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+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 1.5 2.5 3 3.5 4 4.5 6
Overall Grades 96 95 92 76 74 73 72
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 3 of 6 : Determine the value of the dependent variable y at x = 0.
step 4 of 6 : according to the estimated linear model, if the value of the independent variable is increased by one unit, then the change in the dependent variable y given by.
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 : determine the coefficient of determination. round to 3 decimal places.
We have, x= Hours Unsupervised
And y= Overall Grades
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