The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 1 2 3 4 5 5.5 6 Overall Grades 96 89 87 77 76 68 64  **Please circle the answer for each step so I don't get confused. Thanks in advance for helping me with the breakdown and notes** Step 1 of 6 :   Find the estimated slope. Round your answer to three decimal places. Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places. Step 5 of 6: Determine if the statement "All points predicted by the linear model fall on the same line" is true or false. Step 6 of 6: Find the value of the coefficient of determination. Round your answer to three decimal places.

Trigonometry (MindTap Course List)
8th Edition
ISBN:9781305652224
Author:Charles P. McKeague, Mark D. Turner
Publisher:Charles P. McKeague, Mark D. Turner
Chapter4: Graphing And Inverse Functions
Section: Chapter Questions
Problem 6GP: If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use...
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** had to resubmit this question because the first time the data was duplicated and reflected incorrectly. 

The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant.

Hours Unsupervised 1 2 3 4 5 5.5 6
Overall Grades 96 89 87 77 76 68 64

 **Please circle the answer for each step so I don't get confused. Thanks in advance for helping me with the breakdown and notes**

Step 1 of 6 :  

Find the estimated slope. Round your answer to three decimal places.

Step 2 of 6:

Find the estimated y-intercept. Round your answer to three decimal places.

Step 5 of 6:

Determine if the statement "All points predicted by the linear model fall on the same line" is true or false.

Step 6 of 6:

Find the value of the coefficient of determination. Round your answer to three decimal places.

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