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Explore advanced regression methods, including dummy-variable and interaction effects, and master the assumptions and diagnostics necessary for robust statistical modeling in Stata. This course deepens your understanding of regression analysis and prepares you to handle complex data relationships.
This course delves into advanced regression techniques such as dummy-variable regression, interaction and moderation effects, and the critical evaluation of regression assumptions. Learners will gain expertise in diagnosing and addressing issues like multicollinearity, non-linearity, and influential observations. The course also introduces logistic regression and survival analysis, equipping participants to analyze a wide range of data types and research questions.
Through a blend of conceptual explanations and practical Stata demonstrations, the course emphasizes the application of advanced regression methods and diagnostic tools. Learners build on their foundational skills to tackle more complex analytical challenges with confidence.
This course is part two of a three-course Specialization designed to build a complete and cohesive understanding of the subject. While it offers valuable skills on its own, you'll gain the most benefit by progressing through all three courses as a structured learning journey.
This course is based on Applied Statistics Using Stata, by Mehmet Mehmetoglu and Tor Georg Jakobsen.
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