To construct: A scatterplot of calories burnt against MPH for various incline positions obtained from two types of treadmills.

Question

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Answer 1

Question

Chapter 29, Problem 29.47E

a.

To determine

To construct: A scatterplot of calories burnt against MPH for various incline positions obtained from two types of treadmills.

b.

To determine

To fit: A multiple regression model using the listed variables for predicting calories burnt.

c.

To check: Whether the model provides a better fit for the given data.

Answer:

The model provides a better fit for the given data.

Explanation:

Justification:

R-square:

The R-square is a multiple correlation coefficient and it is the square of correlation between the observed response variable and predicted response variable.

R-square tells about the fit of the model. If the R-square value is high then the model fits better.

From the MINITAB output it can be seen that the R-square value is 98.62%. This tells that the explanatory variables could explain 98.62% of variation in predicting the calories burnt.

d.

To determine

To find: Whether there is any significant differences in the relationship between the calories burnt and speed for two treadmills.

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Answer 2

Question

Chapter 29, Problem 29.47E

a.

To determine

To construct: A scatterplot of calories burnt against MPH for various incline positions obtained from two types of treadmills.

b.

To determine

To fit: A multiple regression model using the listed variables for predicting calories burnt.

c.

To check: Whether the model provides a better fit for the given data.

Answer:

The model provides a better fit for the given data.

Explanation:

Justification:

R-square:

The R-square is a multiple correlation coefficient and it is the square of correlation between the observed response variable and predicted response variable.

R-square tells about the fit of the model. If the R-square value is high then the model fits better.

From the MINITAB output it can be seen that the R-square value is 98.62%. This tells that the explanatory variables could explain 98.62% of variation in predicting the calories burnt.

d.

To determine

To find: Whether there is any significant differences in the relationship between the calories burnt and speed for two treadmills.

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Answer 3

Question

Chapter 29, Problem 29.47E

a.

To determine

To construct: A scatterplot of calories burnt against MPH for various incline positions obtained from two types of treadmills.

b.

To determine

To fit: A multiple regression model using the listed variables for predicting calories burnt.

c.

To check: Whether the model provides a better fit for the given data.

Answer:

The model provides a better fit for the given data.

Explanation:

Justification:

R-square:

The R-square is a multiple correlation coefficient and it is the square of correlation between the observed response variable and predicted response variable.

R-square tells about the fit of the model. If the R-square value is high then the model fits better.

From the MINITAB output it can be seen that the R-square value is 98.62%. This tells that the explanatory variables could explain 98.62% of variation in predicting the calories burnt.

d.

To determine

To find: Whether there is any significant differences in the relationship between the calories burnt and speed for two treadmills.

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Answer 4

Question

Chapter 29, Problem 29.47E

a.

To determine

To construct: A scatterplot of calories burnt against MPH for various incline positions obtained from two types of treadmills.

b.

To determine

To fit: A multiple regression model using the listed variables for predicting calories burnt.

c.

To check: Whether the model provides a better fit for the given data.

Answer:

The model provides a better fit for the given data.

Explanation:

Justification:

R-square:

The R-square is a multiple correlation coefficient and it is the square of correlation between the observed response variable and predicted response variable.

R-square tells about the fit of the model. If the R-square value is high then the model fits better.

From the MINITAB output it can be seen that the R-square value is 98.62%. This tells that the explanatory variables could explain 98.62% of variation in predicting the calories burnt.

d.

To determine

To find: Whether there is any significant differences in the relationship between the calories burnt and speed for two treadmills.

Expert Solution & Answer

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Answer 5

Chapter 29, Problem 29.47E

a.

To determine

To construct: A scatterplot of calories burnt against MPH for various incline positions obtained from two types of treadmills.

b.

To determine

To fit: A multiple regression model using the listed variables for predicting calories burnt.

c.

To check: Whether the model provides a better fit for the given data.

Answer:

The model provides a better fit for the given data.

Explanation:

Justification:

R-square:

The R-square is a multiple correlation coefficient and it is the square of correlation between the observed response variable and predicted response variable.

R-square tells about the fit of the model. If the R-square value is high then the model fits better.

From the MINITAB output it can be seen that the R-square value is 98.62%. This tells that the explanatory variables could explain 98.62% of variation in predicting the calories burnt.

d.

To determine

To find: Whether there is any significant differences in the relationship between the calories burnt and speed for two treadmills.

Answer 6

Chapter 29, Problem 29.47E

a.

To determine

To construct: A scatterplot of calories burnt against MPH for various incline positions obtained from two types of treadmills.

Answer 7

Chapter 29, Problem 29.47E

a.

To determine

To construct: A scatterplot of calories burnt against MPH for various incline positions obtained from two types of treadmills.

Answer 8

b.

To determine

To fit: A multiple regression model using the listed variables for predicting calories burnt.

Answer 9

b.

To determine

To fit: A multiple regression model using the listed variables for predicting calories burnt.

Answer 10

c.

To check: Whether the model provides a better fit for the given data.

Answer:

The model provides a better fit for the given data.

Explanation:

Justification:

R-square:

The R-square is a multiple correlation coefficient and it is the square of correlation between the observed response variable and predicted response variable.

R-square tells about the fit of the model. If the R-square value is high then the model fits better.

From the MINITAB output it can be seen that the R-square value is 98.62%. This tells that the explanatory variables could explain 98.62% of variation in predicting the calories burnt.

d.

To determine

To find: Whether there is any significant differences in the relationship between the calories burnt and speed for two treadmills.

Answer 11

c.

To check: Whether the model provides a better fit for the given data.

Answer:

The model provides a better fit for the given data.

Explanation:

Justification:

R-square:

The R-square is a multiple correlation coefficient and it is the square of correlation between the observed response variable and predicted response variable.

R-square tells about the fit of the model. If the R-square value is high then the model fits better.

From the MINITAB output it can be seen that the R-square value is 98.62%. This tells that the explanatory variables could explain 98.62% of variation in predicting the calories burnt.

d.

To determine

To find: Whether there is any significant differences in the relationship between the calories burnt and speed for two treadmills.

Answer 12

Expert Solution & Answer

Answer 13

Expert Solution & Answer

Answer 14

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Answer 15

Ch. 29.1 - Prob. 29.1AYK Ch. 29.1 - Prob. 29.2AYK Ch. 29.2 - Prob. 29.3AYK Ch. 29.2 - Prob. 29.4AYK Ch. 29.2 - Prob. 29.5AYK Ch. 29.3 - Prob. 29.6AYK Ch. 29.3 - Prob. 29.7AYK Ch. 29.4 - Prob. 29.8AYK Ch. 29.4 - Prob. 29.9AYK Ch. 29.4 - Prob. 29.10AYK

To construct: A scatterplot of calories burnt against MPH for various incline positions obtained from two types of treadmills.

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To construct: A scatterplot of calories burnt against MPH for various incline positions obtained from two types of treadmills.

To fit: A multiple regression model using the listed variables for predicting calories burnt.

To find: Whether there is any significant differences in the relationship between the calories burnt and speed for two treadmills.

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Chapter 29 Solutions