Question 1

A least squares linear trend line is just a simple regression line with the years recoded.

Accepted Answer

A) True 
 B)False

Question 2

Instruction 14-5
A contractor developed a multiplicative time-series model to forecast the number of contracts in future quarters, using quarterly data on number of contracts during the three-year period from 2008 to 2010. The following is the resulting regression equation:
$$\log _ { 10 } \hat { Y } = 3.37 + 0.117 X - 0.083 Q _ { 1 } + 1.28 Q _ { 2 } + 0.617 Q _ { 3 }$$
Where
$\hat { Y }$ is the estimated number of contracts in a quarter.
$X$ is the coded quarterly value with $X = 0$ in the first quarter of 2008 .
$Q _ { 1 }$ is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.
$Q _ { 2 }$ is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise.
$Q _ { 3 }$ is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise.
-Referring to Instruction 14-5,using the regression equation,which of the following values is the best forecast for the number of contracts in the third quarter of 2011?

Accepted Answer

A)  133,352 
B)  421,697 
C)  49,091 
D)  1,482,518 
A)  133,352 
B)  421,697 
C)  49,091 
D)  1,482,518

Question 3

Instruction 14-3
The number of cases of merlot wine sold by a Barossa Valley Winery in an eight-year period follows.
 $\begin{array}{ll}
\text { Year } &\text { Coses of }\
& \text { Wine } \
2003 & 270 \
2004 & 356 \
2005 & 398 \
2006 & 456 \
2007 & 358 \
2008 & 500 \
2009 & 410 \
2010 & 376
\end{array}$

-Referring to Instruction 14-3,a centred five-year moving average is to be constructed for the wine sales.The number of moving averages that will be calculated is_______.

Accepted Answer

The answer of Instruction 14-3
The number of cases of merlot...

Question 4

The more expensive commodities are overly influential in an unweighted aggregate price index.

Accepted Answer

A) True 
 B)False

Question 5

In the Holt-Winters method of forecasting,which of the following would give more weight to recent trend and less to past trend?

Accepted Answer

A)  Smaller values of V. 
B)  Larger values of V. 
C)  Larger values of U. 
D)  Smaller values of U. 
A)  Smaller values of V. 
B)  Larger values of V. 
C)  Larger values of U. 
D)  Smaller values of U.

Question 6

Laspeyres price index is a form of weighted aggregate price index.

Accepted Answer

A) True 
 B)False

Question 7

Instruction 14-12
The number of cases of chardonnay wine sold by a winery in an eight-year period follows.
 $$\begin{array} { | l | l | } 
\hline \text { Year } & \text { Case of Wine } \
\hline 2003 & 270 \
\hline 2004 & 356 \
\hline 2005 & 398 \
\hline 2006 & 456 \
\hline 2007 & 438 \
\hline 2008 & 478 \
\hline 2009 & 460 \
\hline 2010 & 480 \
\hline
\end{array}$$
-Referring to Instruction 14-12,set up a scatter diagram (i.e.,a time-series plot)with year on the horizontal X-axis.

Accepted Answer

The answer of Instruction 14-12
The number of cases of chardonnay...

Question 8

Unweighted aggregate price indexes account for differences in the magnitude of prices per unit and differences in the consumption levels of the items in the market basket.

Accepted Answer

A) True 
 B)False

Question 9

Instruction 14-6
A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the four-year period from 2005 to 2009. The following is the resulting regression equation:
$$\log _ { 10 } \hat { Y } = 6.102 + 0.012 X - 0.129 Q _ { 1 } - 0.054 Q _ { 2 } + 0.098 Q _ { 3 }$$
Where
$X$ is the coded quarterly value with $X = 0$ in the first quarter of 2005 .
$Q _ { 1 }$ is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.
$Q _ { 2 }$ is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise.
$Q _ { 3 }$ is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise.
-Referring to Instruction 14-6,to obtain a forecast for the first quarter of 2009 using the model,which of the following sets of values should be used in the regression equation?

Accepted Answer

A)  X = 16, Q1 = 1, Q2 = 0, Q3 = 0 
B)  X = 17, Q1 = 1, Q2 = 0, Q3 = 0 
C)  X = 17, Q1 = 0, Q2 = 1, Q3 = 0 
D)  X = 16, Q1 = 0, Q2 = 1, Q3 = 0 
A)  X = 16, Q1 = 1, Q2 = 0, Q3 = 0 
B)  X = 17, Q1 = 1, Q2 = 0, Q3 = 0 
C)  X = 17, Q1 = 0, Q2 = 1, Q3 = 0 
D)  X = 16, Q1 = 0, Q2 = 1, Q3 = 0

Question 10

Instruction 14-4
The number of train passengers arriving in Adelaide on the Overland on six successive Mondays were: 60, 72, 96, 84, 36 and 48.
-Referring to Instruction 14-4,the number of arrivals will be smoothed with a three-term moving average.The last smoothed value will be _______.

