7. Interpreting statistical software output in regression Aa Aa Suppose you work

Question

7. Interpreting statistical software output in regression Aa Aa Suppose you work in the admissions department of a small liberal arts college. You wonder if you can predict students' college grade point averages (GPAs) by their high school GPAs. You randomly select 50 recent graduates and collect their high school GPAs and college GPAs. You use a statistical software package to run a regression predicting college GPA from high school GPA. Use the following output to answer the questions that follow Descriptive Statistics Mean 3.064 3.214 Std Deviation 0.5574 0.6027 College GPA High school GPA 50 Model Summary Adjusted R Square 0.194 Std Error of the Estimate 0.5003 Model R Square 0.459a 0.211 a. Predictors: (constant) high school GPA

Explanation / Answer

y^ = 0.4247 *X + 1.6989

Y^ is predicted value of college GPA

X is value of high School GPA

p-value of b is 0.0008 < level of significance

hence you can reject the null ,you can conclude that both are linearly related

pearson correlation is sqrt(SS_Reg/SS_T) = sqrt(3.211/15.225) = 0.4592418

hence 0.459 is correct

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