Question 1

The time-series component that reflects a wavelike pattern describing a long-term trend that is generally apparent over a number of years is called:

Accepted Answer

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

Question 2

Seasonal variations will be present in a deseasonalised time series.

Accepted Answer

A) True 
 B)False

Question 3

The following trend line was calculated from quarterly data for 2006-2010: ŷ = 2.35 + 0.12t, where t = 1 for the first quarter of 2006. The seasonal indexes computed from the trend line for the four quarters of the year 2011 are 0.88, 0.93, 1.04, and 1.17, respectively. The seasonalised forecast for the third quarter of the year 2011 is:

Accepted Answer

A)  5.314. 
B)  6.119. 
C)  4.286. 
D)  4.641. 
A)  5.314. 
B)  6.119. 
C)  4.286. 
D)  4.641.

Question 4

If autumn 2013 sales were $20 500 and the summer seasonal index was 1.17, then the deseasonalised 2010 autumn sales value would be:

Accepted Answer

A)  $19 422. 
B)  $13 675. 
C)  $14 188. 
D)  $18 720. 
A)  $19 422. 
B)  $13 675. 
C)  $14 188. 
D)  $18 720.

Question 5

A company selling swimming goggles wants to analyze the company's Australian sales figure.
Describe the 4 components of the line graph of Swimming goggle quarterly sales (in $000's) given below.

Accepted Answer

Trend = 12.237 + 0.27t
The tre

Question 6

We calculate the three-period moving averages for a time series for all time periods except the:

Accepted Answer

A)  first and last period. 
B)  first two periods. 
C)  last two periods. 
D)  first and last two periods. 
A)  first and last period. 
B)  first two periods. 
C)  last two periods. 
D)  first and last two periods.

Question 7

To calculate the five-period moving average of a time series for a given time period, we average the value in that time period and the values in the four preceding periods.

Accepted Answer

A) True 
 B)False

Question 8

Which of the following is true?

Accepted Answer

A)  In trend analysis, the independent variable is time only if the equation is linear. 
B)  The number of time periods in a centred moving average is always even. 
C)  If the seasonal index for December sales is 120, this means that December sales tend to be 120% higher than the 'average' month. 
D)  The cyclical component of a time series refers to repeating patterns that have a period of a year or less. 
A)  In trend analysis, the independent variable is time only if the equation is linear. 
B)  The number of time periods in a centred moving average is always even. 
C)  If the seasonal index for December sales is 120, this means that December sales tend to be 120% higher than the 'average' month. 
D)  The cyclical component of a time series refers to repeating patterns that have a period of a year or less.

Question 9

A time series regression equation measuring the number of surfboards sold by a surfboard manufacturing company in Australia is given below: Y = 35 + 4Q1 + 0.5Q3 + 8Q4 + 3t
With t in quarters and the origin is December 2010 and Q1 is the indicator variable for March, Q3 is the indicator variable for September and Q4 is the indicator variable for December.
Which of the following statements is correct?

Accepted Answer

A)  There is a mistake with this regression model because all the coefficients of the indicator variables are positive. 
B)  There is no indicator variable for the June quarter in this model because there is no seasonal effect in June due to winter in Australia. 
C)  There is a mistake with this model because the indicator variable for the June quarter has been left out. 
D)  There is no indicator variable for the June quarter in this model because we need one less indicator variable than number of categories to use indicator variables with regression for a time series. 
A)  There is a mistake with this regression model because all the coefficients of the indicator variables are positive. 
B)  There is no indicator variable for the June quarter in this model because there is no seasonal effect in June due to winter in Australia. 
C)  There is a mistake with this model because the indicator variable for the June quarter has been left out. 
D)  There is no indicator variable for the June quarter in this model because we need one less indicator variable than number of categories to use indicator variables with regression for a time series.

Question 10

The daily sales figures below have been recorded in a medium-sized insurance company. $$\begin{array}{l}
\text { Week }\
\begin{array} { | l | c c c c | } 
\hline \text { Day } & 1 & 2 & 3 & 4 \
\hline \text { Monday } & 38 & 46 & 35 & 59 \
\text { Tuesday } & 40 & 36 & 52 & 53 \
\text { Wednesday } & 17 & 32 & 25 & 28 \
\text { Thursday } & 20 & 17 & 28 & 33 \
\text { Friday } & 26 & 20 & 32 & 20 \
\hline
\end{array}
\end{array}$$ a. Compute the three-day and five-day moving averages.
b. Plot the series and the moving averages on the same graph.
c. Does there appear to be a seasonal (weekly) pattern?

Accepted Answer

a. @#IMG-DLM& b. @#IMG-DLM& c. There app

Question 11

A 5 period moving average will show less fluctuation than a 3 period moving average, for the same time series.

