PSY202H1 Chapter 16: PSY202 - Chapter 16 (Lecture 6-8)
Document Summary
Pearson correlation describes and measures a linear relationship between two variables. This relationship can be easier to see by drawing a straight line through middle of data points (identifying the centre of the relationship or central tendency) Linear regression is a procedure that identifies where line should be placed. Linear equations: linear relationship between variables x and y, a and b are fixed constant. B is beta and is the slope which determines how much y changes when x is increased by 1 point. A is alpha the y-intercept and determines when x= 0. E is the residual (error) term measuring difference between the value predicted by the regression model for given versus actual value (but not used in line of best fit) X is the value of the independent variable (x), what is predicting/explaining y: to obtain the line, just pick two points using the formula and then connect them together.