Accepted Answer

The answer of Instruction 14-4
The number of train passengers arriving...

Question 11

Instruction 14-19
Business closures in Perth from 2005 to 2010 were:
 $$\begin{array} { | l | l | } 
\hline 2005 & 10 \
\hline 2005 & 11 \
\hline 2007 & 13 \
\hline 2008 & 19 \
\hline 2009 & 24 \
\hline 2010 & 35 \
\hline
\end{array}$$ Microsoft Excel was used to fit both first-order and second-order autoregressive models, resulting in the following partial outputs:
 SIMMARY OUTIPU - Second-Order Mode
$\begin{array}{ll}
&\text { Coefficients }\
\text { Intercept } & -5.77 \
\text { X Variable 1 } & 0.80 \
\text { X Variable 2 } & 1.14
\end{array}$

SIMMARY OUTPUT - Fist-Order Model
 $\begin{array}{ll}
&\text { Coefficients }\
\text { Intercept } & -4.16 \
\text { X Variable 1 } & 1.59
\end{array}$
-Referring to Instruction 14-19,the fitted values for the second-order autoregressive model are _______,_______,_______,and _______.

Accepted Answer

14.43,17.1

Question 12

What type of forecasting is based entirely on the past and present values of a variable?

Accepted Answer

A)  Economic forecasting 
B)  Time-series forecasting 
C)  Casual forecasting 
D)  Qualitative forecasting 
A)  Economic forecasting 
B)  Time-series forecasting 
C)  Casual forecasting 
D)  Qualitative forecasting

Question 13

Instruction 14-21
Given below are the average prices for three types of energy products in Australia from 2006 to 2010.
 $$\begin{array} { | l | c | c | c | } 
\hline \text { Year } & \text { Electricity } & \text { Natural Gas } & \text { Fuel Oil } \
\hline 2006 & 43.205 & 25.893 & 0.892 \
\hline 2007 & 16.959 & 28.749 & 0.969 \
\hline 2008 & 47.202 & 28.933 & 1.034 \
\hline 2009 & 48.874 & 29.872 & 0.913 \
\hline 2010 & 48.693 & 28.384 & 0.983 \
\hline
\end{array}$$
-Referring to Instruction 14-21,what is the unweighted price index for the group of three energy items in 2009 using 2006 as the base year?

Accepted Answer

The answer of Instruction 14-21
Given below are the average prices...

Question 14

Instruction 14-6
A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the four-year period from 2005 to 2009. The following is the resulting regression equation:
$$\log _ { 10 } \hat { Y } = 6.102 + 0.012 X - 0.129 Q _ { 1 } - 0.054 Q _ { 2 } + 0.098 Q _ { 3 }$$
Where
$X$ is the coded quarterly value with $X = 0$ in the first quarter of 2005 .
$Q _ { 1 }$ is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.
$Q _ { 2 }$ is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise.
$Q _ { 3 }$ is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise.
-Referring to Instruction 14-6,the best interpretation of the coefficient of X (0.012)in the regression equation is:

Accepted Answer

A)  The annual growth rate in revenues is around 1.2%. 
B)  The quarterly growth rate in revenues is around 1.2%. 
C)  The quarterly compound growth rate in revenues is around 2.8%. 
D)  The annual growth rate in revenues is around 2.8%. 
A)  The annual growth rate in revenues is around 1.2%. 
B)  The quarterly growth rate in revenues is around 1.2%. 
C)  The quarterly compound growth rate in revenues is around 2.8%. 
D)  The annual growth rate in revenues is around 2.8%.

Question 15

The effect of an unpredictable,rare event will be contained in the _______ component.

Accepted Answer

A)  trend 
B)  cyclical 
C)  irregular 
D)  seasonal 
A)  trend 
B)  cyclical 
C)  irregular 
D)  seasonal

Question 16

Instruction 14-2
The following table contains the number of complaints received in a department store for the first six months of last year.
 $$\begin{array} { c c } 
\text { Month } & \text { Complaints } \
\text { January } & 36 \
\text { February } & 45 \
\text { March } & 81 \
\text { April } & 50 \
\text { May } & 108 \
\text { June } & 144
\end{array}$$
-Referring to Instruction 14-2,if a three-term moving average is used to smooth this series,how many values would it have?

Accepted Answer

A)  Five 
B)  Three 
C)  Two 
D)  Four 
A)  Five 
B)  Three 
C)  Two 
D)  Four

Question 17

Instruction 14-15
The number of train passengers arriving in Adelaide on the Overland on six successive Mondays were: 60, 72, 96, 84, 36 and 48.
-Referring to Instruction 14-15,the Holt-Winters method for forecasting with smoothing constant of 0.3 for both level and trend will be used to smooth the number of arrivals.The smoothed values of the level and trend for the second Monday are _______ and _______,respectively.

