Question

A data analyst unit at a major state university is tasked with predicting the performance of...

  1. A data analyst unit at a major state university is tasked with predicting the performance of graduate students using metrics generally available during the application process. They decide to model student success based on two predictors: GRE scores, undergraduate GPA. Write out the regression equation including main effects and interaction terms, given the following coefficients. Where possible, use variable names!

Intercept=25.176xMA+dJ9odpQHORKP4BYVQx+zez9m8AAAAASUVOR

βGRE=.0024QFuc4FcjqBJBgAAAABJRU5ErkJggg==

βGPA=5.610Zgf6cuz2BacgdqwS28y3AAAAAElFTkSuQmCC

βGRE*GPA=.0006OU0I4vX2JjlrvFLIG4VIPiutHYfzKeB4D4fdSZ2C

  1. Regression equation:

  1. Given the regression equation, what would you predict the graduate performance score to be for a student with an incoming GRE score of 650 and a GPA of 3.15?

  1. What does a predicted graduate performance score of 25.17 represent? Is this a meaningful value?
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Answer #1

Answer:

Given the

The following coefficients

Intercept = 25.17

\beta GRE = 0.0024

\beta GPA = 5.61

\beta GRE * \beta GPA = 0.0006

A data analyst unit at a major state university is tasked with predicting the performance of graduate students using mehics gstudent with an incoming GRE Score 650 GPA of score 3.15 when X=650 X = 3.15 graduate perlormance score 3.15 y = 25.17+0.0024So, practically CPA would not take the value 2070 (ie X₂70) predicted graduate perler mance will be greater than as.17 C beca

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