Question 1

Additive models are most appropriate over longer periods of time or when the data magnitude is growing rapidly over time.

Accepted Answer

A) True 
 B)False

Question 2

Over the short run, exponential and linear trends may look alike.

Accepted Answer

A) True 
 B)False

Question 3

Might it be OK to use exponential smoothing to forecast 2010 for Bob's data?

Accepted Answer

A) No, under no circumstances 
B) Yes, if you use only the most recent 10 years 
C) Yes, if you need a long-term forecast 
D) No, since the data appear to be erratic 
A) No, under no circumstances 
B) Yes, if you use only the most recent 10 years 
C) Yes, if you need a long-term forecast 
D) No, since the data appear to be erratic

Question 4

If yt = 544e0.07t, then the forecast for period 7 is approximately:

Accepted Answer

A) 989. 
B) 888. 
C) 678. 
D) 589. 
A) 989. 
B) 888. 
C) 678. 
D) 589.

Question 5

Which of the following best describes the decomposition modeling approach to forecasting?

Accepted Answer

A) The values of certain variables are used to predict the values of others. 
B) Series are separated into trend, seasonal, irregular, and cyclical components. 
C) Forecasts are based on an average of recent values. 
D) Sophisticated models such as regression with binaries are preferred. 
A) The values of certain variables are used to predict the values of others. 
B) Series are separated into trend, seasonal, irregular, and cyclical components. 
C) Forecasts are based on an average of recent values. 
D) Sophisticated models such as regression with binaries are preferred.

Question 6

Multiplicative models are most appropriate over longer periods of time or when the data magnitude is growing rapidly over time.

Accepted Answer

A) True 
 B)False

Question 7

Which is a characteristic of an additive (as opposed to multiplicative) time-series model?

Accepted Answer

A) Appropriate for financial data over a longer time period 
B) Appropriate for rapidly growing financial data 
C) Appropriate for data that vary by an order of magnitude 
D) Appropriate for short-term data with a steady dollar growth 
A) Appropriate for financial data over a longer time period 
B) Appropriate for rapidly growing financial data 
C) Appropriate for data that vary by an order of magnitude 
D) Appropriate for short-term data with a steady dollar growth

Question 8

Which statement is most defensible regarding the time series shown below?

Accepted Answer

A) There appears to be strong seasonality. 
B) There appears to be a six-month seasonal cycle. 
C) The trend appears to be exponential. 
D) The quadratic trend would be required. 
A) There appears to be strong seasonality. 
B) There appears to be a six-month seasonal cycle. 
C) The trend appears to be exponential. 
D) The quadratic trend would be required.

Question 9

Seasonality is usually ignored because there is no statistical way to describe it.

Accepted Answer

A) True 
 B)False

Question 10

The implied turning point (peak or trough) of yt = 516 - 42t + 3t2 would be in which period? Hint: Use calculus to solve for the value of t that would maximize or minimize yt.

Accepted Answer

A) t = 7 
B) t = -7 
C) t = 6 
D) t = -42 
A) t = 7 
B) t = -7 
C) t = 6 
D) t = -42

Question 11

If Y1 = 116 and Y7 = 255, then the simple index number for period 7 (denoted I7) is:

Accepted Answer

A) 215.3. 
B) 219.8. 
C) 222.7. 
D) 242.4. 
A) 215.3. 
B) 219.8. 
C) 222.7. 
D) 242.4.

Question 12

A centered moving average provides good forecasts when there is a strong upward trend in the data.

Accepted Answer

A) True 
 B)False

Question 13

Which model assumes a constant percentage rate of growth?

Accepted Answer

A) Linear 
B) Quadratic 
C) Cubic 
D) Exponential 
A) Linear 
B) Quadratic 
C) Cubic 
D) Exponential

Question 14

The MAD measures the average absolute size of the forecast error.

Accepted Answer

A) True 
 B)False

Question 15

If a fitted trend equation is yt = 227e-.098t then the forecast for period 5 is:

Accepted Answer

A) 372. 
B) -87. 
C) -216. 
D) 139. 
A) 372. 
B) -87. 
C) -216. 
D) 139.

Question 16

In a multiplicative model, if the seasonal factor is 1.15 for a particular season, then we expect that the time series in that season would be (other things being equal):

Accepted Answer

A) 115% above the trend. 
B) 115% below the trend. 
C) 15% above the trend. 
D) 15% below the trend. 
A) 115% above the trend. 
B) 115% below the trend. 
C) 15% above the trend. 
D) 15% below the trend.

Question 17

The compound growth rate in the fitted trend equation yt = 228e-.0982t is:

Accepted Answer

A) 98.2 percent. 
B) -9.82 percent. 
C) 198.2 percent. 
D) 228 percent. 
A) 98.2 percent. 
B) -9.82 percent. 
C) 198.2 percent. 
D) 228 percent.

Question 18

Which statement is correct for a simple index number?

