Question 1

Using 2008 as the base year,the 2007 value of the Paasche' Price Index is ___.

Accepted Answer

A) 99.79 
B) 192.51 
C) 100.29 
D) 59.19 
E) 39.99 
A) 99.79 
B) 192.51 
C) 100.29 
D) 59.19 
E) 39.99

Question 2

What is the forecast for the Period 7 using a 3-period moving average technique,given the following time-series data for six past periods?

Accepted Answer

A) 164.67 
B) 156.00 
C) 148.00 
D) 126.57 
E) 158.67 
A) 164.67 
B) 156.00 
C) 148.00 
D) 126.57 
E) 158.67

Question 3

One of the main techniques for isolating the effects of seasonality is reconstitution.

Accepted Answer

A) True 
 B)False

Question 4

Determine trend in time-series data by using linear regression trend analysis,quadratic model trend analysis,and Holt's two-parameter exponential smoothing method.

Accepted Answer

Regression analysis with either linear o

Question 5

A stationary time-series data has only trend but no cyclical or seasonal effects.

Accepted Answer

A) True 
 B)False

Question 6

One of the main techniques for isolating the effects of seasonality is decomposition.

Accepted Answer

A) True 
 B)False

Question 7

Two popular general categories of smoothing techniques are exponential models and logarithmic models.

Accepted Answer

A) True 
 B)False

Question 8

A time series with forecast values and error terms is presented in the following table.The mean absolute deviation (MAD)for this forecast is ___.

Accepted Answer

A) 3.10 
B) 12.40 
C) 2.48 
D) 6.67 
E) 5.10 
A) 3.10 
B) 12.40 
C) 2.48 
D) 6.67 
E) 5.10

Question 9

When forecasting with exponential smoothing,data from previous periods is ___.

Accepted Answer

A) given equal importance 
B) given exponentially increasing importance 
C) ignored 
D) given exponentially decreasing importance 
E) linearly decreasing importance 
A) given equal importance 
B) given exponentially increasing importance 
C) ignored 
D) given exponentially decreasing importance 
E) linearly decreasing importance

Question 10

Weighted aggregate price indexes are also known as ___.

Accepted Answer

A) unbalanced indexes 
B) balanced indexes 
C) value indexes 
D) multiplicative indexes 
E) overall indexes 
A) unbalanced indexes 
B) balanced indexes 
C) value indexes 
D) multiplicative indexes 
E) overall indexes

Question 11

An exponential smoothing technique in which the smoothing constant alpha is equal to one is equivalent to a naïve forecasting model.

Accepted Answer

A) True 
 B)False

Question 12

One of the ways to overcome the autocorrelation problem in a regression forecasting model is to increase the level of significance for the F test

Accepted Answer

A) True 
 B)False

Question 13

Fitting a linear trend to 36 monthly data points (January 2000 = 1,February 2000 = 2,March 2000 = 3,etc. )produced the following tables:     The projected trend value for January 2003 is ___.

Accepted Answer

A) 231.39 
B) 555.71 
C) 339.50 
D) 447.76 
E) 355.71 
A) 231.39 
B) 555.71 
C) 339.50 
D) 447.76 
E) 355.71

Question 14

Typically,the denominator used to calculate an index number is a measurement for the ___ period.

Accepted Answer

A) base 
B) current 
C) spanning 
D) intermediate 
E) peak 
A) base 
B) current 
C) spanning 
D) intermediate 
E) peak

Question 15

A time series with forecast values and error terms is presented in the following table.The mean squared error (MSE)for this forecast is ___.

Accepted Answer

A) 8.86 
B) 44.31 
C) 3.28 
D) 11.08 
E) 28.01 
A) 8.86 
B) 44.31 
C) 3.28 
D) 11.08 
E) 28.01

Question 16

One of the ways to overcome the autocorrelation problem in a regression forecasting model is to transform the variables by taking the first-order differences.

Accepted Answer

A) True 
 B)False

Question 17

The following graph of a time-series data suggests a ___ trend.

Accepted Answer

A) linear 
B) tangential 
C) cosine 
D) quadratic 
E) flat 
A) linear 
B) tangential 
C) cosine 
D) quadratic 
E) flat

Question 18

Account for seasonal effects of time-series data by using decomposition and Winters' three-parameter exponential smoothing method.

Accepted Answer

Decomposition is a method for

Question 19

Using a three-month moving average,the forecast value for October made at the end of September in the following time series would be ___.

Accepted Answer

A) 7.67 
B) 8 
C) 9 
D) 6.89 
E) 7.25 
A) 7.67 
B) 8 
C) 9 
D) 6.89 
E) 7.25

Question 20

The forecast value for August was 12 and the actual value turned out to be 5.Using exponential smoothing with $\alpha$ = 0.20,the forecast value for September would be ___.

Accepted Answer

A) 10.10 
B) 9.88 
C) 12.00 
D) 10.6 
E) 11 
A) 10.10 
B) 9.88 
C) 12.00 
D) 10.6 
E) 11

Using 2008 as the base year,the 2007 value of the Paasche' Price Index is ___.

