This three-day workshop provides a comprehensive introduction to regression analysis, focusing on practical application using software such as Stata, R, and SPSS. Participants will gain essential skills for conducting robust regression analyses, interpreting results, and solving common data issues, all of which are crucial for advancing academic and professional research in various fields.

Topics Covered
Introduction to Regression , Understanding Variables , Relationship Exploration , Basic Concepts , Types of Regression , Model Basics , Interpreting Coefficients , Linearity Assumption , Estimating Parameters , Visualizing Relationships , Expanding Model Complexity , Handling Multiple Variables , Interpreting New Coefficients , Assumptions and Limitations , Coefficient Significance , Model Fit Analysis , Residuals Examination , Normality Checks , Assumptions Testing , Identifying Outliers , Significance tests , bivariate plots , correlations , Simple Linear Regression , numeric predictor , binary predictor , Interpretation , Model building , Dummy variables , Interpretation of adjusted coefficients , Research questions , AIC/BIC , Deviance , Adjusted R-squared , Model Assumptions , Model Selection , Exploring Associations , Multiple Linear Regression in Stata , Interaction terms , Univariable summary , Bivariate Associations , Simple Linear regression in R , Multiple Linear Regression , model selection