# Let us suppose we are predicting the score on a training post-test from the number of years of education and the score on an aptitude test given before training. Here is the regression equation: Y = 25 + .5X1 +10X2,

Let us suppose we are predicting the score on a training post-test from the number of years of education and the score on an aptitude test given before training. Here is the regression equation:

*Y* = 25 + .5*X*_{1} +10*X*_{2},

where *X*_{1 }= years of education and *X*_{2} = aptitude test score.

What does the .5 in front of *X*_{1 }tell us?

Group of answer choices

### Need assignment help for this question?

If you need assistance with writing your essay, we are ready to help you!

## OUR PROCESS

### Order

### Payment

### Writing

### Delivery

**Why Choose Us: **Cost-efficiency, Plagiarism free, Money Back Guarantee, On-time Delivery, Total Сonfidentiality, 24/7 Support, 100% originality

where the equation crosses the *y*-axis

how much change in post-test score you get per unit change in aptitude test score

how much change in the post-test score you get per unit change in years of education

how much change in the years of education you get per unit change in post-test score