Students in QMB 3600-Quantitative Methods in Business course decided to research the relationship between the Mid Term Exam, the average number of study hours spent per week during the semester and the final course grade for a given student. A sample of containing data from a previous semester was provided by the instructor and summarized in the following table: Final Course Grade Average Number of study hours per week 2.0 4.0 3.5 Student # Mid-Term Exam Grade 50.0 60.0 65.0 85.0 1 3 55.0 78.0 4 85.0 6.0 90.0 55.0 5.0 70.0 72.0 4.5 89.0 6.5 3.0 5.5 7.5 75.0 91.0 65.0 89.0 96.0 8. 45.0 88.0 90.0 10 Develop a linear regression model, where Y is the Final Grade Course and X is the Mid-Term Exam. Calculate the coefficient of determination (r), the coefficient of correlation (r), the variance (o) for the model and apply Hypothesis Testing to test the significance of the linear model for a = 0.05 exactly as demonstrated in the Triple A Construction Example on page 121 of your textbook. Show all your calculations and follow the same guidance provided in Problem #1. Plot a scatter diagram for the data used in topic (a) and plot the linear regression model as well. Follow the same guidance provided in Problem #1. Develop a linear regression model, where Y is the Final Grade Course and X is the Average Number of Study Hours per week. Calculate the coefficient of determination (r'), the coefficient of correlation (r), the variance (o*) for the model and apply Hypothesis Testing to test the significance of the linear model for a = 0.05 exactly as demonstrated in the Triple A Construction Example on page 121 of your textbook. Show all your calculations and follow the same guidance provided in Problem #1. Plot a scatter diagram for the data used in topic (c) and plot the linear regression model as well. Follow the same guidance provided in Problem #1. .., Based on the coefficient of determination (r) for each linear regression models developed, which of the two linear regression models should be used to predict the Final Grade in QMB 3600 and explain your decision.

Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter7: Distance And Approximation
Section7.3: Least Squares Approximation
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Students in QMB 3600 - Quantitative Methods in Business course decided to research the relationship
between the Mid Term Exam, the average number of study hours spent per week during the semester and the
final course grade for a given student. A sample of containing data from a previous semester was provided by the
instructor and summarized in the following table:
Average Number of
study hours per week
Student #
Mid-Term Exam
Final Course Grade
Grade
1
50.0
2.0
65.0
60.0
4.0
85.0
55.0
3.5
78.0
4
85.0
6.0
90.0
55.0
5.0
70.0
6.
72.0
4.5
89.0
7
75.0
6.5
91.0
8
45.0
3.0
65.0
88.0
5.5
89.0
10
90.0
7.5
96.0
Develop a linear regression model, where Y is the Final Grade Course and X is the Mid-Term Exam.
Calculate the coefficient of determination (r), the coefficient of correlation (r), the variance (o?) for the model
and apply Hypothesis Testing to test the significance of the linear model for a = 0.05 exactly as demonstrated in
the Triple A Construction Example on page 121 of your textbook. Show all your calculations and follow the same
guidance provided in Problem #1.
Plot a scatter diagram for the data used in topic (a) and plot the linear regression model as well. Follow
the same guidance provided in Problem #1.
Develop a linear regression model, where Y is the Final Grade Course and X is the Average Number of
Study Hours per week. Calculate the coefficient of determination (r?), the coefficient of correlation (r), the variance
(o*) for the model and apply Hypothesis Testing to test the significance of the linear model for a = 0.05 exactly as
demonstrated in the Triple A Construction Example on page 121 of your textbook. Show all your calculations and
follow the same guidance provided in Problem #1.
Plot a scatter diagram for the data used in topic (c) and plot the linear regression model as well. Follow
the same guidance provided in Problem #1.
.., Based on the coefficient of determination (r) for each linear regression models developed, which of
the two linear regression models should be used to predict the Final Grade in QMB 3600 and explain your decision.
Transcribed Image Text:Students in QMB 3600 - Quantitative Methods in Business course decided to research the relationship between the Mid Term Exam, the average number of study hours spent per week during the semester and the final course grade for a given student. A sample of containing data from a previous semester was provided by the instructor and summarized in the following table: Average Number of study hours per week Student # Mid-Term Exam Final Course Grade Grade 1 50.0 2.0 65.0 60.0 4.0 85.0 55.0 3.5 78.0 4 85.0 6.0 90.0 55.0 5.0 70.0 6. 72.0 4.5 89.0 7 75.0 6.5 91.0 8 45.0 3.0 65.0 88.0 5.5 89.0 10 90.0 7.5 96.0 Develop a linear regression model, where Y is the Final Grade Course and X is the Mid-Term Exam. Calculate the coefficient of determination (r), the coefficient of correlation (r), the variance (o?) for the model and apply Hypothesis Testing to test the significance of the linear model for a = 0.05 exactly as demonstrated in the Triple A Construction Example on page 121 of your textbook. Show all your calculations and follow the same guidance provided in Problem #1. Plot a scatter diagram for the data used in topic (a) and plot the linear regression model as well. Follow the same guidance provided in Problem #1. Develop a linear regression model, where Y is the Final Grade Course and X is the Average Number of Study Hours per week. Calculate the coefficient of determination (r?), the coefficient of correlation (r), the variance (o*) for the model and apply Hypothesis Testing to test the significance of the linear model for a = 0.05 exactly as demonstrated in the Triple A Construction Example on page 121 of your textbook. Show all your calculations and follow the same guidance provided in Problem #1. Plot a scatter diagram for the data used in topic (c) and plot the linear regression model as well. Follow the same guidance provided in Problem #1. .., Based on the coefficient of determination (r) for each linear regression models developed, which of the two linear regression models should be used to predict the Final Grade in QMB 3600 and explain your decision.
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