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? \[\begin{array} { | l | l | l | l | l | l | l | } \hline \text { Period } & 1 & 2 & 3 & 4 & 5 & 6 \\ \hline \text { Value } & 136 & 126 & - 146 & - 148 & - 156 & 164 \\ \hline \end{array}\]

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 B

A time series with forecast values and error terms is presented in the following table.The mean squared error (MSE)for this forecast is ___________. $\begin{array}{|r|r|r|r|} \hline \text { Monthh } & \text { Actual } & \text { Forecast} & \text { Error } \\ \hline \text { July } & 5 & & \\ \hline \text { Aug } & 11 & 5 & 6.00 \\ \hline \text { Sept } & 13 & 6.8 & 6.20 \\ \hline \text { Oct } & 6 & 8.66 & -2.66 \\ \hline \text { Nov } & 5 & 7.862 & -2.86 \\ \hline \end{array}$

A) 13.33 B) 17.94 C) 89.71 D) 22.43 E) 32.34 A) 13.33 B) 17.94 C) 89.71 D) 22.43 E) 32.34

A time series with forecast values is presented in the following table: \[\begin{array} { | r | r | r | } \hline \text { Month } & \text { Actual } & \text { Forecast } \\ \hline \text { Jan } & 1 & \\ \hline \text { Mar } & 1.2 & * \\ \hline \text { May } & 1.15 & * \\ \hline \text { Jul } & 1.25 & * \\ \hline \text { Sep } & 1.3 & * \\ \hline \text { Nov } & 1.275 & x \\ \hline \end{array}\] If the mean square error (MSE)until September is 0.01125, and the overall MSE is 0.010125, Then x = ______.

A) 1.15 B) 1.25 C) 1.3 D) 1.25 or 1.3 E) 1.2 or 1.35 A) 1.15 B) 1.25 C) 1.3 D) 1.25 or 1.3 E) 1.2 or 1.35

A time series with forecast values is presented in the following table: \[\begin{array} { | r | r | r | } \hline \text { Month } & \text { Actual. } & \text { Forecast } \\ \hline J a n & a & \\ \hline \text { Mar } & 12 a & 1.1 a \\ \hline \text { May} & 1.15 a & 1.2 a \\ \hline J ul & 1.25 a & 12.21 a \\ \hline \mathrm { Sep } & 1.3 a & 1.25 a \\ \hline \end{array}\] On this table, a is some nondisclosed value.The mean absolute deviation (MAD) Is ______% of a.

A) 6a B) 0.06a C) 6 D) 0.06 E) 4.8 A) 6a B) 0.06a C) 6 D) 0.06 E) 4.8

Using a three-month moving average, the forecast value for November in the following time series is ____________. \[\begin{array} { | r | r | } \hline \text { July } & 5 \\ \hline \text { Amg } & 11 \\ \hline \text { Sent } & 13 \\ \hline \text { Oct } & 6 \\ \hline \end{array}\]

A) 11.60 B) 10.00 C) 9.67 D) 8.60 E) 6.00 A) 11.60 B) 10.00 C) 9.67 D) 8.60 E) 6.00

Exam 15: Time-Series Forecasting and Index Numbers

The forecast value for July was 210 and the actual value turned out to be 195.The researcher is using exponential smoothing and determines that the forecast value for August is 206.25.Then he is using α = ______.

Free

(Multiple Choice)

4.9/5

(38)

Question 1

Correct Answer:

Verified

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

Free

(True/False)

4.8/5

(42)

Question 2

Correct Answer:

Verified

False

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? Period 1 2 3 4 5 6 Value 136 126 -146 -148 -156 164

Free

(Multiple Choice)

4.8/5

(27)

Question 3

Correct Answer:

Verified

The city golf course is interested in starting a junior golf program.The golf pro has collected data on the number of youths under 13 that have played golf during the last 4 months.Using a three-month moving average (with weights of 5, 3, and 1 for the most current value, next most current value and oldest value, respectively), the forecast value for November in the following time series would be ____________. Joly 28 Ang 27 Sept 17 Oct 19

(Multiple Choice)

4.8/5

(43)

Question 4

A time series with forecast values and error terms is presented in the following table.The mean squared error (MSE)for this forecast is ___________. Monthh Actual Forecast Error July 5 Aug 11 5 6.00 Sept 13 6.8 6.20 Oct 6 8.66 -2.66 Nov 5 7.862 -2.86

(Multiple Choice)

4.8/5

(31)

Question 5

Which of the following is not a component of time series data?

