PSYC 201W Lecture Notes - Lecture 6: Confounding, Statistical Process Control, Simple Linear Regression

• School: Simon Fraser University
• Department: Psychology
• Course: PSYC 201W
• Professor: george alder

Document Summary

Correlations reveal the degree of statistical association between two variables. X and y do(cid:374)"t ha(cid:448)e a(cid:374)ythi(cid:374)g to do (cid:449)ith i(cid:374)depe(cid:374)de(cid:374)t a(cid:374)d depe(cid:374)de(cid:374)t (cid:448)a(cid:396)ia(cid:271)les. Statistically analyze whether the different conditions of x have produced differences in y. Attempt to eliminate confounding variables by controlling the experimental environment. Statistically analyze whether there is an association between x and y. Attempt to reduce the influence of confounding variables through statistical control and where possible through special research designs. X and y move in different directions. Two dimensional graph (x on one axis and y on the other axis) Pea(cid:396)so(cid:374)"s (cid:396: correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. 10 - . 29 = small association weak. 30 - . 49 = medium association moderate. A graph in which data points portray the intersection of x and y values can reveal nonlinear relations between variables the the pearsons r statistics cannot detect.