PSYC 201W Chapter Notes - Chapter 8: Simple Linear Regression, Regression Analysis, Scatter Plot

• School: Simon Fraser University
• Department: Psychology
• Course: PSYC 201W
• Professor: Matthew Sigal

Document Summary

Regression analysis: ability to predict scores on one variable from one or more variables. Regression equation: equation from which one can predict scores on one variable from one or more other variables: regression lines show the nature and the linearity of the relationship. Line of best fit (least squares regression line) Intercept: point where our line crosses the y-axis (x=0) Multiple regression analysis: statistical procedure by which an equation is derived that can predict one variable from a set of variables: using more than one predictor improves the accuracy of the prediction. Formal test of model fit: did we account for a significant amount of the variation in y, f-statistic that is the ratio of variance accounts for over total variation. Other tests: test of significance for the intercept, test of significance for the slope. Study designs and steps: scatterplots are great summaries for linear regression models, they do not address everything we need.