Deck 18: Forecasting

Question 1

In the simple exponential smoothing forecasting model, you need at least 30 observations to set the smoothing constant alpha.

Answer 1

False

Question 2

Exponential smoothing forecasts always lag behind the actual occurrence but can be corrected somewhat with a trend adjustment.

Answer 2

True

Question 3

Time series forecasting models make predictions about the future based on analysis of past data.

Answer 3

True

Question 4

Simple exponential smoothing lags changes in demand.

Question 5

Exponential smoothing is always the best and most accurate of all forecasting models.

Question 6

Cyclical influences on demand are often expressed graphically as a linear function that is either upward or downward sloping.

Question 7

Cyclical influences on demand may come from occurrences such as political elections, war, or economic conditions.

Question 8

The value of the smoothing constant alpha in an exponential smoothing model is between 0 and 1.

Question 9

Bayesian analysis is the simplest way to choose weights for the weighted moving average forecasting model.

Question 10

Experience and trial and error are the simplest ways to choose weights for the weighted moving average forecasting model.

Question 11

In the weighted moving average forecasting model, the weights must add up to one times the number of data points.

Question 12

The weighted moving average forecasting model uses a weighting scheme to modify the effects of individual data points. This is its major advantage over the simple moving average model.

Question 13

A central premise of exponential smoothing is that more recent data are less indicative of the future than data from the distant past.

Question 14

Because the factors governing demand for products are very complex, all forecasts of demand contain error.

Question 15

In exponential smoothing, it is desirable to use a higher smoothing constant when forecasting demand for a product experiencing high growth.

Question 16

In a forecasting model using simple exponential smoothing, the data pattern should remain stationary.

Question 17

The equation for exponential smoothing states that the new forecast is equal to the old forecast plus the error of the old forecast.

Question 18

In a forecasting model using simple moving average, the shorter the time span used for calculating the moving average, the closer the average follows volatile trends.

Question 19

Trend lines are usually the last things considered when developing a forecast.

Question 20

Random errors can be defined as those that cannot be explained by the forecast model being used.

Question 21

Market research is a quantitative method of forecasting.

Question 22

It is difficult to identify the trend in time series data.

Question 23

Linear regression is not useful for aggregate planning.

Question 24

Decomposition of a time series means identifying and separating the time series data into its components.

Question 25

A time series is defined in the text as chronologically ordered data that may contain one or more components of demand variation: trend, seasonal, cyclical, autocorrelation, and random.

Question 26

In forecasting, RSFE stands for "running sum of forecast errors."

Question 27

There are no differences in strategic and tactical forecasting. A forecast is a mathematical projection, and its ultimate purpose should make no difference to the analyst.

Question 28

A tracking signal (TS) can be calculated using the arithmetic sum of forecast deviations divided by the MAD.

Question 29

Qualitative forecasting techniques generally take advantage of the knowledge of experts and therefore do not require much judgment.

Question 30

Multiple regression analysis uses several regression models to generate a forecast.

Question 31

MAD statistics can be used to generate tracking signals.

Question 32

A restriction in using linear regression is that it assumes that past data and future projections fall on or near a straight line.

Question 33

When forecast errors occur in a normally distributed pattern, the ratio of the mean absolute deviation to the standard deviation is 2 to 1, or 2 × MAD = 1 standard deviation.

Question 34

For every forecasting problem, there is one best forecasting technique.

Question 35

RSFE in forecasting stands for "reliable safety function error."

Question 36

A good forecaster is one who develops special skills and experience at one forecasting technique and is capable of applying it to widely diverse situations.

Question 37

The standard error of the estimate of a linear regression is not useful for judging the fit between the data and the regression line when doing forecasts.

Question 38

Random errors in forecasting occur when an undetected secular trend is not included in a forecasting model.

Question 39

In causal relationship forecasting, leading indicators are used to forecast occurrences.

Question 40

Regression is a functional relationship between two or more correlated variables, where one variable is used to predict another.

Question 41

A moving average can be useful for forecasting but it introduces random fluctuations into the forecast that must be dealt with.

Question 42

Exponential smoothing models are not very accurate.

Question 43

The greater the ability of a forecasting model to react quickly to changes in demand, the less accurate the forecast needs to be.

Question 44

There is one type of seasonal variation.

Question 45

With a simple moving average, the number of periods used has a major impact on its ability to smooth out fluctuation but does not have much impact on its forecasting ability.

Question 46

In time series data depicting demand, which of the following is not considered a component of demand variation?

A) Trend
B) Seasonal
C) Cyclical
D) Variance
E) Autocorrelation

Question 47

Exponential smoothing models require minimal data storage.

Question 48

Linear regression works both for time series and causal relationship forecasting.

Question 49

When average, trend, and seasonality are removed from the data, random variations are what remains.

Question 50

Forecast error is the same as residuals.

