Consider the following data and calculate S1 using simple exponential smoothing and = 0.3.

\[\begin{array} { c c } \text { Time }

Exam 16: Time Series Forecasting and Index Numbers

Assume that the current date is February 1,2003.The linear regression model was applied to a monthly time series based on the last 24 months' sales (from January 2000 through December 2002).The following partial computer output summarizes the results. Coefficient Estimate Intercept 4.3 2.07 Slope 1.6 2.98 Determine the predicted sales for this month.

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Question 1

Correct Answer:

Verified

A

Given the following data,compute the total error (sum of the error terms).

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Question 2

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$\begin{array} { | l | l | l | } \hline \text { Week } & \text { Sales } & \text { Forecasted Sales } \\\hline 1 & 22 & 22.719 \\\hline 2 & 27 & 27.117 \\\hline 3 & 23 & 31.515 \\\hline 4 & 31 & 35.913 \\\hline 5 & 45 & 40.311 \\\hline 6 & 47 & 44.709 \\\hline 7 & 45 & 49.107 \\\hline 8 & 42 & 53.505 \\\hline\end{array}$
22.896
Feedback: $\begin{array} { | l | l | l | } \hline \text { Error } & \text { Sales } & \text { Forecasted Sales } \\\hline .719 & 22 & 22.719 \\\hline .117 & 27 & 27.117 \\\hline 8.515 & 23 & 31.515 \\\hline 4.913 & 31 & 35.913 \\\hline - 4.689 & 45 & 40.311 \\\hline - 2.291 & 47 & 44.709 \\\hline 4.107 & 45 & 49.107 \\\hline 11.505 & 42 & 53.505 \\\hline 22.896 & & \\\hline\end{array}$

When a forecaster uses a multiplicative decomposition model or time series regression model,she or he assumes that the time series components are changing over time.

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Question 3

Correct Answer:

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False

The demand for a product for the last six years has been 15,15,17,18,20,and 19.The manager wants to predict the demand for this time series using the following simple linear trend equation: tr_t = 12 + 2t.What are the forecast errors for the 5^th and 6^th years?

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Question 4

The ___________ component of a time series refers to the erratic time series movements that follow no recognizable or regular pattern.

(Multiple Choice)

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Question 5

The linear regression trend model was applied to a time series sales data set based on the last 24 months' sales.The following partial computer output was obtained.

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Question 6

Given the following data,compute the mean absolute deviation.

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Question 7

The price and quantity of several food items are listed below for the years 1990 and 2000.

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Question 8

Since a(n)____________ index employs the base-period quantities in all succeeding periods,it allows for ready comparisons for identical quantities of goods purchased between the base period and all succeeding periods.

(Multiple Choice)

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Question 9

A simple index is obtained by dividing the current value of a time series by the value of a time series in the _____________ time period and by multiplying this ratio by 100.

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Question 10

A time series decomposition method would not be used to forecast seasonal data.

(True/False)

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Question 11

If the errors produced by a forecasting method for 3 observations are +3,+3,and -3,then what is the mean absolute deviation?

(Multiple Choice)

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Question 12

If a time series exhibits increasing seasonal variation,one approach is to first use a ______ transformation that produces a transformed time series that exhibits constant seasonal variation.Then,_ variables can be used to model the time series with constant seasonal variation.

(Multiple Choice)

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Question 13

Consider the following data and calculate S₁ using simple exponential smoothing and = 0.3.

(Essay)

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Question 14

The following data on prices and quantities for the years 1995 and 2000 are given for three products.

(Essay)

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Question 15

A simple index is computed by using the values of one time series,while a(n)___________ index is based on a "market basket" consisting of more than one time series.

(Multiple Choice)

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Question 16

When deseasonalizing a time series observation,we divide the actual time series observation by its ___________.

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Question 17

Use the following price information for three grains.

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Question 18

A restaurant has been experiencing higher sales during the weekends,compared to the weekdays.Daily restaurant sales patterns for this restaurant over a week are an example of a(n)_________ component of a time series.

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Question 19

For monthly seasonal data,we define the nonseasonal level of the Sample Autocorrelation Function (SAC)to be lags 12 and 24.

(True/False)

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Question 20

Given the following data,compute the total error (sum of the error terms).

When a forecaster uses a multiplicative decomposition model or time series regression model,she or he assumes that the time series components are changing over time.

The demand for a product for the last six years has been 15,15,17,18,20,and 19.The manager wants to predict the demand for this time series using the following simple linear trend equation: tr_t = 12 + 2t.What are the forecast errors for the 5^th and 6^th years?