Accepted Answer

A) True 
 B)False

Question 12

A time series regression equation for a surfboard manufacturing company in Australia is given below: Y = 35 + 4Q1 + 0.5Q3 + 8Q4 + 3t
With t in quarters, the origin is December 2010 and Q1 is the indicator variable for March, Q3 is the indicator variable for September and Q4 is the indicator variable for December.
Which of the following is the correct value of the estimate for the number of surfboards sold by this manufacturing company in June 2013?

Accepted Answer

A)  68 
B)  77.5 
C)  65 
D)  None of these choices are correct 
A)  68 
B)  77.5 
C)  65 
D)  None of these choices are correct

Question 13

A time series is shown in the table below: $\quad $$\quad $$\quad $$\quad $$\quad $$\quad $$\quad $$\quad $$\quad $$\quad $$\text{Week}$
$\begin{array} { | l | c c c c | } 
\hline \text { Day } & 1 & 2 & 3 & 4 \
\hline \text { Monday } & 16 & 15 & 18 & 21 \
\text { Tuesday } & 22 & 21 & 20 & 25 \
\text { Wednesday } & 20 & 23 & 20 & 24 \
\text { Thursday } & 29 & 28 & 32 & 28 \
\text { Friday } & 35 & 31 & 29 & 36 \
\hline
\end{array}$ a. Compute the five-day moving averages to remove the seasonal and random variation.
b. Calculate the seasonal (daily) indexes.
c. What do the daily indexes tell us?
d. Find the regression trend line.
e. Calculate the seasonal indexes, based on the regression trend line developed in (d).

Accepted Answer

None

Question 14

One measure of the accuracy of a forecasting model is the:

Accepted Answer

A)  deseasonalised time series. 
B)  four-period moving average. 
C)  mean absolute deviation. 
D)  smoothing constant. 
A)  deseasonalised time series. 
B)  four-period moving average. 
C)  mean absolute deviation. 
D)  smoothing constant.

Question 15

The total number of overtime hours (in 1000s) worked in a large steel mill was recorded for 16 quarters, as shown below. $$\begin{array} { | c | c | c | } 
\hline \text { Year } & \text { Quarter } & \text { Overtime hours } \
\hline 2007 & 1 & 20 \
& 2 & 30 \
& 3 & 28 \
& 4 & 20 \
 { 2008 } & 1 & 24 \
& 2 & 34 \
& 3 & 28 \
& 4 & 21 \
{ 2009 } & 1 & 28 \
& 2 & 38 \
& 3 & 31 \
& 4 & 26 \
2010& 1 & 30 \
& 2 & 41 \
& 3 & 35 \
& 4 & 28 \
\hline
\end{array}$$ a. Use the regression technique to calculate the linear trend line.
b. Calculate the seasonal indexes based on the regression trend line in part (a).
c. What do the seasonal indexes tell us?

Accepted Answer

a. ŷ_t = 23.2 + 0.668t. b. Use Excel to ca

Question 16

We compute the five-period moving averages for all time periods except the first two and the last two.

Accepted Answer

A) True 
 B)False

Question 17

In determining monthly seasonal indexes for petrol consumption, the sum of the 12 means for petrol consumption as a percentage of the moving average is 1230. To get the seasonal indexes, each of the 12 monthly means is to be multiplied by:

Accepted Answer

A)  1200 / 1230. 
B)  1230 / 1200. 
C)  (1230 + 1200) / 2. 
D)  (1230 + 1200) / 12. 
A)  1200 / 1230. 
B)  1230 / 1200. 
C)  (1230 + 1200) / 2. 
D)  (1230 + 1200) / 12.

Question 18

Of the four different components of a time series, cyclical variation is the one most likely to exhibit the long-term direction of the data.

Accepted Answer

A) True 
 B)False

Question 19

In determining weekly seasonal indexes for natural gas consumption, the sum of the 52 means for gas consumption as a percentage of the moving average is 5195. To get the seasonal indexes, each monthly mean is to be multiplied by (5200 / 5195).

Accepted Answer

A) True 
 B)False

Question 20

Petrol sales in Newcastle have been recorded over the past 10 months as shown below. $$\begin{array} { | l | c c c c c c c c c c | } 
\hline \text { Month } & \text { Jan } & \text { Feb } & \text { Mar } & \text { Apr } & \text { May } & \text { Jun } & \text { Jul } & \text { Aug } & \text { Sep } & \text { Oct } \
\hline \text { Sales } & 75 & 72 & 81 & 92 & 90 & 105 & 112 & 107 & 110 & 93 \
\hline
\end{array}$$ a. Compute the five-month moving average.
b. Calculate the four-month moving average, and four-month centred moving average.
c. Compute the exponentially smoothed sales with w = 0.4 and w = 0.8.
d. Draw the time series and the two sets of exponentially smoothed values. Does there appear to be a trend component in the time series?

