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The accompanying data file shows the midterm and final scores for 32 students in a statistics course Click here for the Excel Data File
a. Estimate a students final score as a function of hiss/her midterm score. (Round your answers t decimal places.) Final27.5818+ 0.6774 Midterm b. Find the standard error of the estimate. (Round your answer to 2 decimal places.) 14.947 c. Interpret the coefficient of determination. (Round your answer to 2 decimal places.) R means that % of the sample Variation â–¼ | in Final grades is explained by the sample regression equation

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In this case, the coefficient of determination is 0.5297, which means that 53% of the sample variation in Final grades is explained by the sample regression equation.

The data file contains the midterm and final scores of 32 students in a statistics course. To estimate a student's final score as a function of their midterm score, we used a regression analysis. The regression equation was Final = 27.5818 + 0.6774 Midterm. This equation can be used to predict the final score of a student based on their midterm score. The standard error of the estimate was 14.947. This indicates the accuracy of the estimated final score. The coefficient of determination was 0.5297, which means that 53% of the sample variation in final grades is explained by the regression equation. This tells us that the regression equation is a relatively good predictor of a student's final score.

Given:

Midterm Score = x

Final Score = y

Regression Equation: y = 27.5818 + 0.6774x

Standard Error of the Estimate = 14.947

Coefficient of Determination = 0.5297

Calculating Final Score:

y = 27.5818 + 0.6774x

y = 27.5818 + 0.6774(x)

y = 27.5818 + 0.6774(x)

y = 27.5818 + 0.6774(x)

y = 27.5818 + 0.6774x

Final Score = 27.5818 + 0.6774(Midterm Score)

Learn more about regression here

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