Exam 16: Analyzing and Forecasting Time-Series Data

A company has developed a linear trend model to forecast monthly sales.The following data show the actual sales and the "fitted" sales for months 1-12. Based on these data,what is the value for the mean absolute deviation for months 1-12?

(Multiple Choice)

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Question 61

A company has developed a linear trend model to forecast monthly sales.The following data show the actual sales and the "fitted" sales for months 1-12. Based on these data,what is the mean square error for the linear trend model?

(Multiple Choice)

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Question 62

The Boxer Company has been in business since 1998.The following sales data are recorded by quarter for the years 2010-2012. The managers at the company wish to determine the seasonal indexes for each quarter during the year.The first step in the process is to remove the seasonal and random components.To do this,they will begin by computing a four-period moving average.They then compute the centered moving average.What is the next step in applying the multiplicative model?

(Multiple Choice)

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Question 63

A stockbroker at a large brokerage firm recently analyzed the combined annual profits for all firms in the airline industry.One time-series component that may have been present in these annual data was a seasonal component.

(True/False)

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Question 64

You are given the following linear trend model: F_t = 345.60 - 200.5(t).This model implies that in year 1,the dependent variable had a value of 145.1.

(True/False)

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Question 65

Large values of the Durbin-Watson d statistic indicate that positive autocorrelation among the forecast errors exists.

(True/False)

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Question 66

The time-series component that implies a long-term upward or downward pattern is called the trend component.

(True/False)

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Question 67

While virtually all time series exhibit a random component,not all time series exhibit other components.

(True/False)

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Question 68

Recently,a manager for a major retailer computed the following seasonal indexes: The manager then developed the following least squares trend model based on the past five years of quarterly data: = 200 + 11.5t.Based on this,the seasonally adjusted forecast for quarter 25,which is the winter quarter,is 489.11

(True/False)

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Question 69

Which of the following time-series components is almost always present in sales data for electronics companies?

(Multiple Choice)

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Question 70

The reason for using split samples in developing a forecasting model is to eliminate the potential for bias in the resulting model.

(True/False)

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Question 71

A company has developed a linear trend regression model based on 16 quarters of data.The independent variable is the measure of time (t = 1 thru 16 where quarter 1 is winter quarter,2 is spring,etc. ).The company has also developed seasonal indexes for each quarter as follows: The linear trend forecast equation is: = 120 + 56t. Given this information,what is the seasonally adjusted forecast for period 19?

(Multiple Choice)

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Question 72

In a single exponential smoothing model,finding the forecast value for each period requires having the actual and forecast values from the proceeding period.This is not possible for the first period,so for the first period one should use the actual value as the forecast value.

(True/False)

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Question 73

Which of the following is true about forecast bias?

(Multiple Choice)

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Question 74

If a forecasting model produces forecast errors (residuals)that are negatively correlated,then we expect a negative residual to be followed by another negative residual to be followed by another negative residual and so forth.

(True/False)

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Question 75

The All American Toy Company has a very seasonal sales pattern.Sales are high during the fall quarter,drop off substantially in the winter quarter and are more typical during spring and summer quarters.The following historical data exist for the past 16 quarters. Based on these data,develop a seasonally adjusted forecast for the four quarters of 2013 using a linear trend regression model.

(Essay)

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Question 76

The Baker's Candy Company has been in business for three years.The quarterly sales data for the company are shown as follows: Based on this information,the data reflect both a linear trend and seasonal components.

(True/False)

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Question 77

The following output is provided for a linear trend regression-based forecasting model based on 12 months of data: Suppose that the actual sales for months 13-15 are: 720,680,800.Given this,which of the following is the forecast bias value for months 13-15?

(Multiple Choice)

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Question 78

The forecasting interval is the unit of time for which forecasts are made.

(True/False)

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Question 79

You are given the following linear trend model: F_t = 345.60 - 200.5(t).The forecast for period 15 is approximately -2,662.

(True/False)

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Question 80

Showing 61 - 80 of 133

A company has developed a linear trend model to forecast monthly sales.The following data show the actual sales and the "fitted" sales for months 1-12. Based on these data,what is the value for the mean absolute deviation for months 1-12?

A company has developed a linear trend model to forecast monthly sales.The following data show the actual sales and the "fitted" sales for months 1-12. Based on these data,what is the mean square error for the linear trend model?

A stockbroker at a large brokerage firm recently analyzed the combined annual profits for all firms in the airline industry.One time-series component that may have been present in these annual data was a seasonal component.

You are given the following linear trend model: F_t = 345.60 - 200.5(t).This model implies that in year 1,the dependent variable had a value of 145.1.

Large values of the Durbin-Watson d statistic indicate that positive autocorrelation among the forecast errors exists.