Accepted Answer

a. \[\begin{array} { | l | c c | } 
\hli

The time-series component that reflects a wavelike pattern describing a long-term trend that is generally apparent over a number of years is called:

Seasonal variations will be present in a deseasonalised time series.

If autumn 2013 sales were $20 500 and the summer seasonal index was 1.17, then the deseasonalised 2010 autumn sales value would be:

A company selling swimming goggles wants to analyze the company's Australian sales figure. Describe the 4 components of the line graph of Swimming goggle quarterly sales (in $000's) given below.

We calculate the three-period moving averages for a time series for all time periods except the:

To calculate the five-period moving average of a time series for a given time period, we average the value in that time period and the values in the four preceding periods.

Which of the following is true?

A 5 period moving average will show less fluctuation than a 3 period moving average, for the same time series.

One measure of the accuracy of a forecasting model is the:

We compute the five-period moving averages for all time periods except the first two and the last two.

In determining monthly seasonal indexes for petrol consumption, the sum of the 12 means for petrol consumption as a percentage of the moving average is 1230. To get the seasonal indexes, each of the 12 monthly means is to be multiplied by:

Of the four different components of a time series, cyclical variation is the one most likely to exhibit the long-term direction of the data.

In determining weekly seasonal indexes for natural gas consumption, the sum of the 52 means for gas consumption as a percentage of the moving average is 5195. To get the seasonal indexes, each monthly mean is to be multiplied by (5200 / 5195).

What Is Statistics

Types of Data, Data Collection and Sampling

Graphical Descriptive Methods Nominal Data

Graphical Descriptive Techniques Numerical Data

Numerical Descriptive Measures

Probability

Random Variables and Discrete Probability Distributions

Continuous Probability Distributions

Statistical Inference: Introduction

Sampling Distributions

Estimation: Describing a Single Population

Estimation: Comparing Two Populations

Hypothesis Testing: Describing a Single Population

Hypothesis Testing: Comparing Two Populations

Inference About Population Variances

Analysis of Variance

Additional Tests for Nominal Data: Chi-Squared Tests

Simple Linear Regression and Correlation

Multiple Regression

Model Building

Nonparametric Techniques

Statistical Inference: Conclusion

Index Numbers

Decision Analysis

Filters

Exam 23: Time-Series Analysis and Forecasting

The time-series component that reflects a wavelike pattern describing a long-term trend that is generally apparent over a number of years is called:

Seasonal variations will be present in a deseasonalised time series.

If autumn 2013 sales were $20 500 and the summer seasonal index was 1.17, then the deseasonalised 2010 autumn sales value would be:

A company selling swimming goggles wants to analyze the company's Australian sales figure. Describe the 4 components of the line graph of Swimming goggle quarterly sales (in $000's) given below.

We calculate the three-period moving averages for a time series for all time periods except the:

To calculate the five-period moving average of a time series for a given time period, we average the value in that time period and the values in the four preceding periods.

Which of the following is true?

A 5 period moving average will show less fluctuation than a 3 period moving average, for the same time series.

One measure of the accuracy of a forecasting model is the:

We compute the five-period moving averages for all time periods except the first two and the last two.

In determining monthly seasonal indexes for petrol consumption, the sum of the 12 means for petrol consumption as a percentage of the moving average is 1230. To get the seasonal indexes, each of the 12 monthly means is to be multiplied by:

Of the four different components of a time series, cyclical variation is the one most likely to exhibit the long-term direction of the data.

In determining weekly seasonal indexes for natural gas consumption, the sum of the 52 means for gas consumption as a percentage of the moving average is 5195. To get the seasonal indexes, each monthly mean is to be multiplied by (5200 / 5195).

What Is Statistics

Types of Data, Data Collection and Sampling

Graphical Descriptive Methods Nominal Data

Graphical Descriptive Techniques Numerical Data

Numerical Descriptive Measures

Probability

Random Variables and Discrete Probability Distributions

Continuous Probability Distributions

Statistical Inference: Introduction

Sampling Distributions

Estimation: Describing a Single Population

Estimation: Comparing Two Populations

Hypothesis Testing: Describing a Single Population

Hypothesis Testing: Comparing Two Populations

Inference About Population Variances

Analysis of Variance

Additional Tests for Nominal Data: Chi-Squared Tests

Simple Linear Regression and Correlation

Multiple Regression

Model Building

Nonparametric Techniques

Statistical Inference: Conclusion

Index Numbers

Decision Analysis

Filters