What is the forecast for the Period 7 using a 3-period moving average technique,given the following time-series data for six past periods?

One of the main techniques for isolating the effects of seasonality is reconstitution.

Determine trend in time-series data by using linear regression trend analysis,quadratic model trend analysis,and Holt's two-parameter exponential smoothing method.

A stationary time-series data has only trend but no cyclical or seasonal effects.

One of the main techniques for isolating the effects of seasonality is decomposition.

Two popular general categories of smoothing techniques are exponential models and logarithmic models.

A time series with forecast values and error terms is presented in the following table.The mean absolute deviation (MAD)for this forecast is ___.

When forecasting with exponential smoothing,data from previous periods is ___.

Weighted aggregate price indexes are also known as ___.

An exponential smoothing technique in which the smoothing constant alpha is equal to one is equivalent to a naïve forecasting model.

One of the ways to overcome the autocorrelation problem in a regression forecasting model is to increase the level of significance for the F test

Fitting a linear trend to 36 monthly data points (January 2000 = 1,February 2000 = 2,March 2000 = 3,etc. )produced the following tables: The projected trend value for January 2003 is ___.

Typically,the denominator used to calculate an index number is a measurement for the ___ period.

A time series with forecast values and error terms is presented in the following table.The mean squared error (MSE)for this forecast is ___.

One of the ways to overcome the autocorrelation problem in a regression forecasting model is to transform the variables by taking the first-order differences.

The following graph of a time-series data suggests a ___ trend.

Account for seasonal effects of time-series data by using decomposition and Winters' three-parameter exponential smoothing method.

Using a three-month moving average,the forecast value for October made at the end of September in the following time series would be ___.

The forecast value for August was 12 and the actual value turned out to be 5.Using exponential smoothing with $\alpha$ = 0.20,the forecast value for September would be ___.

Introduction to Statistics

Charts and Graphs

Descriptive Statistics

Probability

Discrete Distributions

Continuous Distributions

Sampling and Sampling Distributions

Statistical Inference: Estimation for Single Populations

Statistical Inference: Hypothesis Testing for Single Populations

Statistical Inferences About Two Populations

Analysis of Variance and Design of Experiments

Simple Regression Analysis and Correlation

Multiple Regression Analysis

Building Multiple Regression Models

Analysis of Categorical Data

Nonparametric Statistics

Statistical Quality Control

Decision Analysis

Filters

Exam 15: Time-Series Forecasting and Index Numbers

Using 2008 as the base year,the 2007 value of the Paasche' Price Index is ___.

What is the forecast for the Period 7 using a 3-period moving average technique,given the following time-series data for six past periods?

One of the main techniques for isolating the effects of seasonality is reconstitution.

Determine trend in time-series data by using linear regression trend analysis,quadratic model trend analysis,and Holt's two-parameter exponential smoothing method.

A stationary time-series data has only trend but no cyclical or seasonal effects.

One of the main techniques for isolating the effects of seasonality is decomposition.

Two popular general categories of smoothing techniques are exponential models and logarithmic models.

A time series with forecast values and error terms is presented in the following table.The mean absolute deviation (MAD)for this forecast is ___.

When forecasting with exponential smoothing,data from previous periods is ___.

Weighted aggregate price indexes are also known as ___.

An exponential smoothing technique in which the smoothing constant alpha is equal to one is equivalent to a naïve forecasting model.

One of the ways to overcome the autocorrelation problem in a regression forecasting model is to increase the level of significance for the F test

Fitting a linear trend to 36 monthly data points (January 2000 = 1,February 2000 = 2,March 2000 = 3,etc. )produced the following tables: The projected trend value for January 2003 is ___.

Typically,the denominator used to calculate an index number is a measurement for the ___ period.

A time series with forecast values and error terms is presented in the following table.The mean squared error (MSE)for this forecast is ___.

One of the ways to overcome the autocorrelation problem in a regression forecasting model is to transform the variables by taking the first-order differences.

The following graph of a time-series data suggests a ___ trend.

Account for seasonal effects of time-series data by using decomposition and Winters' three-parameter exponential smoothing method.

Using a three-month moving average,the forecast value for October made at the end of September in the following time series would be ___.

The forecast value for August was 12 and the actual value turned out to be 5.Using exponential smoothing with α\alphaα = 0.20,the forecast value for September would be ___.

Introduction to Statistics

Charts and Graphs

Descriptive Statistics

Probability

Discrete Distributions

Continuous Distributions

Sampling and Sampling Distributions

Statistical Inference: Estimation for Single Populations

Statistical Inference: Hypothesis Testing for Single Populations

Statistical Inferences About Two Populations

Analysis of Variance and Design of Experiments

Simple Regression Analysis and Correlation

Multiple Regression Analysis

Building Multiple Regression Models

Analysis of Categorical Data

Nonparametric Statistics

Statistical Quality Control

Decision Analysis

Filters

The forecast value for August was 12 and the actual value turned out to be 5.Using exponential smoothing with $\alpha$ = 0.20,the forecast value for September would be ___.