The time-series component that implies a long-term upward or downward pattern is called the trend component.

While virtually all time series exhibit a random component,not all time series exhibit other components.

Which of the following time-series components is almost always present in sales data for electronics companies?

The reason for using split samples in developing a forecasting model is to eliminate the potential for bias in the resulting model.

In a single exponential smoothing model,finding the forecast value for each period requires having the actual and forecast values from the proceeding period.This is not possible for the first period,so for the first period one should use the actual value as the forecast value.

Which of the following is true about forecast bias?

If a forecasting model produces forecast errors (residuals)that are negatively correlated,then we expect a negative residual to be followed by another negative residual to be followed by another negative residual and so forth.

The Baker's Candy Company has been in business for three years.The quarterly sales data for the company are shown as follows: Based on this information,the data reflect both a linear trend and seasonal components.

The following output is provided for a linear trend regression-based forecasting model based on 12 months of data: Suppose that the actual sales for months 13-15 are: 720,680,800.Given this,which of the following is the forecast bias value for months 13-15?

The forecasting interval is the unit of time for which forecasts are made.

You are given the following linear trend model: F_t = 345.60 - 200.5(t).The forecast for period 15 is approximately -2,662.

The Where,Why,and How of Data Collection

Graphs,Charts and Tablesdescribing Your Data

Describing Data Using Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Introduction to Continuous Probability Distributions

Introduction to Sampling Distributions

Estimating Single Population Parameters

Introduction to Hypothesis Testing

Estimation and Hypothesis Testing for Two Population Parameters

Hypothesis Tests and Estimation for Population Variances

Analysis of Variance

Goodness-Of-Fit Tests and Contingency Analysis

Introduction to Linear Regression and Correlation Analysis

Multiple Regression Analysis and Model Building

Introduction to Nonparametric Statistics

Introduction to Quality and Statistical Process Control

Filters

Exam 16: Analyzing and Forecasting Time-Series Data

A company has developed a linear trend model to forecast monthly sales.The following data show the actual sales and the "fitted" sales for months 1-12. Based on these data,what is the value for the mean absolute deviation for months 1-12?

A company has developed a linear trend model to forecast monthly sales.The following data show the actual sales and the "fitted" sales for months 1-12. Based on these data,what is the mean square error for the linear trend model?

A stockbroker at a large brokerage firm recently analyzed the combined annual profits for all firms in the airline industry.One time-series component that may have been present in these annual data was a seasonal component.

You are given the following linear trend model: Ft = 345.60 - 200.5(t).This model implies that in year 1,the dependent variable had a value of 145.1.

Large values of the Durbin-Watson d statistic indicate that positive autocorrelation among the forecast errors exists.

The time-series component that implies a long-term upward or downward pattern is called the trend component.

While virtually all time series exhibit a random component,not all time series exhibit other components.

Which of the following time-series components is almost always present in sales data for electronics companies?

The reason for using split samples in developing a forecasting model is to eliminate the potential for bias in the resulting model.

In a single exponential smoothing model,finding the forecast value for each period requires having the actual and forecast values from the proceeding period.This is not possible for the first period,so for the first period one should use the actual value as the forecast value.

Which of the following is true about forecast bias?

If a forecasting model produces forecast errors (residuals)that are negatively correlated,then we expect a negative residual to be followed by another negative residual to be followed by another negative residual and so forth.

The Baker's Candy Company has been in business for three years.The quarterly sales data for the company are shown as follows: Based on this information,the data reflect both a linear trend and seasonal components.

The following output is provided for a linear trend regression-based forecasting model based on 12 months of data: Suppose that the actual sales for months 13-15 are: 720,680,800.Given this,which of the following is the forecast bias value for months 13-15?

The forecasting interval is the unit of time for which forecasts are made.

You are given the following linear trend model: Ft = 345.60 - 200.5(t).The forecast for period 15 is approximately -2,662.

The Where,Why,and How of Data Collection

Graphs,Charts and Tablesdescribing Your Data

Describing Data Using Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Introduction to Continuous Probability Distributions

Introduction to Sampling Distributions

Estimating Single Population Parameters

Introduction to Hypothesis Testing

Estimation and Hypothesis Testing for Two Population Parameters

Hypothesis Tests and Estimation for Population Variances

Analysis of Variance

Goodness-Of-Fit Tests and Contingency Analysis

Introduction to Linear Regression and Correlation Analysis

Multiple Regression Analysis and Model Building

Introduction to Nonparametric Statistics

Introduction to Quality and Statistical Process Control

Filters

You are given the following linear trend model: F_t = 345.60 - 200.5(t).This model implies that in year 1,the dependent variable had a value of 145.1.

You are given the following linear trend model: F_t = 345.60 - 200.5(t).The forecast for period 15 is approximately -2,662.