(Multiple Choice)

4.8/5

(35)

Question 6

A time series analysis was performed to determine the number of new online customers that joined the 'Jelly of the Month Club'.The actual number of new customers, the forecast values and the error terms are presented in the following table.The mean absolute deviation (MAD)for this forecast is ___________. Monthh Actual Forecast Error July 4 Aug 6 5 -1 Sept 3 6 3 Oct 9 8 -1 Nov 8 9 1

(Multiple Choice)

4.9/5

(35)

Question 7

Index numbers are used to compare various time frame measures to a base time period measure.

(True/False)

4.8/5

(36)

Question 8

Fitting a linear trend to 36 monthly data points (January 2011 = 1, February 2011 =2, March 2011 = 3, etc.)produced the following tables. The projected trend value for January 2014 is ________.

(Multiple Choice)

4.9/5

(21)

Question 9

A time series with forecast values is presented in the following table: Month Actual Forecast Jan 1 Mar 1.2 * May 1.15 * Jul 1.25 * Sep 1.3 * Nov 1.275 x If the mean square error (MSE)until September is 0.01125, and the overall MSE is 0.010125, Then x = ______.

(Multiple Choice)

4.7/5

(40)

Question 10

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

(True/False)

4.9/5

(49)

Question 11

If autocorrelation occurs in regression analysis, then the confidence intervals and tests using the t and F distributions are no longer strictly applicable.

(True/False)

4.8/5

(34)

Question 12

Jim Royo, Manager of Billings Building Supply (BBS), wants to develop a model to forecast BBS's monthly sales (in $1,000's).He selects the dollar value of residential building permits (in $10,000)as the predictor variable.An analysis of the data yielded the following tables. $Jim Royo, Manager of Billings Building Supply (BBS), wants to develop a model to forecast BBS's monthly sales (in $1,000's).He selects the dollar value of residential building permits (in $10,000)as the predictor variable.An analysis of the data yielded the following tables. Jim's calculated value for the Durbin-Watson statistic is 1.93.Using \alpha = 0.05, the appropriate decision is: _____.$ $Jim Royo, Manager of Billings Building Supply (BBS), wants to develop a model to forecast BBS's monthly sales (in $1,000's).He selects the dollar value of residential building permits (in $10,000)as the predictor variable.An analysis of the data yielded the following tables. Jim's calculated value for the Durbin-Watson statistic is 1.93.Using \alpha = 0.05, the appropriate decision is: _.$ Jim's calculated value for the Durbin-Watson statistic is 1.93.Using $\alpha$ = 0.05, the appropriate decision is: _____.

(Multiple Choice)

4.9/5

(28)

Question 13

A time series with forecast values is presented in the following table: Month Actual. Forecast Jan a Mar 12a 1.1a May 1.15a 1.2a Jul 1.25a 12.21a 1.3a 1.25a On this table, a is some nondisclosed value.The mean absolute deviation (MAD) Is ______% of a.

(Multiple Choice)

4.8/5

(34)

Question 14

Unweighted price indexes can only compare across the entire successive time period for which there is data.

(True/False)

4.8/5

(30)

Question 15

If the Year_t Quarter_q actual value is 9,885 and the Year_t Quarter_q deseasonalized value is 10,112.53, then the Year_t Quarter_q seasonal index is ______.

(Multiple Choice)

4.9/5

(32)

Question 16

When the error terms of a regression forecasting model are correlated the problem of autocorrelation occurs.

(True/False)

4.9/5

(39)

Question 17

Using a three-month moving average (with weights of 6, 3, and 1 for the most current value, next most current value and oldest value, respectively), the forecast value for November in the following time series is ____________. July 5 Amg 11 Sent 13 Oct 6

(Multiple Choice)

4.8/5

(31)

Question 18

Using a three-month moving average (with weights of 6, 3, and 1 for the most current value, next most current value and oldest value, respectively), the forecast value for October made at the end of September in the following time series would be__________. July 5 Amg 11 Sent 13 Oct 6

(Multiple Choice)

4.7/5

(37)

Question 19

Using a three-month moving average, the forecast value for November in the following time series is ____________. July 5 Amg 11 Sent 13 Oct 6

(Multiple Choice)

4.8/5

(35)

Question 20

Showing 1 - 20 of 103

The forecast value for July was 210 and the actual value turned out to be 195.The researcher is using exponential smoothing and determines that the forecast value for August is 206.25.Then he is using α = ______.

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

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? Period 1 2 3 4 5 6 Value 136 126 -146 -148 -156 164

A time series with forecast values and error terms is presented in the following table.The mean squared error (MSE)for this forecast is ___________. Monthh Actual Forecast Error July 5 Aug 11 5 6.00 Sept 13 6.8 6.20 Oct 6 8.66 -2.66 Nov 5 7.862 -2.86

Which of the following is not a component of time series data?

