5th Edition Full Test Bank Chapter.3 Forecasting - Supply Chain Management Core 5e Complete Test Bank by F. Robert Jacobs. DOCX document preview.
Operations and Supply Chain Management: The Core, 5e (Jacobs)
Chapter 3 Forecasting
1) Continual review and updating in light of new data is a forecasting technique called second-guessing.
Difficulty: 1 Easy
Topic: Quantitative Forecasting Models
Learning Objective: 03-01 Understand how forecasting is essential to supply chain planning.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
2) Cyclical influences on demand are often expressed graphically as a linear function that is either upward or downward sloping.
Difficulty: 1 Easy
Topic: Components of Demand
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
3) Cyclical influences on demand may come from occurrences such as political elections, war, or economic conditions.
Difficulty: 1 Easy
Topic: Components of Demand
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
4) Trend lines are usually the last things considered when developing a forecast.
Difficulty: 1 Easy
Topic: Components of Demand
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
5) Time series forecasting models make predictions about the future based on analysis of past data.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
6) In the weighted moving average forecasting model the weights must add up to one times the number of data points.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
7) In a forecasting model using simple exponential smoothing the data pattern should remain stationary.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
8) 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.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
9) In the simple exponential smoothing forecasting model you need at least 30 observations to set the smoothing constant alpha.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
10) Experience and trial and error are the simplest ways to choose weights for the weighted moving average forecasting model.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
11) Bayesian analysis is the simplest way to choose weights for the weighted moving average forecasting model.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
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.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
13) A central premise of exponential smoothing is that more recent data is less indicative of the future than data from the distant past.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
14) The equation for exponential smoothing states that the new forecast is equal to the old forecast plus the error of the old forecast.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
15) Exponential smoothing is always the best and most accurate of all forecasting models.
Difficulty: 1 Easy
Topic: From Bean to Cup: Starbucks Global Supply Chain Challenge
Learning Objective: 03-01 Understand how forecasting is essential to supply chain planning.
Bloom's: Create
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
16) In exponential smoothing, it is desirable to use a higher smoothing constant when forecasting demand for a product experiencing high growth.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
17) The value of the smoothing constant alpha in an exponential smoothing model is between 0 and 1.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
18) Simple exponential smoothing lags changes in demand.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
19) Exponential smoothing forecasts always lag behind the actual occurrence but can be corrected somewhat with a trend adjustment.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
20) Because the factors governing demand for products are very complex, all forecasts of demand contain error.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
21) Random errors can be defined as those that cannot be explained by the forecast model being used.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
22) 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.
Difficulty: 2 Medium
Topic: From Bean to Cup: Starbucks Global Supply Chain Challenge
Learning Objective: 03-01 Understand how forecasting is essential to supply chain planning.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
23) Random errors in forecasting occur when an undetected secular trend is not included in a forecasting model.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
24) The MAD is used to generate tracking signals.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
25) MAD statistics can be used to generate tracking signals.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
26) RSFE in forecasting stands for "reliable safety function error."
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
27) In forecasting, RSFE stands for "running sum of forecast errors."
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
28) A tracking signal (TS) can be calculated using the arithmetic sum of forecast deviations divided by the MAD.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
29) A restriction in using linear regression is that it assumes that past data and future projections fall on or near a straight line.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
30) Regression is a functional relationship between two or more correlated variables, where one or more variables are used to predict a single variable of interest.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
31) Linear regression is not useful for aggregate planning.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
32) 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.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
33) Multiple regression analysis uses several regression models to generate a forecast.
Difficulty: 1 Easy
Topic: Causal Relationship Forecasting
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
34) For every forecasting problem there is one best forecasting technique.
Difficulty: 1 Easy
Topic: From Bean to Cup: Starbucks Global Supply Chain Challenge
Learning Objective: 03-01 Understand how forecasting is essential to supply chain planning.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
35) 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.
Difficulty: 1 Easy
Topic: Quantitative Forecasting Models
Learning Objective: 03-01 Understand how forecasting is essential to supply chain planning.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
36) In causal relationship forecasting leading indicators are used to forecast occurrences.
Difficulty: 1 Easy
Topic: Causal Relationship Forecasting
Learning Objective: 03-01 Understand how forecasting is essential to supply chain planning.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
37) Qualitative forecasting techniques generally take advantage of the knowledge of experts and therefore do not require much judgment.
Difficulty: 1 Easy
Topic: Qualitative Techniques in Forecasting
Learning Objective: 03-03 Apply qualitative techniques to forecast demand.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
38) Market research is a quantitative method of forecasting.
