Exam 12: Correlation R and Regression Y BX A

A Pearson's product-moment correlation coefficient is often abbreviated as "correlation."

If r(8) = 1.2, p > .05, there must have been a sample size of 10.

If we find a correlation between training and job performance, we can conclude ______.

When calculating a correlation, the variable you choose for x and the variable you choose for y is critical to interpretation.

How are the coefficient of determination and correlation similar? How are they different?

If the correlation between sales and profit is .7, what percentage of variance in sales is unshared with variance in profit?

Weekly compensation Monthly sales 545 33 604 41 628 63 382 20 267 18 570 72 563 49 389 42 567 65 528 50 You run a used car dealership and want to know if you are appropriately compensating your sales force, so you collect weekly compensation rates and counts of monthly sales with the intent of comparing them. 1)What is the research question? 2)What are the hypotheses? 3)What are the degrees of freedom for the statistical significance test? 4)What is the critical value for this test? 5)State the formal results of the test. 6)Should you compute a coefficient of determination? How do you know? If so, calculate it. 7)Regress sales on compensation, and report the formula for the regression line here. 8)State all appropriate conclusions. 9)If a salesperson was compensated 450, what would we expect sales to be?

Significance tests for correlation are generally ______.

In this regression formula (y′ = 2x + 1), the "1" is the ______ and the "2" is the ______ .

Regression can also be called least squares regression because ______.

As CEO compensation decreases, stock price decreases. This describes ______.

Pearson's r is ______.

A regression line can be used to predict values outside the range of the original predictor.

In regression, we always regress the y variable on the x variable.

The line of best fit is the best line that can be used to describe ______.

Given a dataset where r = -.9, adding a new case where the value of x is high and the value of y is low is most likely to ______.

H₁:  = 0 is a valid alternative hypothesis for testing the statistical significance of a correlation.

The covariance formula differs from the variance formula in that instead of squaring the difference between each score and its mean, we multiply the difference between each x score and its mean with each y score and its mean.

Pearson's r is the most common type of correlation.

The covariance is different from the variance in that the covariance ______.