method?

A) 22,000
B) 20,000
C) 18,000
D) 15,000
E) 12,000

Question 66

Professor Z needs to allocate time among several tasks next week to include time for students' appointments. Thus, he needs to forecast the number of students who will seek appointments. He has gathered the following data:
$$\begin{array} { | c | c | } \hline \text { Week } & { \text { \# of students } } \\\hline 6 \text { weeks ago } & 85 \\\hline 5 \text { weeks ago } & 110 \\\hline 4 \text { weeks ago } & 95 \\\hline 3 \text { weeks ago } & 80 \\\hline 2 \text { weeks ago } & 65 \\\hline \text { Last week } & 50 \\\hline\end{array}$$
What is the forecast for this year using the last-value forecasting method?

A) 49
B) 50
C) 52
D) 65
E) 78

Question 67

A manager uses the equation y = 40,000 + 150x to predict monthly receipts. What is the forecast for July if x = 0 in April?

A) 40,450
B) 40,600
C) 42,100
D) 42,250
E) 42,400

Question 68

An operation analyst is forecasting this year's demand for one of his company's products based on the following historical data:
$$\begin{array} { | c | c | } \hline \text { Year } & \text { \# Sald } \\\hline 4 \text { years ago } & 10,000 \\\hline 3 \text { years ago } & 12,000 \\\hline \text { 2 years ago } & 18,000 \\\hline \text { Last year } & 20,000 \\\hline\end{array}$$
What is the forecast for this year using exponential smoothing with ? = 0.2, if the forecast for last year was 15,000?

A) 20,000
B) 19,000
C) 17,500
D) 16,000
E) 15,000

Question 69

The following table shows the quarterly sales of widgets over the past two years. Calculate the seasonal factor for Quarter 2.
$$\begin{array} {| l | r |} \hline{ \text { Quarter } } & \text { Sules } \\\hline \text { Q1 last year } & 10,000 \\\hline\text { Q2 last year } & 11,000 \\\hline \text { Q3 last year } & 7,500 \\\hline \text { Q4 last year } & 8 , 0 0 0 \\\hline \text { Q1 this year } & 15,000 \\\hline\text { Q2 this year } & 17,000 \\\hline \text { Q3 this year } & 10,500 \\\hline \text { Q4 this year } & 11,500\\\hline\end{array}$$

A) 0.74
B) 0.99
C) 1.14
D) 1.24
E) 1.29

Question 70

The primary method for causal forecasting is:

A) sensitivity analysis.
B) linear regression.
C) moving-average.
D) exponential smoothing.
E) the Delphi method.

Question 71

Professor Z needs to allocate time among several tasks next week to include time for students' appointments. Thus, he needs to forecast the number of students who will seek appointments. He has gathered the following data:
$$\begin{array} { | c | c | } \hline \text { Week } & { \text { \# of students } } \\\hline 6 \text { weeks ago } & 85 \\\hline 5 \text { weeks ago } & 110 \\\hline 4 \text { weeks ago } & 95 \\\hline 3 \text { weeks ago } & 80 \\\hline 2 \text { weeks ago } & 65 \\\hline \text { Last week } & 50 \\\hline\end{array}$$
What is the forecast for this year using a moving-average forecast based on the last three weeks?

A) 49
B) 50
C) 52
D) 65
E) 78

Question 72

Which of the following would be an advantage of using a sales force composite to develop a demand forecast?

A) The sales staff is least affected by changing customer needs.
B) The sales force can easily distinguish between customer desires and probable actions.
C) The sales staff is often aware of customer's future plans.
D) Salespeople are least likely to be biased by sales quotas.
E) None of the answer choices is correct.

Question 73

An operation analyst is forecasting this year's demand for one of his company's products based on the following historical data:
$$\begin{array} { | c | c | } \hline \text { Year } & \text { \# Sald } \\\hline 4 \text { years ago } & 10,000 \\\hline 3 \text { years ago } & 12,000 \\\hline \text { 2 years ago } & 18,000 \\\hline \text { Last year } & 20,000 \\\hline\end{array}$$
What is the forecast for this year using a moving-average forecast based on the last four years?

A) 22,000
B) 20,000
C) 18,000
D) 15,000
E) 12,000

Question 74

Professor Z needs to allocate time among several tasks next week to include time for students' appointments. Thus, he needs to forecast the number of students who will seek appointments. He has gathered the following data:
$$\begin{array} { | c | c | } \hline \text { Week } & { \text { \# of students } } \\\hline 6 \text { weeks ago } & 85 \\\hline 5 \text { weeks ago } & 110 \\\hline 4 \text { weeks ago } & 95 \\\hline 3 \text { weeks ago } & 80 \\\hline 2 \text { weeks ago } & 65 \\\hline \text { Last week } & 50 \\\hline\end{array}$$
What is the forecast for this week using exponential smoothing with trend if ? = 0.5 and ? = 0.1? Assume the forecast for last week was 65 and the forecast for two weeks ago was 75, and that the trend estimate for last week's forecast was ?5.

A) 49
B) 50
C) 52
D) 65
E) 78

Question 75

The business analyst for Ace Business Machines, Inc. wants to forecast this year's demand for manual typewriters based on the following historical data:
$$\begin{array} { | c | c | } \hline \text { Time Periad } & \text { Demand } \\\hline 5 \text { years ago } & 900 \\\hline 4 \text { years ago } & 700 \\\hline 3 \text { years ago } & 600 \\\hline 2 \text { years ago } & 500 \\\hline \text { Last year } & 300 \\\hline\end{array}$$
What is the forecast for this year using exponential smoothing with ? = 0.4, if the forecast for two years ago was 750?

A) 163
B) 180
C) 300
D) 467
E) 510

Question 76

An operation analyst is forecasting this year's demand for one of his company's products based on the following historical data:
$$\begin{array} { | c | c | } \hline \text { Year } & \text { \# Sald } \\\hline 4 \text { years ago } & 10,000 \\\hline 3 \text { years ago } & 12,000 \\\hline \text { 2 years ago } & 18,000 \\\hline \text { Last year } & 20,000 \\\hline\end{array}$$
The previous trend line has predicted 18,500 for two years ago, and 19,700 for last year. What was the mean absolute deviation for these forecasts?

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

Question 77

The equation y = 350 − 2.5x is used to predict quarterly demand where x = 0 in the second quarter of last year. Quarterly seasonal factors are Q1 = 1.5, Q2 = 0.8, Q3 = 1.1, and Q4 = 0.6. What is the forecast for the last quarter of this year?

A) 199.5
B) 201
C) 266
D) 268
E) 335