Accepted Answer

A) For the base year, the index is set to 0.000. 
B) We cannot use index numbers to compare two time series measured in different units. 
C) The simple relative index for period t = 5 is calculated as Y5/Y1. 
D) Weighted index numbers have few practical applications because of their complexity. 
A) For the base year, the index is set to 0.000. 
B) We cannot use index numbers to compare two time series measured in different units. 
C) The simple relative index for period t = 5 is calculated as Y5/Y1. 
D) Weighted index numbers have few practical applications because of their complexity.

Question 19

Multiplicative models are avoided in business because they are too complicated.

Accepted Answer

A) True 
 B)False

Question 20

Which is a time series?

Accepted Answer

A) Last year's GDP in 27 developing countries 
B) Year-end unemployment rates in the United States, 2000-2010 
C) Passenger miles flown by each of 10 major airlines in 2010 
D) The number of "hits" on each of 10 websites yesterday 
A) Last year's GDP in 27 developing countries 
B) Year-end unemployment rates in the United States, 2000-2010 
C) Passenger miles flown by each of 10 major airlines in 2010 
D) The number of "hits" on each of 10 websites yesterday

Additive models are most appropriate over longer periods of time or when the data magnitude is growing rapidly over time.

Over the short run, exponential and linear trends may look alike.

Might it be OK to use exponential smoothing to forecast 2010 for Bob's data?

If y_t = 544e^0.07^t, then the forecast for period 7 is approximately:

Which of the following best describes the decomposition modeling approach to forecasting?

Multiplicative models are most appropriate over longer periods of time or when the data magnitude is growing rapidly over time.

Which is a characteristic of an additive (as opposed to multiplicative) time-series model?

Which statement is most defensible regarding the time series shown below?

Seasonality is usually ignored because there is no statistical way to describe it.

The implied turning point (peak or trough) of y_t = 516 - 42t + 3t² would be in which period? Hint: Use calculus to solve for the value of t that would maximize or minimize y_t.

If Y₁ = 116 and Y₇ = 255, then the simple index number for period 7 (denoted I₇) is:

A centered moving average provides good forecasts when there is a strong upward trend in the data.

Which model assumes a constant percentage rate of growth?

The MAD measures the average absolute size of the forecast error.

If a fitted trend equation is y_t = 227e^-.098^t then the forecast for period 5 is:

In a multiplicative model, if the seasonal factor is 1.15 for a particular season, then we expect that the time series in that season would be (other things being equal):

The compound growth rate in the fitted trend equation y_t = 228e^-.0982^t is:

Which statement is correct for a simple index number?

Multiplicative models are avoided in business because they are too complicated.

Which is a time series?

Overview of Statistics

Data Collection

Describing Data Visually

Descriptive Statistics

Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling Distributions and Estimation

One-Sample Hypothesis Tests

Two-Sample Hypothesis Tests

Analysis of Variance

Simple Regression

Multiple Regression

Chi-Square Tests

Nonparametric Tests

Quality Management

Filters

Exam 14: Time Series Analysis

Additive models are most appropriate over longer periods of time or when the data magnitude is growing rapidly over time.

Over the short run, exponential and linear trends may look alike.

Might it be OK to use exponential smoothing to forecast 2010 for Bob's data?

If yt = 544e0.07t, then the forecast for period 7 is approximately:

Which of the following best describes the decomposition modeling approach to forecasting?

Multiplicative models are most appropriate over longer periods of time or when the data magnitude is growing rapidly over time.

Which is a characteristic of an additive (as opposed to multiplicative) time-series model?

Which statement is most defensible regarding the time series shown below?

Seasonality is usually ignored because there is no statistical way to describe it.

The implied turning point (peak or trough) of yt = 516 - 42t + 3t2 would be in which period? Hint: Use calculus to solve for the value of t that would maximize or minimize yt.

If Y1 = 116 and Y7 = 255, then the simple index number for period 7 (denoted I7) is:

A centered moving average provides good forecasts when there is a strong upward trend in the data.

Which model assumes a constant percentage rate of growth?

The MAD measures the average absolute size of the forecast error.

If a fitted trend equation is yt = 227e-.098t then the forecast for period 5 is:

In a multiplicative model, if the seasonal factor is 1.15 for a particular season, then we expect that the time series in that season would be (other things being equal):

The compound growth rate in the fitted trend equation yt = 228e-.0982t is:

Which statement is correct for a simple index number?

Multiplicative models are avoided in business because they are too complicated.

Which is a time series?

Overview of Statistics

Data Collection

Describing Data Visually

Descriptive Statistics

Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling Distributions and Estimation

One-Sample Hypothesis Tests

Two-Sample Hypothesis Tests

Analysis of Variance

Simple Regression

Multiple Regression

Chi-Square Tests

Nonparametric Tests

Quality Management

Filters

If y_t = 544e^0.07^t, then the forecast for period 7 is approximately:

The implied turning point (peak or trough) of y_t = 516 - 42t + 3t² would be in which period? Hint: Use calculus to solve for the value of t that would maximize or minimize y_t.

If Y₁ = 116 and Y₇ = 255, then the simple index number for period 7 (denoted I₇) is:

If a fitted trend equation is y_t = 227e^-.098^t then the forecast for period 5 is:

The compound growth rate in the fitted trend equation y_t = 228e^-.0982^t is: