Consider a sample of students' study hours per week and grade point average (GPA). A researcher wants to investigate study hours as a predictor for GPA. The GPA data has a mean of 3.586 with a standard deviation of 0.285. The study hours data has a mean of 17.477 with a standard deviation of 11.409. The correlation coefficient for this bivariate data is 0.133, as shown in the table below. GPA Study Hours |Мean 3.586 17.477 Standard Deviation 0.285 11.409 Correlation R= 0.133 What is the slope of the linear regression line for this data? Round to the nearest ten-thousandth place. bị
Consider a sample of students' study hours per week and grade point average (GPA). A researcher wants to investigate study hours as a predictor for GPA. The GPA data has a mean of 3.586 with a standard deviation of 0.285. The study hours data has a mean of 17.477 with a standard deviation of 11.409. The correlation coefficient for this bivariate data is 0.133, as shown in the table below. GPA Study Hours |Мean 3.586 17.477 Standard Deviation 0.285 11.409 Correlation R= 0.133 What is the slope of the linear regression line for this data? Round to the nearest ten-thousandth place. bị
MATLAB: An Introduction with Applications
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Transcribed Image Text:Consider a sample of students' study hours per week and grade point average (GPA). A researcher wants to
investigate study hours as a predictor for GPA.
The GPA data has a mean of 3.586 with a standard deviation of 0.285. The study hours data has a mean of
17.477 with a standard deviation of 11.409. The correlation coefficient for this bivariate data is 0.133, as
shown in the table below.
GPA
Study Hours
Mean
3.586
17.477
Standard Deviation
0.285
11.409
Correlation
R= 0.133
What is the slope of the linear regression line for this data? Round to the nearest ten-thousandth place. b1
%3D
Expert Solution
Step 1
From the provided information,
Standard deviation of study hours (Sx) = 11.409
Standard deviation of GPA (Sy) = 0.285
Correlation (r) = 0.133
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