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Lecture 14

Lecture 14 - Bivariate Regression Analysis
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Department
Political Science
Course
POL3371
Professor
Ivan Katchanovski
Semester
Winter

Description
March 11, 2014 Bivariate Regression Analysis RegressionAnalysis  Widely used to test research hypotheses o Can test more than one research hypothesis simultaneously keeping all other factors constant  Origins: Francis Galton and eugenics  Assumes linear relationship  Variables at interval-ratio level o In practice, can also be used for ordinal variables if they are treated as interval- ratio o Can be used for nominal variables only when they are transformed into dummy variables Bivariate Regression Analysis  Bivariate linear regression o Examines the relationship between two variables  Regression o Can determine how much of the variation in the dependent variable is explained (predicted) by the independent variable o If the independent variable is a statistically significant predictor of the dependent variable o Direction of relationship Unstandardized Regression Coefficient  Regression coefficient  Positive sign of regression coefficient: positive effect of the independent variable on the dependent variable  Negative sign of regression coefficient: negative effect of the independent variable on the dependent variable Statistical Significance  Statistical significance of Regression Coefficient: o Statistically significant if in SPSS p(obtained) = < 0.05 or 0.01 or 0.001 o For small N: can be statistically significant if SPSS p(obtained) < 0.1 o Statistically non-sig
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