Multiple Regression Analysis

From Practical Statistics for Educators
Revision as of 19:07, 16 November 2019 by Kuslis002 (talk | contribs) (→‎Collinearity and Multicollinearity)
Jump to: navigation, search

Collinearity and Multicollinearity

Collinearity is "a condition that exists when two predictors correlate very strongly" (Meyers, Gamst, & Guarino, 2017, p. 189).

Multicollinearity is a condition that exists when "more than two predictors correlate very strongly" (p. 189).


Contribution by: Britany Kuslis, WCSU Cohort 8

Reference: Meyers, S., Gamst, G., & Guarino, A.J. (2017). Applied multivariate research: Design and interpretation. Thousand Oaks, CA: Sage Publications.

Retrieved from "http://practicalstats.labanca.net/index.php?title=Multiple_Regression_Analysis&oldid=158"