MAD and MSE of actual given data and forecasted data and to check accuracy of the forecasted data. Mean absolute deviation MAD is calculated by the division of sum of absolute deviations and number of observations. Here, absolute deviations are calculated by deducting the forecasted data from the actual data. Mean squared error MSE is calculated by the division of sum of square of deviations and number of observations. Here, deviations are calculated by deducting estimated data from the actual data.

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Answer 1

Question

Chapter 2.9, Problem 36P

Summary Introduction

To calculate: MAD and MSE of actual given data and forecasted data and to check accuracy of the forecasted data.

Mean absolute deviation

MAD is calculated by the division of sum of absolute deviations and number of observations. Here, absolute deviations are calculated by deducting the forecasted data from the actual data.

Mean squared error

MSE is calculated by the division of sum of square of deviations and number of observations. Here, deviations are calculated by deducting estimated data from the actual data.

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Answer 2

Question

Chapter 2.9, Problem 36P

Summary Introduction

To calculate: MAD and MSE of actual given data and forecasted data and to check accuracy of the forecasted data.

Mean absolute deviation

MAD is calculated by the division of sum of absolute deviations and number of observations. Here, absolute deviations are calculated by deducting the forecasted data from the actual data.

Mean squared error

MSE is calculated by the division of sum of square of deviations and number of observations. Here, deviations are calculated by deducting estimated data from the actual data.

Expert Solution & Answer

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Answer 3

Question

Chapter 2.9, Problem 36P

Summary Introduction

To calculate: MAD and MSE of actual given data and forecasted data and to check accuracy of the forecasted data.

Mean absolute deviation

MAD is calculated by the division of sum of absolute deviations and number of observations. Here, absolute deviations are calculated by deducting the forecasted data from the actual data.

Mean squared error

MSE is calculated by the division of sum of square of deviations and number of observations. Here, deviations are calculated by deducting estimated data from the actual data.

Expert Solution & Answer

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Answer 4

Question

Chapter 2.9, Problem 36P

Summary Introduction

To calculate: MAD and MSE of actual given data and forecasted data and to check accuracy of the forecasted data.

Mean absolute deviation

MAD is calculated by the division of sum of absolute deviations and number of observations. Here, absolute deviations are calculated by deducting the forecasted data from the actual data.

Mean squared error

MSE is calculated by the division of sum of square of deviations and number of observations. Here, deviations are calculated by deducting estimated data from the actual data.

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Answer 5

Chapter 2.9, Problem 36P

Summary Introduction

To calculate: MAD and MSE of actual given data and forecasted data and to check accuracy of the forecasted data.

Mean absolute deviation

MAD is calculated by the division of sum of absolute deviations and number of observations. Here, absolute deviations are calculated by deducting the forecasted data from the actual data.

Mean squared error

MSE is calculated by the division of sum of square of deviations and number of observations. Here, deviations are calculated by deducting estimated data from the actual data.

Answer 6

Chapter 2.9, Problem 36P

Summary Introduction

To calculate: MAD and MSE of actual given data and forecasted data and to check accuracy of the forecasted data.

Mean absolute deviation

MAD is calculated by the division of sum of absolute deviations and number of observations. Here, absolute deviations are calculated by deducting the forecasted data from the actual data.

Mean squared error

MSE is calculated by the division of sum of square of deviations and number of observations. Here, deviations are calculated by deducting estimated data from the actual data.

Answer 7

Chapter 2.9, Problem 36P

Summary Introduction

To calculate: MAD and MSE of actual given data and forecasted data and to check accuracy of the forecasted data.

Mean absolute deviation

MAD is calculated by the division of sum of absolute deviations and number of observations. Here, absolute deviations are calculated by deducting the forecasted data from the actual data.

Mean squared error

MSE is calculated by the division of sum of square of deviations and number of observations. Here, deviations are calculated by deducting estimated data from the actual data.

Answer 8

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Answer 9

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Answer 10

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Answer 11

Ch. 2.4 - Prob. 1P Ch. 2.4 - Prob. 2P Ch. 2.4 - Prob. 3P Ch. 2.4 - Prob. 4P Ch. 2.4 - Prob. 5P Ch. 2.4 - Prob. 6P Ch. 2.4 - Prob. 7P Ch. 2.4 - Prob. 8P Ch. 2.4 - Prob. 9P Ch. 2.6 - Prob. 10P

Solution Summary: The author calculates MAD and MSE of actual given data and forecasted data.

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