Bayesian World View of Cognition

Statistical Machine Learning

Resources

https://rkabacoff.github.io/datavis/

• Power analysis software: https://webpower.psychstat.org/wiki/models/index

General principles

• Avoid HARKing: Hypothesizing After the Results are Known
• Jamie’s recommendations
  • In the limitation section, talk about what will make you more confident in your statistical anlaysis.
  • For power analysis, focus on the main hypothesis. Don’t try to get enough power for every hypothesis you want to test.

Tips

• Remember to center your predictors
  • (A lesson from a mistake in a “Large-Scale, Multi-Lab” study. https://onlinelibrary.wiley.com/doi/10.1111/desc.70029)
• When there are multiple choices (excluding outliers or not), instead of creating multiple data sheets, create new variables that indicate which treatment of data is used.

Data Preparation

• Use meaning codes for missing values [1]
• A ‘data dictionary’ that includes the name of each variable, a description, and other information. [1]

Math

• Variance of a random vector $X$ along a direction $u$: $V[u^TX] = u^T V[X] u$

Basics

STAT 400: Statistics and Probability I

• Parameter describes a population; Statistic describes a sample
• Point estimate vs. Interval estimate
  • Point estimate is often mean, but can be medium, mode.
  • Interval estimate aka confidence interval.