Statistical Procedures
Topics
- estimating population parameters using random samples
- parametric vs resampling methods
- the role of sample size
- null hypothesis significance testing (NHST)
- what is a p-value
- type I and type II errors
- effect size
- power
- confidence intervals
- parametric vs resampling methods
- Maximum Likelihood Estimation (MLE)
- likelihood function
- MLE for the mean and variance of a normal distribution
- estimating psychometric functions
Notes
- Statistics I: Parametric Statistical Tests
- Statistics II: Resampling, Bootstrapping, & Cross-Validation
- Statistics III: Maximum likelihood estimation (MLE)
Notebooks
- stats_demo1.ipynb (right-click to download)
- stats_demo2.ipynb (right-click to download)
Additional Resources
- the Tutorials listed here are good, in particular “Review of Basic Statistics”: https://designingexperiments.com/supplements/
- Designing Experiments and Analyzing Data: A Model Comparison Perspective] by Maxwell, Delaney, and Kelley
- chapter 1 Using p-values to test a hypothesis from the book Improving Your Statistical Inferences by Daniel Lakens
- Answering questions with data book by Matthew Crump, Danielle Navarro, and Jeffrey Suzuki
- Learning Statistics with R by Danielle Navarro (and an adaptation for Python: Learning Statistics with Python)
- Dance of the p-values (YouTube) by Geoff Cumming
Bayesian Approaches
- Introduction to Applied Bayesian Statistics and Estimation for Social Scientists by Scott Lynch (2007)
- Doing Bayesian Data Analysis by John Kruschke (2015)
- Frequentism and Baysianism: A Practical Introduction by Jake VanderPlas