Difficulty: 1 Easy
Topic: Qualitative Techniques in Forecasting
Learning Objective: 03-03 Apply qualitative techniques to forecast demand.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
39) Decomposition of a time series means identifying and separating the time series data into its components.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
40) 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.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
41) It is difficult to identify the trend in time series data.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
42) In decomposition of time series data it is relatively easy identify cycles and autocorrelation components.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
43) We usually associate the word "seasonal" with recurrent periods of repetitive activity that happen on other than an annual cycle.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
44) 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
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
45) Which of the following is not one of the basic forecasting types discussed in the text?
A) Qualitative
B) Time series analysis
C) Causal relationships
D) Simulation
E) Force field analysis
Difficulty: 1 Easy
Topic: Quantitative Forecasting Models
Learning Objective: 03-01 Understand how forecasting is essential to supply chain planning.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
46) 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
Difficulty: 2 Medium
Topic: Components of Demand
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
47) 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
Difficulty: 1 Easy
Topic: Components of Demand
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
48) 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
Difficulty: 1 Easy
Topic: Components of Demand
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
49) 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
Difficulty: 1 Easy
Topic: Qualitative Techniques in Forecasting
Learning Objective: 03-03 Apply qualitative techniques to forecast demand.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
50) 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
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
51) 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
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
52) 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
Difficulty: 1 Easy
Topic: Causal Relationship Forecasting
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Understand
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
53) 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
Difficulty: 1 Easy
Topic: Qualitative Techniques in Forecasting
Learning Objective: 03-03 Apply qualitative techniques to forecast demand.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
54) 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
Difficulty: 2 Medium
Topic: Qualitative Techniques in Forecasting
Learning Objective: 03-03 Apply qualitative techniques to forecast demand.
Bloom's: Understand
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
55) 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
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
56) 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
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Understand
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
57) 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
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
58) 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
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Understand
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
59) 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
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Understand
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
60) 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
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
61) 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
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Understand
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
62) 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
Difficulty: 1 Easy
Topic: Quantitative Forecasting Models
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
63) A company wants to forecast demand using the simple moving average. If the company uses four prior yearly sales values (i.e., year 2014 = 100, year 2015 = 120, year 2016 = 140, and year 2017 = 210), which of the following is the simple moving average forecast for year 2018?
A) 100.5
B) 140.0
C) 142.5
D) 145.5
E) 155.0
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
64) A company wants to forecast demand using the simple moving average. If the company uses three prior yearly sales values (i.e., year 2015 = 130, year 2016 = 110, and year 2017 =160), which of the following is the simple moving average forecast for year 2018?
A) 100.5
B) 122.5
C) 133.3
D) 135.6
E) 139.3
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
65) A company wants to forecast demand using the weighted moving average. If the company uses two prior yearly sales values (i.e., year 2013 = 110 and year 2015 = 130), and we want to weight year 2016 at 10% and year 2017 at 90%, which of the following is the weighted moving average forecast for year 2018?
A) 120
B) 128
C) 133
D) 138
E) 142
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
66) A company wants to forecast demand using the weighted moving average. If the company uses three prior yearly sales values (i.e., year 2015 = 160, year 2016 = 140 and year 2017 = 170), and we want to weight year 2014 at 30%, year 2015 at 30% and year 2016 at 40%, which of the following is the weighted moving average forecast for year 2018?
A) 170
B) 168
C) 158
D) 152
E) 146
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
67) Which one of the following are among the major reasons that exponential smoothing has become well accepted as a forecasting technique?
A) Accurate and easy to use
B) Sophistication of analysis
C) Predicts turning points
D) Captures patterns in historical data
E) Ability to forecast lagging data trends
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Understand
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
68) The exponential smoothing method requires which of the following data to forecast the future?
A) The most recent forecast
B) Precise actual demand for the past several years
C) The value of the smoothing constant delta
D) Overall industry demand data
E) Tracking values
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
69) Given a prior forecast demand value of 230, a related actual demand value of 250, and a smoothing constant alpha of 0.1, what is the exponential smoothing forecast value for the following period?
A) 230
B) 232
C) 238
D) 248
E) 250
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
70) If a firm produced a standard item with relatively stable demand, the smoothing constant alpha (reaction rate to differences) used in an exponential smoothing forecasting model would tend to be in which of the following ranges?
A) 5% to 10%
B) 20% to 50%
C) 20% to 80%
D) 60% to 120%
E) 90% to 100%
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Understand
AACSB: Reflective Thinking
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71) If a firm produced a product that was experiencing growth in demand, the smoothing constant alpha (reaction rate to differences) used in an exponential smoothing forecasting model would tend to be which of the following?