The ___________ component of a time series refers to the erratic time series movements that follow no recognizable or regular pattern.

The linear regression trend model was applied to a time series sales data set based on the last 24 months' sales.The following partial computer output was obtained.

Given the following data,compute the mean absolute deviation.

The price and quantity of several food items are listed below for the years 1990 and 2000.

Since a(n)____________ index employs the base-period quantities in all succeeding periods,it allows for ready comparisons for identical quantities of goods purchased between the base period and all succeeding periods.

A simple index is obtained by dividing the current value of a time series by the value of a time series in the _____________ time period and by multiplying this ratio by 100.

A time series decomposition method would not be used to forecast seasonal data.

If the errors produced by a forecasting method for 3 observations are +3,+3,and -3,then what is the mean absolute deviation?

If a time series exhibits increasing seasonal variation,one approach is to first use a ______ transformation that produces a transformed time series that exhibits constant seasonal variation.Then,_ variables can be used to model the time series with constant seasonal variation.

Consider the following data and calculate S₁ using simple exponential smoothing and = 0.3.

The following data on prices and quantities for the years 1995 and 2000 are given for three products.

A simple index is computed by using the values of one time series,while a(n)___________ index is based on a "market basket" consisting of more than one time series.

When deseasonalizing a time series observation,we divide the actual time series observation by its ___________.

Use the following price information for three grains.

A restaurant has been experiencing higher sales during the weekends,compared to the weekdays.Daily restaurant sales patterns for this restaurant over a week are an example of a(n)_________ component of a time series.

For monthly seasonal data,we define the nonseasonal level of the Sample Autocorrelation Function (SAC)to be lags 12 and 24.

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Chi-Square Tests

Simple Linear Regression Analysis

Multiple Regression and Model Building

Process Improvement Using Control Charts

Nonparametric Methods

Decision Theory

Filters

Exam 16: Time Series Forecasting and Index Numbers

Given the following data,compute the total error (sum of the error terms).

When a forecaster uses a multiplicative decomposition model or time series regression model,she or he assumes that the time series components are changing over time.

The demand for a product for the last six years has been 15,15,17,18,20,and 19.The manager wants to predict the demand for this time series using the following simple linear trend equation: trt = 12 + 2t.What are the forecast errors for the 5th and 6th years?

The ___________ component of a time series refers to the erratic time series movements that follow no recognizable or regular pattern.

The linear regression trend model was applied to a time series sales data set based on the last 24 months' sales.The following partial computer output was obtained.

Given the following data,compute the mean absolute deviation.

The price and quantity of several food items are listed below for the years 1990 and 2000.

Since a(n)____________ index employs the base-period quantities in all succeeding periods,it allows for ready comparisons for identical quantities of goods purchased between the base period and all succeeding periods.

A simple index is obtained by dividing the current value of a time series by the value of a time series in the _____________ time period and by multiplying this ratio by 100.

A time series decomposition method would not be used to forecast seasonal data.

If the errors produced by a forecasting method for 3 observations are +3,+3,and -3,then what is the mean absolute deviation?

If a time series exhibits increasing seasonal variation,one approach is to first use a ______________ transformation that produces a transformed time series that exhibits constant seasonal variation.Then,_________ variables can be used to model the time series with constant seasonal variation.

Consider the following data and calculate S1 using simple exponential smoothing and = 0.3.

The following data on prices and quantities for the years 1995 and 2000 are given for three products.

A simple index is computed by using the values of one time series,while a(n)___________ index is based on a "market basket" consisting of more than one time series.

When deseasonalizing a time series observation,we divide the actual time series observation by its ___________.

Use the following price information for three grains.

A restaurant has been experiencing higher sales during the weekends,compared to the weekdays.Daily restaurant sales patterns for this restaurant over a week are an example of a(n)_________ component of a time series.

For monthly seasonal data,we define the nonseasonal level of the Sample Autocorrelation Function (SAC)to be lags 12 and 24.

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Chi-Square Tests

Simple Linear Regression Analysis

Multiple Regression and Model Building

Process Improvement Using Control Charts

Nonparametric Methods

Decision Theory

Filters

The demand for a product for the last six years has been 15,15,17,18,20,and 19.The manager wants to predict the demand for this time series using the following simple linear trend equation: tr_t = 12 + 2t.What are the forecast errors for the 5^th and 6^th years?

If a time series exhibits increasing seasonal variation,one approach is to first use a ______ transformation that produces a transformed time series that exhibits constant seasonal variation.Then,_ variables can be used to model the time series with constant seasonal variation.

Consider the following data and calculate S₁ using simple exponential smoothing and = 0.3.