140.648.01 ESSENTIALS OF PROBABILITY AND STATISTICAL INFERENCE III: THEORY OF MODERN STATISTICAL METHODS
Builds on the concepts discussed in 140.646 and 140.647 to lay out the foundation for both classical and modern theory/methods for drawing statistical inference. Includes classical unbiased estimation, unbiased estimating equations, likelihood and conditional likelihood inference, linear models and generalized linear models, and other extended topics. De-emphasizes mathematical proofs and replaces them with extended discussion of interpretation of results and examples for illustration.
Upon successfully completing this course, students will be able to:
Describe the theoretical basis for the current methods used in statistical analysis
- Tuesday 3:30 - 4:50
- Thursday 3:30 - 4:50
Working knowledge of calculus