Credit card spending An analysis of spending by a sample of credit card bank cardholders shows that spending by cardholders in January ( Jan ) is related to their spending in December ( Dec ): The assumptions and conditions of the linear regression seemed to be satisfied and an analyst was about to predict January spending using the model J a n ^ = $ 612.07 + 0.403 D e c . Another analyst worried that different types of cardholders might behave differently. She examined the spending patterns of the cardholders and placed them into five market Segments . When she plotted the data using different colors and symbols for the five different segments, she found the following: Look at this plot carefully and discuss why she might be worried about the predictions from the model J a n ^ = $ 612.07 + 0.403 D e c .

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Answer 1

Textbook Question

Chapter 8, Problem 1E

Credit card spending An analysis of spending by a sample of credit card bank cardholders shows that spending by cardholders in January (Jan) is related to their spending in December (Dec):

Chapter 8, Problem 1E, Credit card spending An analysis of spending by a sample of credit card bank cardholders shows that , example 1

The assumptions and conditions of the linear regression seemed to be satisfied and an analyst was about to predict January spending using the model

J a n ^ = $ 612.07 + 0.403 D e c .

Another analyst worried that different types of cardholders might behave differently. She examined the spending patterns of the cardholders and placed them into five market Segments. When she plotted the data using different colors and symbols for the five different segments, she found the following:

Chapter 8, Problem 1E, Credit card spending An analysis of spending by a sample of credit card bank cardholders shows that , example 2

Look at this plot carefully and discuss why she might be worried about the predictions from the model

J a n ^ = $ 612.07 + 0.403 D e c .

Expert Solution & Answer

To determine

Being worried to make a prediction from the model Jan=$612.07+0.403 Dec., using a second scatterplot.

Explanation of Solution

Given info:

A scatterplot of spending for a sample of credit card bank cardholders in January and in 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 enough condition: The relationship between y and x is 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.

Thus, 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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A company found that the daily sales revenue of its flagship product follows a normal distribution with a mean of $4500 and a standard deviation of $450. The company defines a "high-sales day" that is, any day with sales exceeding $4800. please provide a step by step on how to get the answers in excel Q: What percentage of days can the company expect to have "high-sales days" or sales greater than $4800? Q: What is the sales revenue threshold for the bottom 10% of days? (please note that 10% refers to the probability/area under bell curve towards the lower tail of bell curve) Provide answers in the yellow cells

Answer 2

Textbook Question

Chapter 8, Problem 1E

Credit card spending An analysis of spending by a sample of credit card bank cardholders shows that spending by cardholders in January (Jan) is related to their spending in December (Dec):

Chapter 8, Problem 1E, Credit card spending An analysis of spending by a sample of credit card bank cardholders shows that , example 1

The assumptions and conditions of the linear regression seemed to be satisfied and an analyst was about to predict January spending using the model

J a n ^ = $ 612.07 + 0.403 D e c .

Another analyst worried that different types of cardholders might behave differently. She examined the spending patterns of the cardholders and placed them into five market Segments. When she plotted the data using different colors and symbols for the five different segments, she found the following:

Chapter 8, Problem 1E, Credit card spending An analysis of spending by a sample of credit card bank cardholders shows that , example 2

Look at this plot carefully and discuss why she might be worried about the predictions from the model

J a n ^ = $ 612.07 + 0.403 D e c .

Expert Solution & Answer

To determine

Being worried to make a prediction from the model Jan=$612.07+0.403 Dec., using a second scatterplot.

Explanation of Solution

Given info:

A scatterplot of spending for a sample of credit card bank cardholders in January and in 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 enough condition: The relationship between y and x is 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.

Thus, 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

Textbook Question

Chapter 8, Problem 1E

Credit card spending An analysis of spending by a sample of credit card bank cardholders shows that spending by cardholders in January (Jan) is related to their spending in December (Dec):

Chapter 8, Problem 1E, Credit card spending An analysis of spending by a sample of credit card bank cardholders shows that , example 1

The assumptions and conditions of the linear regression seemed to be satisfied and an analyst was about to predict January spending using the model

J a n ^ = $ 612.07 + 0.403 D e c .

Another analyst worried that different types of cardholders might behave differently. She examined the spending patterns of the cardholders and placed them into five market Segments. When she plotted the data using different colors and symbols for the five different segments, she found the following:

Chapter 8, Problem 1E, Credit card spending An analysis of spending by a sample of credit card bank cardholders shows that , example 2

Look at this plot carefully and discuss why she might be worried about the predictions from the model

J a n ^ = $ 612.07 + 0.403 D e c .

Expert Solution & Answer

To determine

Being worried to make a prediction from the model Jan=$612.07+0.403 Dec., using a second scatterplot.

Explanation of Solution

Given info:

A scatterplot of spending for a sample of credit card bank cardholders in January and in 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 enough condition: The relationship between y and x is 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.

Thus, 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 4

Textbook Question

Chapter 8, Problem 1E

Credit card spending An analysis of spending by a sample of credit card bank cardholders shows that spending by cardholders in January (Jan) is related to their spending in December (Dec):

Chapter 8, Problem 1E, Credit card spending An analysis of spending by a sample of credit card bank cardholders shows that , example 1

The assumptions and conditions of the linear regression seemed to be satisfied and an analyst was about to predict January spending using the model

J a n ^ = $ 612.07 + 0.403 D e c .

Another analyst worried that different types of cardholders might behave differently. She examined the spending patterns of the cardholders and placed them into five market Segments. When she plotted the data using different colors and symbols for the five different segments, she found the following:

Chapter 8, Problem 1E, Credit card spending An analysis of spending by a sample of credit card bank cardholders shows that , example 2

Look at this plot carefully and discuss why she might be worried about the predictions from the model

J a n ^ = $ 612.07 + 0.403 D e c .

Expert Solution & Answer

To determine

Being worried to make a prediction from the model Jan=$612.07+0.403 Dec., using a second scatterplot.

Explanation of Solution

Given info:

A scatterplot of spending for a sample of credit card bank cardholders in January and in 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 enough condition: The relationship between y and x is 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.

Thus, 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 5

Textbook Question

Answer 6

Textbook Question

Answer 7

Expert Solution & Answer

To determine

Being worried to make a prediction from the model Jan=$612.07+0.403 Dec., using a second scatterplot.

Explanation of Solution

Given info:

A scatterplot of spending for a sample of credit card bank cardholders in January and in 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 enough condition: The relationship between y and x is 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.

Thus, 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 8

Expert Solution & Answer

To determine

Being worried to make a prediction from the model Jan=$612.07+0.403 Dec., using a second scatterplot.

Explanation of Solution

Given info:

A scatterplot of spending for a sample of credit card bank cardholders in January and in 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 enough condition: The relationship between y and x is 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.

Thus, 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 9

Expert Solution & Answer

Answer 10

Expert Solution & Answer

Answer 11

To determine

Being worried to make a prediction from the model Jan=$612.07+0.403 Dec., using a second scatterplot.

Answer 12

Explanation of Solution

Given info:

A scatterplot of spending for a sample of credit card bank cardholders in January and in 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 enough condition: The relationship between y and x is 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.

Thus, 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 13

Ch. 8.3 - Each of these scatterplots shows an unusual point....Ch. 8.3 - Prob. 2JC Ch. 8.3 - Prob. 3JC Ch. 8 - Credit card spending An analysis of spending by a...Ch. 8 - Prob. 2E Ch. 8 - Prob. 3E Ch. 8 - Prob. 4E Ch. 8 - Prob. 5E Ch. 8 - Prob. 6E Ch. 8 - Prob. 7E

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