Curriculum
- 10 Sections
- 60 Lessons
- Lifetime
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- Survival Analysis9
- Expectation Maximization (EM)5
- Multiple Hypothesis Testing7
- Computational Statistics11
- 6.0Gauss Newton – Non Linear Least Squares
- 6.1Riemann Sum, Rejection Sampling, Importance Sampling – Part 1
- 6.2Riemann Sum, Rejection Sampling, Importance Sampling – Part 2
- 6.3Rejection Sampling – Bounding Constant
- 6.4Rejection Sampling – Proof
- 6.5Sampling Importance Resampling (SIR)
- 6.6Profile Likelihood
- 6.7Profile Likelihood – what is a profile?
- 6.8Profile Likelihood – simpler examples
- 6.9Laplace’s Method
- 6.10Random Sampling – Uniform & Inverse Transform
- Gaussian Process Regression5
- Other5
- Factor Analysis9
- 9.0Material
- 9.1(Exploratory) Factor Analysis – Introduction
- 9.2(Exploratory) Factor Analysis – Estimation
- 9.3(Exploratory) Factor Analysis – Rotation
- 9.4(Exploratory) Factor Analysis – Code in R
- 9.5Exploratory vs. Confirmatory Factor Analysis
- 9.6(Confirmatory) Factor Analysis – Code in R
- 9.7SEM – Structural Equations Modelling
- 9.8SEM – Code in R
- Time Series Analysis5
- Quantile Regression3
- Clustering1