SOC222H5 Lecture Notes - Menu Bar, Location Test, Effect Size
Document Summary
Terms to know effect size linear (equation) parameter constant a slope b variance covariance definition formula computational formula correlation coefficient r scatter outlier proportion of variation explained (pve) coefficient of determination r2 eta . 1: how much is the effect? (what is the effect size) Find the regression line that fits the data best. Best fit means: comes the closest to all the cases. The equation for a straight line is: y = a + b (x) Y stands for values of the dependent variable. X the independent variable: linneman, pp. Marks = a + b (days) using the equation of the regression line. Income (in sh) = 40 + 2 x hours. Predicted income = 40 + 2 x 0 = 40. Predicted income = 40 + 2 x 10 = 40 + 20 = 60. Predicted income = 40 + 2 x 30 = 40 + 60 = 100. Covariance: how two things change together (systematically, unrelated way).
