Welcome to my website! · below are reources covering statistics and psychometrics principles

Statistical Foundations &
Psychometric Methods

Welcome to my stats and psychometrics website — I am curating a resource for students who are learning about the principles of inferential statistics and the field of psychometrics (measurement assumptions inference rests) - I hope you find this useful.

Track A · Inferential statistics: first principles and concepts Track B · Psychometrics: the science of behavioural measurement Mobile-friendly
Track A · 4 parts

Statistical Foundations

Building inference from first principles — what averaging buys you, how the standard inferential tests actually work, when their assumptions hold, and how to plan a study honestly.

Part A1
LLN, CLT, & Standard Error
Why averaging produces precise estimates. The Law of Large Numbers, the Central Limit Theorem, and the σ/√N formula that drives all of inference.
Read Part 1 →
Part A2
When the Chain Breaks
ANOVA in detail, then what to do when its assumptions fail — Linear Mixed Models, partial pooling, and an introduction to IRT.
Read Part 2 →
Part A3
Where Does Your Data Come From?
Generative distributions, the mean–variance independence question, and the model-matching map for non-Gaussian DVs (GLMs and GLMMs).
Read Part 3 →
Part A4
Effect Size & Power Analysis
Cohen's d, the SD-vs-SE replication bridge, the d² scaling rule, and the AnCred framework for credibility beyond p < .05.
Read Part 4 →
Track B · 3 parts

Measurement & Psychometrics

A companion track on what is actually being measured — the assumptions every Likert scale silently makes, the reliability of psychological measurement, and what attenuation does to the inferences that follow.