統計学[国際環境学コース]

All classes in person: Class 1: Intro to course, basics of statistics and the R programming language Class 2: Multiple regression and logistic regression Class 3: Generalized linear models Class 4: Model selection and quality control Class 5: In-class exercise 1 Class 6: Fixed vs. Random Effects Class 7: Mixed linear models and quality control Class 8: General additive models Class 9: Multivariate linear models Class 10: Principal Components Analysis and NMDS Class 11: In-class exercise 2 Class 12: Final Topics and Review Class 13: FINAL EXAM

Lecture and Practical computer lab

Final Exam (100%)

This class combines lecture and practical application, and students will be tested on the material at the end. Familiarity with both the theory and the use of R will be assessed.