Accepted Answer

The answer of Instruction 14-15
The number of train passengers arriving...

Question 18

In selecting a forecasting model,you should perform a residual analysis.

Accepted Answer

A) True 
 B)False

Question 19

Instruction 14-10
The executive vice president of a drug manufacturing firm believes that the demand for the firm's most popular drug has been evidencing an exponential trend since 1995. She uses Microsoft Excel to obtain the partial output below. The dependent variable is the log base 10 of the demand for the drug, while the independent variable is years, where 1995 is coded as 0, 1996 is coded as 1, etc.
 $$\begin{array} { l l } 
\text { PuMMaression Statistics } & \
\text { MultipleR } & 0.996 \
\text { R Square } & 0.992 \
\text { Adjusted R Square } & 0.991 \
\text { Standard Error } & 0.02831 \
\text { Observations } & 12 \
& \
& \text { Coefiñients } \
\text { Intercept } & 1.44 \
\text { Coded Year } & 0.068
\end{array}$$
-Referring to Instruction 14-10,the forecast for the demand in 2012 is _______

Accepted Answer

The answer of Instruction 14-10
The executive vice president of a...

Question 20

Based on the following scatter plot,which of the time-series components is not present in this quarterly time series?

Accepted Answer

A)  Irregular 
B)  Trend 
C)  Cyclical 
D)  Seasonal 
A)  Irregular 
B)  Trend 
C)  Cyclical 
D)  Seasonal

A least squares linear trend line is just a simple regression line with the years recoded.

The more expensive commodities are overly influential in an unweighted aggregate price index.

In the Holt-Winters method of forecasting,which of the following would give more weight to recent trend and less to past trend?

Laspeyres price index is a form of weighted aggregate price index.

Unweighted aggregate price indexes account for differences in the magnitude of prices per unit and differences in the consumption levels of the items in the market basket.

Instruction 14-4 The number of train passengers arriving in Adelaide on the Overland on six successive Mondays were: 60, 72, 96, 84, 36 and 48. -Referring to Instruction 14-4,the number of arrivals will be smoothed with a three-term moving average.The last smoothed value will be _______.

What type of forecasting is based entirely on the past and present values of a variable?

The effect of an unpredictable,rare event will be contained in the _______ component.

In selecting a forecasting model,you should perform a residual analysis.

Based on the following scatter plot,which of the time-series components is not present in this quarterly time series?

Defining and Collecting Data

Organising and Visualising Data

Numerical Descriptive Measures

Basic Probability

Some Important Discrete Probability Distributions

The Normal Distribution and Other Continuous Distributions

Sampling Distributions

Confidence Interval Estimation

Fundamentals of Hypothesis Testing: One-Sample Tests

Hypothesis Testing: Two-Sample Tests

Analysis of Variance

Simple Linear Regression

Introduction to Multiple Regression

Chi-Square Tests

Multiple Regression Model Building

Decision Making

Statistical Applications in Quality Management

Further Non-Parametric Tests

Filters

Exam 14: Time-Series Forecasting and Index Numbers

A least squares linear trend line is just a simple regression line with the years recoded.

The more expensive commodities are overly influential in an unweighted aggregate price index.

In the Holt-Winters method of forecasting,which of the following would give more weight to recent trend and less to past trend?

Laspeyres price index is a form of weighted aggregate price index.

Unweighted aggregate price indexes account for differences in the magnitude of prices per unit and differences in the consumption levels of the items in the market basket.

Instruction 14-4 The number of train passengers arriving in Adelaide on the Overland on six successive Mondays were: 60, 72, 96, 84, 36 and 48. -Referring to Instruction 14-4,the number of arrivals will be smoothed with a three-term moving average.The last smoothed value will be _______.

What type of forecasting is based entirely on the past and present values of a variable?

The effect of an unpredictable,rare event will be contained in the _______ component.

In selecting a forecasting model,you should perform a residual analysis.

Based on the following scatter plot,which of the time-series components is not present in this quarterly time series?

Defining and Collecting Data

Organising and Visualising Data

Numerical Descriptive Measures

Basic Probability

Some Important Discrete Probability Distributions

The Normal Distribution and Other Continuous Distributions

Sampling Distributions

Confidence Interval Estimation

Fundamentals of Hypothesis Testing: One-Sample Tests

Hypothesis Testing: Two-Sample Tests

Analysis of Variance

Simple Linear Regression

Introduction to Multiple Regression

Chi-Square Tests

Multiple Regression Model Building

Decision Making

Statistical Applications in Quality Management

Further Non-Parametric Tests

Filters