Explain the reason of being worried from the given model.

Question

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Answer 1

Question

Chapter 8, Problem 1E

To determine

Explain the reason of being worried from the given model.

Expert Solution & Answer

Explanation of Solution

Given info:

A scatterplots of spending for a sample of credit card bank cardholders in January and are December is given. The corresponding regression model to predict January spending from December spending is Jan=$612.07+0.403 Dec.

Another scatterplot of spending for a sample of credit card bank cardholders in January and that in December for five market segments is given.

Justification:

The conditions for a scatterplot that is well-fitted for the data is as follows:

Straight line condition: The relationship between y and x should be straight enough to proceed with a linear regression model.
Outlier condition: No outlier must be there which influences the fit of the least square line.
Thickness condition: The spread of the data around the generally straight relationship seems to be consistent for all values of x.

The different segments are not scattered at random throughout the scatterplot.

Moreover, the spread of the data is not consistent for all values of December and each segment may have a different relationship that might affect the accuracy of the model to predict.

The relationship between the spending of credit card bank cardholders in January and in December is not straight enough to proceed with a linear regression model.

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Answer 2

Question

Chapter 8, Problem 1E

To determine

Explain the reason of being worried from the given model.

Expert Solution & Answer

Explanation of Solution

Given info:

A scatterplots of spending for a sample of credit card bank cardholders in January and are December is given. The corresponding regression model to predict January spending from December spending is Jan=$612.07+0.403 Dec.

Another scatterplot of spending for a sample of credit card bank cardholders in January and that in December for five market segments is given.

Justification:

The conditions for a scatterplot that is well-fitted for the data is as follows:

Straight line condition: The relationship between y and x should be straight enough to proceed with a linear regression model.
Outlier condition: No outlier must be there which influences the fit of the least square line.
Thickness condition: The spread of the data around the generally straight relationship seems to be consistent for all values of x.

The different segments are not scattered at random throughout the scatterplot.

Moreover, the spread of the data is not consistent for all values of December and each segment may have a different relationship that might affect the accuracy of the model to predict.

The relationship between the spending of credit card bank cardholders in January and in December is not straight enough to proceed with a linear regression model.

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Answer 3

Question

Chapter 8, Problem 1E

To determine

Explain the reason of being worried from the given model.

Expert Solution & Answer

Explanation of Solution

Given info:

A scatterplots of spending for a sample of credit card bank cardholders in January and are December is given. The corresponding regression model to predict January spending from December spending is Jan=$612.07+0.403 Dec.

Another scatterplot of spending for a sample of credit card bank cardholders in January and that in December for five market segments is given.

Justification:

The conditions for a scatterplot that is well-fitted for the data is as follows:

Straight line condition: The relationship between y and x should be straight enough to proceed with a linear regression model.
Outlier condition: No outlier must be there which influences the fit of the least square line.
Thickness condition: The spread of the data around the generally straight relationship seems to be consistent for all values of x.

The different segments are not scattered at random throughout the scatterplot.

Moreover, the spread of the data is not consistent for all values of December and each segment may have a different relationship that might affect the accuracy of the model to predict.

The relationship between the spending of credit card bank cardholders in January and in December is not straight enough to proceed with a linear regression model.

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Subscribe now to access step-by-step solutions to millions of textbook problems written by subject matter experts!

Answer 4

Question

Chapter 8, Problem 1E

To determine

Explain the reason of being worried from the given model.

Expert Solution & Answer

Explanation of Solution

Given info:

A scatterplots of spending for a sample of credit card bank cardholders in January and are December is given. The corresponding regression model to predict January spending from December spending is Jan=$612.07+0.403 Dec.

Another scatterplot of spending for a sample of credit card bank cardholders in January and that in December for five market segments is given.

Justification:

The conditions for a scatterplot that is well-fitted for the data is as follows:

Straight line condition: The relationship between y and x should be straight enough to proceed with a linear regression model.
Outlier condition: No outlier must be there which influences the fit of the least square line.
Thickness condition: The spread of the data around the generally straight relationship seems to be consistent for all values of x.

The different segments are not scattered at random throughout the scatterplot.

Moreover, the spread of the data is not consistent for all values of December and each segment may have a different relationship that might affect the accuracy of the model to predict.

The relationship between the spending of credit card bank cardholders in January and in December is not straight enough to proceed with a linear regression model.

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Subscribe now to access step-by-step solutions to millions of textbook problems written by subject matter experts!

Answer 5

Chapter 8, Problem 1E

To determine

Explain the reason of being worried from the given model.

Expert Solution & Answer

Explanation of Solution

Given info:

A scatterplots of spending for a sample of credit card bank cardholders in January and are December is given. The corresponding regression model to predict January spending from December spending is Jan=$612.07+0.403 Dec.

Another scatterplot of spending for a sample of credit card bank cardholders in January and that in December for five market segments is given.

Justification:

The conditions for a scatterplot that is well-fitted for the data is as follows:

Straight line condition: The relationship between y and x should be straight enough to proceed with a linear regression model.
Outlier condition: No outlier must be there which influences the fit of the least square line.
Thickness condition: The spread of the data around the generally straight relationship seems to be consistent for all values of x.

The different segments are not scattered at random throughout the scatterplot.

Moreover, the spread of the data is not consistent for all values of December and each segment may have a different relationship that might affect the accuracy of the model to predict.

The relationship between the spending of credit card bank cardholders in January and in December is not straight enough to proceed with a linear regression model.

Answer 6

Chapter 8, Problem 1E

To determine

Explain the reason of being worried from the given model.

Expert Solution & Answer

Explanation of Solution

Given info:

A scatterplots of spending for a sample of credit card bank cardholders in January and are December is given. The corresponding regression model to predict January spending from December spending is Jan=$612.07+0.403 Dec.

Another scatterplot of spending for a sample of credit card bank cardholders in January and that in December for five market segments is given.

Justification:

The conditions for a scatterplot that is well-fitted for the data is as follows:

Straight line condition: The relationship between y and x should be straight enough to proceed with a linear regression model.
Outlier condition: No outlier must be there which influences the fit of the least square line.
Thickness condition: The spread of the data around the generally straight relationship seems to be consistent for all values of x.

The different segments are not scattered at random throughout the scatterplot.

Moreover, the spread of the data is not consistent for all values of December and each segment may have a different relationship that might affect the accuracy of the model to predict.

The relationship between the spending of credit card bank cardholders in January and in December is not straight enough to proceed with a linear regression model.

Answer 7

Chapter 8, Problem 1E

To determine

Explain the reason of being worried from the given model.

Answer 8

Expert Solution & Answer

Explanation of Solution

Given info:

A scatterplots of spending for a sample of credit card bank cardholders in January and are December is given. The corresponding regression model to predict January spending from December spending is Jan=$612.07+0.403 Dec.

Another scatterplot of spending for a sample of credit card bank cardholders in January and that in December for five market segments is given.

Justification:

The conditions for a scatterplot that is well-fitted for the data is as follows:

Straight line condition: The relationship between y and x should be straight enough to proceed with a linear regression model.
Outlier condition: No outlier must be there which influences the fit of the least square line.
Thickness condition: The spread of the data around the generally straight relationship seems to be consistent for all values of x.

The different segments are not scattered at random throughout the scatterplot.

Moreover, the spread of the data is not consistent for all values of December and each segment may have a different relationship that might affect the accuracy of the model to predict.

The relationship between the spending of credit card bank cardholders in January and in December is not straight enough to proceed with a linear regression model.