Question 51

CPFR stands for "collective planning, forecasting, and reordering."

Question 52

We usually associate the word "seasonal" with recurrent periods of repetitive activity that happen on other than an annual cycle.

Question 53

CPFR is an Internet tool to coordinate forecasting, production, and purchasing in a firm's supply chain.

Question 54

Time series analysis is based on the idea that data relating to past demand can be used to predict future demand.

Question 55

Exponential smoothing models require a great deal of computation.

Question 56

The goal of CPFR is to make sure suppliers know how much demand a firm is forecasting.

Question 57

Exponential smoothing with trend requires two different smoothing constants.

Question 58

Autocorrelation means that the value expected at any point is highly correlated with its future values.

Question 59

Exponential smoothing models can be very complex.

Question 60

In decomposition of time series data, it is relatively easy to identify cycles and autocorrelation components.

Question 61

In general, which forecasting time frame best identifies seasonal effects?

A) Short-term forecasts
B) Quick-time forecasts
C) Long-range forecasts
D) Medium-term forecasts
E) Rapid-change forecasts

Question 62

In most cases, demand for products or services can be broken into several components. Which of the following is considered a component of demand?

A) Forecast error
B) Autocorrelation
C) Previous demand
D) Consistent demand
E) Repeat demand

Question 63

In general, which forecasting time frame compensates most effectively for random variation and short-term changes?

A) Short-term forecasts
B) Quick-time forecasts
C) Long-range forecasts
D) Medium-term forecasts
E) Rapid-change forecasts

Question 64

Which of the following considerations is not a factor in deciding which forecasting model a firm should choose?

A) Time horizon to forecast
B) Product
C) Accuracy required
D) Data availability
E) Analyst availability

Question 65

In business forecasting, what is usually considered a medium-term time period?

A) Six weeks to one year
B) Three months to two years
C) One to five years
D) One to six months
E) Six months to six years

Question 66

In most cases, demand for products or services can be broken down into several components. Which of the following is not considered a component of demand?

A) Average demand for a period
B) A trend
C) Seasonal elements
D) Past data
E) Autocorrelation

Question 67

Which of the following forecasting methodologies is considered a time series forecasting technique?

A) Simple moving average
B) Market research
C) Leading indicators
D) Historical analogy
E) Simulation

Question 68

Which of the following forecasting methodologies is considered a time series forecasting technique?

A) Delphi method
B) Exponential averaging
C) Simple movement smoothing
D) Weighted moving average
E) Simulation

Question 69

In most cases, demand for products or services can be broken into several components. Which of the following is considered a component of demand?

A) Cyclical elements
B) Future demand
C) Past demand
D) Inconsistent demand
E) Level demand

Question 70

Which of the following forecasting methods can be used for short-term forecasting?

A) Simple exponential smoothing
B) Delphi technique
C) Market research
D) Hoskins-Hamilton smoothing
E) Serial regression

Question 71

Which of the following is not one of the basic types of forecasting?

A) Qualitative
B) Time series analysis
C) Causal relationships
D) Simulation
E) Force field analysis

Question 72

A company wants to forecast demand using the simple moving average. If the company uses three prior yearly sales values , which of the following is the simple moving average forecast for year 2020?

A) 100.5
B) 122.5
C) 133.3
D) 135.6
E) 139.3

Question 73

In business forecasting, what is usually considered a short-term time period?

A) Four weeks or less
B) More than three months
C) Six months or more
D) Less than three months
E) One year

Question 74

In general, which forecasting time frame is best to detect general trends?

A) Short-term forecasts
B) Quick-time forecasts
C) Long-range forecasts
D) Medium-term forecasts
E) Rapid-change forecasts

Question 75

A company wants to forecast demand using the simple moving average. If the company uses four prior yearly sales values , which of the following is the simple moving average forecast for year 2020?

A) 100.5
B) 140.0
C) 142.5
D) 145.5
E) 155.0

Question 76

Which of the following forecasting methods is very dependent on selection of the right individuals who will judgmentally be used to actually generate the forecast?

A) Time series analysis
B) Simple moving average
C) Weighted moving average
D) Delphi method
E) Panel consensus

Question 77

Which of the following forecasting methodologies is considered a causal forecasting technique?

A) Exponential smoothing
B) Weighted moving average
C) Linear regression
D) Historical analogy
E) Market research

Question 78

Which of the following forecasting methodologies is considered a qualitative forecasting technique?

A) Simple moving average
B) Market research
C) Linear regression
D) Exponential smoothing
E) Multiple regression

Question 79

Which of the following forecasting methods uses executive judgment as its primary component for forecasting?

A) Historical analogy
B) Time series analysis
C) Panel consensus
D) Market research
E) Linear regression

Question 80

In business forecasting, what is usually considered a long-term time period?

A) Three months or longer
B) Six months or longer
C) One year or longer
D) Two years or longer
E) Ten years or longer