SBS 340 Regression Analysis
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This SBS 340 Regression Analysis course aims to provide the basic knowledge of regression analysis related to empirical work in the social sciences. Regression analysis is the application of statistical techniques when using data to test theories/hypotheses of the social sciences. The course focuses on the classic linear regression model. Students will gain experience collecting data from various sources, analyzing data using regression and statistical analysis, interpreting results, and writing research papers.
Principal component regression is a technique used to analyze multiple regression data that have multicollinearity. When multicollinearity occurs, the least squares estimates are unbiased, but their variance is large so that they may be far from the true value. By adding some degree of bias to the regression estimate, principal component regression can reduce the standard error. It is hoped that the final result will be a more reliable estimate. NCSS also provides another bias regression method, namely ridge regression.
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