 Chapter 3! 1

UNIT 7 VOCABULARY – CHAPTERS 3 & 14 2

(4) the LSRL and y-hat Note: Remember that the “a” and the “b” are both statistics; their calculated values would change with different ordered pairs. (5) “residuals” and a residual plot * Each residual = (for each specific ordered pair) * A “residual plot” -- instead of X and Y graphed – usually has X and the residual value for each X 3

(6) Extrapolation vs. Interpolation (beyond)(inside) (7) Slope Interpretation for an LSRL: > For every one unit increase in X, on average, Y changes by this amount > Always put these in context! 4

(8) Correlation (“r”) – the degree to which a linear model fits a set of data (9) r-squared ( ): the % of the variation in the response values that can be accounted for by our linear model (with the explanatory variable that we are using) 5

(10) So how can we tell if a linear model is “good” at fitting the data set?  High correlation value (“r”)  Graphing it – the LSRL fits close to the points  Graphing the residuals – the residual plot is scattered with no pattern 6