Index numbers are used to compare various time frame measures to a base time period measure.

Fitting a linear trend to 36 monthly data points (January 2011 = 1, February 2011 =2, March 2011 = 3, etc.)produced the following tables. The projected trend value for January 2014 is ________.

A time series with forecast values is presented in the following table: Month Actual Forecast Jan 1 Mar 1.2 * May 1.15 * Jul 1.25 * Sep 1.3 * Nov 1.275 x If the mean square error (MSE)until September is 0.01125, and the overall MSE is 0.010125, Then x = ______.

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

If autocorrelation occurs in regression analysis, then the confidence intervals and tests using the t and F distributions are no longer strictly applicable.

A time series with forecast values is presented in the following table: Month Actual. Forecast Jan a Mar 12a 1.1a May 1.15a 1.2a Jul 1.25a 12.21a 1.3a 1.25a On this table, a is some nondisclosed value.The mean absolute deviation (MAD) Is ______% of a.

Unweighted price indexes can only compare across the entire successive time period for which there is data.

If the Year_t Quarter_q actual value is 9,885 and the Year_t Quarter_q deseasonalized value is 10,112.53, then the Year_t Quarter_q seasonal index is ______.

When the error terms of a regression forecasting model are correlated the problem of autocorrelation occurs.

Using a three-month moving average (with weights of 6, 3, and 1 for the most current value, next most current value and oldest value, respectively), the forecast value for November in the following time series is ____________. July 5 Amg 11 Sent 13 Oct 6

Using a three-month moving average (with weights of 6, 3, and 1 for the most current value, next most current value and oldest value, respectively), the forecast value for October made at the end of September in the following time series would be__________. July 5 Amg 11 Sent 13 Oct 6

Using a three-month moving average, the forecast value for November in the following time series is ____________. July 5 Amg 11 Sent 13 Oct 6

Introduction to Statistics and Business Analytics

Visualizing Data With 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

The forecast value for July was 210 and the actual value turned out to be 195.The researcher is using exponential smoothing and determines that the forecast value for August is 206.25.Then he is using α = ______.

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

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? Period 1 2 3 4 5 6 Value 136 126 -146 -148 -156 164

A time series with forecast values and error terms is presented in the following table.The mean squared error (MSE)for this forecast is ___________. Monthh Actual Forecast Error July 5 Aug 11 5 6.00 Sept 13 6.8 6.20 Oct 6 8.66 -2.66 Nov 5 7.862 -2.86

Which of the following is not a component of time series data?

Index numbers are used to compare various time frame measures to a base time period measure.

Fitting a linear trend to 36 monthly data points (January 2011 = 1, February 2011 =2, March 2011 = 3, etc.)produced the following tables. The projected trend value for January 2014 is ________.

A time series with forecast values is presented in the following table: Month Actual Forecast Jan 1 Mar 1.2 * May 1.15 * Jul 1.25 * Sep 1.3 * Nov 1.275 x If the mean square error (MSE)until September is 0.01125, and the overall MSE is 0.010125, Then x = ______.

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

If autocorrelation occurs in regression analysis, then the confidence intervals and tests using the t and F distributions are no longer strictly applicable.

A time series with forecast values is presented in the following table: Month Actual. Forecast Jan a Mar 12a 1.1a May 1.15a 1.2a Jul 1.25a 12.21a 1.3a 1.25a On this table, a is some nondisclosed value.The mean absolute deviation (MAD) Is ______% of a.

Unweighted price indexes can only compare across the entire successive time period for which there is data.

If the Yeart Quarterq actual value is 9,885 and the Yeart Quarterq deseasonalized value is 10,112.53, then the Yeart Quarterq seasonal index is ______.

When the error terms of a regression forecasting model are correlated the problem of autocorrelation occurs.

Using a three-month moving average (with weights of 6, 3, and 1 for the most current value, next most current value and oldest value, respectively), the forecast value for November in the following time series is ____________. July 5 Amg 11 Sent 13 Oct 6

Using a three-month moving average (with weights of 6, 3, and 1 for the most current value, next most current value and oldest value, respectively), the forecast value for October made at the end of September in the following time series would be__________. July 5 Amg 11 Sent 13 Oct 6

Using a three-month moving average, the forecast value for November in the following time series is ____________. July 5 Amg 11 Sent 13 Oct 6

Introduction to Statistics and Business Analytics

Visualizing Data With 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

If the Year_t Quarter_q actual value is 9,885 and the Year_t Quarter_q deseasonalized value is 10,112.53, then the Year_t Quarter_q seasonal index is ______.