Optimization algorithm that minimizes squared errors to estimate parameters

Standardized measure of association bounded between -1 and 1

Unstandardized measure of shared variance limited by units

The fundamental form of most statistical models

The uncertainty remaining after fitting the model to the data

Should be judged by magnitude (effect size), not p-values

The value of the function when X is zero (crosses y-axis)

The regression model collapses to the Mean of Y (flat line)

Necessary to detect non-linear relationships (e.g., U-shaped) missed by r

Magnitude of change in f(x) resulting from a change in x