PSY 707 - Intermediate Statistics II

(3 units)

This course provides a comprehensive overview of basic and advanced topics in regression analysis. It emphasizes statistical theory, research design, and practical applications in empirical research, along with hands-on development of procedural and computer skills. Topics include simple and multiple regression, diagnostics and remedial measures, model selection, generalized linear models, and path analysis.

Maximum units a student may earn: 3

Grading Basis: Graded
Units of Lecture: 3
Offered: Every Spring

Student Learning Outcomes
Upon completion of this course, students will be able to:
1. describe and interpret concepts and theories involved in linear regression models (both simple and multiple) and generalized linear models (e.g., logistic, probit, and poisson).
2. identify and appropriately utilize complicated models that involve polynomial or interaction terms.
3. apply assumption checks and outlier checks for regression models, including conducting appropriate model diagnostics and using proper remedial measures.
4. conduct model selection with attention to various model fit indices.
5. use appropriate regression analysis and to write up results and discuss the implications in research manuscripts.
6. utilize statistical software (e.g., R) to conduct statistical analysis.

Click here for course scheduling information. | Check course textbook information