Last year, five randomly selected students took a math aptitude test before they began their statistics course. The Statistics Department would like to analyze the relationship of the data, make predictions using the regression equation and validate the regression equation. The data of the math aptitude test score and corresponding statistics grade are shown in Table 4. Table 4 Score on math aptitude test (x)Statistics grade (y) 95 85 85 80 80 75 70 75 60 65 Answers at 2 decimal places. ( α) Calculate Σα, Συ, Σay and Σα . Ex = Ey = Exy = Ex2 = (b) Calculate the value of b and bo. bo = (c) Based on your answers in (a) and (b), what linear regression equation best predicts statistics performance, based on math aptitude scores? ŷ =

Last year, five randomly selected students took a math aptitude test before they began their statistics course. The Statistics Department would like to analyze the relationship of the data, make predictions using the regression equation and validate the regression equation. The data of the math aptitude test score and corresponding statistics grade are shown in Table 4. Table 4 Score on math aptitude test (x)Statistics grade (y) 95 85 85 80 80 75 70 75 60 65 Answers at 2 decimal places. ( α) Calculate Σα, Συ, Σay and Σα . Ex = Ey = Exy = Ex2 = (b) Calculate the value of b and bo. bo = (c) Based on your answers in (a) and (b), what linear regression equation best predicts statistics performance, based on math aptitude scores? ŷ =

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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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 2 3 4 4.5 5 5.5 Overall Grades 98 95 93 90 89 72 69 Table Copy Data Step 1 of 6 : Find the estimated slope. Round your answer to three decimal places.
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 2 3 4 4.5 5 5.5 Overall Grades 98 95 93 90 89 72 69 Table Copy Data Step 2 of 6 : Find the estimated y-intercept. Round your answer to three decimal places.
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