AP Statistics - "Golden Sheet" for Regression

slope

For each increase of 1 "unit" in "x", the model predicts an (increase/decrease) of _ "units" in "y".

y-intercept

The model predicts that at 0 "units" of "x", the "y" value will be _ "units".

residual plot

"No pattern" is a good thing! If we see a curve, we're using the wrong model.

correlation coefficient (r)

There is a (weak/moderate/strong) (negative/positive) (linear/nonlinear) association between "x" and "y" for the "subjects in context".

coefficient of determination (r^2)

_% of the variation in "y" can be explained by the linear model for "x" and "y".

residual (e = y - ŷ)

For a "x" value of _ "units", the model (over/under)estimated the actual value of "y" by _ "units".

standard error of residuals (s)

_ is the typical distance between the observed and predicted "y" values for the points in this regression.