Correlation and Regression

Covariance is x and y in the same formula as variance is x squared.

Table B3 determines whether or not the observed pearson r is a "rare event" unlikely to have occured by chance.

A large sample size usually makes r values significant.

The formula and calculation for comparing r's will not be required on test.

Regression

Uses the classic equation for a line: y = mx + b, but the letters are different in stats. It is y=bx+a where b is the slope and a is the y intercept.

Slope = rise over run or y1-y2 divided by x1-x2

Prediction comes from graphing the line and predicting x, y coordinates on the line.

Data that can be described as a line is known as perfectly linear relationship.

Best-fitting line is known as the regression line.

Method of least-square creates the regression line (or best-fitting line): It is the line that minimizes the overall distance between the regression line and the data points.

Calculation is not required for test.