A) Close to zero.
B) A very low percentage, less than 10%.
C) The more rapid the growth, the higher the percentage.
D) The more rapid the growth, the lower the percentage.
E) 50% or more.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Understand
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
72) Given a prior forecast demand value of 1,100, a related actual demand value of 1,000, and a smoothing constant alpha of 0.3, what is the exponential smoothing forecast value?
A) 1,000
B) 1,030
C) 1,070
D) 1,130
E) 970
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
73) A company wants to generate a forecast for unit demand for year 2018 using exponential smoothing. The actual demand in year 2017 was 120. The forecast demand in year 2017 was 110. Using this data and a smoothing constant alpha of 0.1, which of the following is the resulting year 2018 forecast value?
A) 100
B) 110
C) 111
D) 114
E) 120
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
74) As a consultant you have been asked to generate a unit demand forecast for a product for year 2018 using exponential smoothing. The actual demand in year 2017 was 750. The forecast demand in year 2017 was 960. Using this data and a smoothing constant alpha of 0.3, which of the following is the resulting year 2018 forecast value?
A) 766
B) 813
C) 897
D) 1,023
E) 1,120
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
75) Which of the following is a possible source of bias error in forecasting?
A) Failing to include the right variables
B) Using the wrong forecasting method
C) Employing less sophisticated analysts than necessary
D) Using incorrect data
E) Using standard deviation rather than MAD
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
76) Which of the following are used to describe the degree of error?
A) Weighted moving average
B) Regression
C) Moving average
D) Forecast as a percent of actual
E) Mean absolute deviation
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Understand
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
77) A company has actual unit demand for three consecutive years of 124, 126, and 135. The respective forecasts for the same three years are 120, 120, and 130. Which of the following is the resulting MAD value that can be computed from this data?
A) 1
B) 3
C) 5
D) 15
E) 123
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
78) A company has actual unit demand for four consecutive years of 100, 105, 135, and 150. The respective forecasts were 120 for all four years. Which of the following is the resulting MAD value that can be computed from this data?
A) 2.5
B) 10
C) 20
D) 22.5
E) 30
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
79) If you were selecting from a variety of forecasting models based on MAD, which of the following MAD values from the same data would reflect the most accurate model?
A) 0.2
B) 0.8
C) 1.0
D) 10.0
E) 100.0
Difficulty: 3 Hard
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Understand
AACSB: Reflective Thinking
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80) A company has calculated its running sum of forecast errors to be 500 and its mean absolute deviation is exactly 35. Which of the following is the company's tracking signal?
A) Cannot be calculated based on this information
B) About 14.3
C) More than 35
D) Exactly 35
E) About 0.07
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
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81) A company has a MAD of 10. Its wants to have a 99.7 percent control limits on its forecasting system. It's most recent tracking signal value is 3.1. What can the company conclude from this information?
A) The forecasting model is operating acceptably
B) The forecasting model is out of control and needs to be corrected
C) The MAD value is incorrect
D) The upper control value is less than 20
E) It is using an inappropriate forecasting methodology
Difficulty: 3 Hard
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Create
AACSB: Analytical Thinking
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82) You are hired as a consultant to advise a small firm on forecasting methodology. Based on your research you find the company has a MAD of 3. Its wants to have a 99.7 percent control limits on its forecasting system. Its most recent tracking signal value is 15. What should be your report to the company?
A) The forecasting model is operating acceptably
B) The forecasting model is out of control and needs to be corrected
C) The MAD value is incorrect
D) The upper control value is less than 20
E) The company is using an inappropriate forecasting methodology
Difficulty: 3 Hard
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Create
AACSB: Analytical Thinking
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83) Which of the following is the portion of observations you would expect to see lying within a plus or minus 3 MAD range?
A) 57.05 percent
B) 88.95 percent
C) 98.36 percent
D) 99.85 percent
E) 100 percent
Difficulty: 3 Hard
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
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84) Which of the following is the portion of observations you would expect to see lying within a plus or minus 2 MAD range?
A) 57.04
B) 89.04
C) 98.33
D) 99.86
E) 100.00
Difficulty: 3 Hard
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
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85) If the intercept value of a linear regression model is 40, the slope value is 40, and the value of X is 40, which of the following is the resulting forecast value using this model?
A) 120
B) 1,600
C) 1,640
D) 2,200
E) 64,000
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
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86) A company hires you to develop a linear regression forecasting model. Based on the company's historical sales information, you determine the intercept value of the model to be 1,200. You also find the slope value is minus 50. If after developing the model you are given a value of X = 10, which of the following is the resulting forecast value using this model?
