MKT 500 Chapter Notes - Chapter 15: Scatter Plot, Dependence Analysis, Multicollinearity

• School: Ryerson University
• Department: Marketing
• Course: MKT 500
• Professor: Julie Kellershohn

Document Summary

Regression analysis: a predicive analysis technique in which one or more variables are used to predict the level of another by use of the straight-line formula. Bivariate (simple) regression: only two variables are being analyzed: formula for a straight-line: y = a + bx. Dependent variable: that which is predicted, and it is customarily termed y in the regression straight-line equaion. Independent variable: that which is used to predict the dependent variable, and is termed x in the regression formula. There is no cause-and-efect relaionship or true dependence between the dependent and independent variable; it is strictly a staisically relaionship, not causal. Least squares criterion: a way of guaranteeing that the straight line that runs through the points on the scater diagram is posiioned to minimize the verical distances away from the line of the various points. Outlier: a data point that is substanially outside the normal range of the data points being analyzed.