MKT 3340 Study Guide - Midterm Guide: Spurious Relationship, Regression Analysis, Dependent And Independent Variables

• School: UT-Dallas
• Department: Marketing Management
• Course: MKT 3340
• Professor: Prasad Ashutosh

Document Summary

Correlation: measures the strength of linear association between two metric variables. Regression: measures the strength of relationships between a metric variable (y) and a function fo one or more metric variables (x) Population: population correlation (p, y = alpha + beta(x) + epsilon. Sample: sample correlation (r, sample regression model: y = a + b x + e. Correlation coefficient: index number, between range of -1. 0 and +1. 0 that communicates both the strength and the direction of the linear relationship between two metric variables. Covariation: the amount of change in one variable systematically associated with a change in another variable, vary together, the difference between value and means are similar. Positive correlation between two metric variables x and y: observations of high values on one are associated with high values of the other and vice versa. Spurious correlation: although two variables may be correlated, this does not imply causality.