A) – 1,800
B) 700
C) 1,230
D) 1,150
E) 12,000
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
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87) Heavy sales of umbrellas during a rain storm is an example of which of the following?
A) A trend
B) A causal relationship
C) A statistical correlation
D) A coincidence
E) A fad
Difficulty: 1 Easy
Topic: Causal Relationship Forecasting
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Remember
AACSB: Reflective Thinking
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88) You are using an exponential smoothing model for forecasting. The running sum of the forecast error statistics (RSFE) are calculated each time a forecast is generated. You find the last RSFE to be 34. Originally the forecasting model used was selected because it's relatively low MAD of 0.4. To determine when it is time to reevaluate the usefulness of the exponential smoothing model you compute tracking signals. Which of the following is the resulting tracking signal?
A) 85
B) 60
C) 13.6
D) 12.9
E) 8
Difficulty: 2 Medium
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
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89) Using the exponential smoothing model for forecasting, the smoothing constant alpha determines the level of smoothing and
A) the slope of the growth curve.
B) the speed of reaction to differences between forecasts and actual results.
C) the intercept on the Y-axis.
D) the next forecast error.
E) a measure of forecast accuracy.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-03 Apply qualitative techniques to forecast demand.
Bloom's: Understand
AACSB: Reflective Thinking
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90) The least squares method refers to
A) a computation in linear regression.
B) selecting participants for the Delphi Technique.
C) time series decomposition into smaller and smaller units.
D) determining the smallest sources of error in a forecast.
E) calculating the running sum of forecast errors.
Difficulty: 1 Easy
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Understand
AACSB: Reflective Thinking
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91) Collaborative Planning, Forecasting, and Replenishment (CPFR) is a web-based tool used to coordinate demand forecasting, production and purchase planning, and inventory replenishment between supply chain trading partners. In practice CPFR often doesn't deliver on its' promise because;
1) Computer systems at supplier companies cannot be made to work with each other.
2) Forecast errors accumulate as data exchanges are made down the supply chain culminating in the "feast or famine" phenomena known as the "bullwhip effect."
3) Firms in a supply chain may not trust each other sufficiently to share information openly.
4) conflicting objectives between the profit-maximizing vendor and the cost-minimizing customer give rise to adversarial supply chain relationships.
A) All of these
B) 2 and 4 above
C) 1 and 3 above
D) 1, 3, and 4 above
E) 3 and 4 above
Difficulty: 3 Hard
Topic: Web based collaborative forecasting
Learning Objective: 03-04 Apply collaborative techniques to forecast demand.
Bloom's: Understand
AACSB: Reflective Thinking
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92) A company wants to forecast demand using the simple moving average. The company uses four positive prior yearly (2014, 2015, 2016 and 2017) sales values. All yearly sales figures are unique (no repetitions). Which of the following is most accurate about the moving average forecast for year 2018?
- Has to be smaller than at least one of the four yearly sales figures.
- Has to be larger than at least one of the four yearly sales figures.
- Has to be between the smallest and largest yearly sales figures.
- Has to greater than all four yearly sales figures.
A) Choice A
B) Choice B
C) Choice C
D) Choice D
E) Choice A, B and C only
Difficulty: 3 Hard
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
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93) As a consultant, you have been asked to generate a unit demand forecast for a product for year 2018 using exponential smoothing. You have data for the past three years and the forecast and the actual are the same for the first period of your data (3 years ago). Which of the following is most accurate?
- Forecast for year 2018 will be higher than the actual for 2017, if your α is close to 1.0
- Forecast for 2018 will be between all the actual sales
- Exponential smoothing is a type of weighted average forecasting method
A) Choice A
B) Choice B
C) Choice C
D) Choice B and C only
E) None of the above
Difficulty: 3 Hard
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
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94) As a consultant, you have been thinking about choosing the "right" alpha (smoothing constant) for forecasting using exponential smoothing. Which of the following is most accurate about alpha?
- If alpha is high, speed of reaction to changes in actually low.
- If a firm produces standard product with relatively stable demand, alpha should be small.
- Products experiencing growth should be assigned higher alpha value.
- Alpha could be more than 1.0, and in this case (1-alpha) will become negative to make up for it.
A) Choice A
B) Choice B
C) Choice C
D) Choice D
E) Choice B and C
Difficulty: 3 Hard
Topic: Time Series Analysis
Learning Objective: 03-02 Evaluate demand using quantitative forecasting models.
Bloom's: Analyze
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Document Information
Connected Book
Supply Chain Management Core 5e Complete Test Bank
By F. Robert Jacobs