a. Explanation Given info: The output shows the analysis for GPA and meals per week. Calculation: The null and alternative hypotheses are, H 0 : β 1 = 0 That is, there is no linear relationship between the number of meals eaten as a family and grades. H 1 : β 1 ≠ 0 That is, there is a linear relationship between the number of meals eaten as a family and grades. From given information, it can be observed that the data were judged acceptable for inference, the sampling distribution of the regression slope can be modeled by a student’s t -model. The linear regression model is, y ^ v = b 0 + b 1 x v Where, y ^ v represents the predicted variable, x v represents the predictor variable b 0 represents intercept and b 1 represents slope. From the output, it can be observed that the predicted variable is GPA, predictor variable is meals per week, intercept is 2.7288 and the slope is 0.1093. Thus, the linear regression model that predicts from meals per week is, G P A ^ = 2.7288 + 0.1093 ( Meals/Week ) From the output, it can be observed that degrees of freedom is 140 ( = 142 − 2 ) . The formula for finding the test statistic is, t = b 1 − β 1 S E ( b 1 ) Substitute 0 b. To determine Explain the whether the association would be useful in prediction a student’s grade point average. c. To determine Explain the whether the answers to part a and b contradictory.

Intro Stats, Books a la Carte Edition (5th Edition)

5th Edition

ISBN: 9780134210285

Author: Richard D. De Veaux, Paul Velleman, David E. Bock

Publisher: PEARSON

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Chapter R, Problem 5.45RE

To determine

Test an appropriate hypothesis for checking there is any evidence of an association.

Write conclusions.

To determine

Explain the whether the association would be useful in prediction a student’s grade point average.

To determine

Explain the whether the answers to part a and b contradictory.

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Chapter R, Problem 5.44RE

Chapter R, Problem 5.46RE

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Test an appropriate hypothesis for checking there is any evidence of an association. Write conclusions.

Solution Summary: The author analyzes the relationship between grades and the number of meals eaten as a family. The linear regression model predicts GPA, meals per week, intercept, and slope.

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Test an appropriate hypothesis for checking there is any evidence of an association. Write conclusions.

Explain the whether the association would be useful in prediction a student’s grade point average.

Explain the whether the answers to part a and b contradictory.

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Test an appropriate hypothesis for checking there is any evidence of an association.

Write conclusions.