Statistics
1
Statistics
2
Probability
2.1
Intuition for Probability
2.2
Pandemic Risk Management
3
Big Data Paradox
3.1
Quarantine fatigue thins fat-tailed impacts
3.2
Herd Immunity impossible with new Mutants
3.3
Danish Mask Study
4
Fat Tails
4.1
Extremes
4.1.1
Catastrophe Principle
4.2
Statistical Consequences of Fat Tails
4.2.1
Power Law Distributions
4.3
Lindy Effect
5
R Programming Language
5.1
Reinsurance
5.2
Superspreaders
5.3
Vaccine
6
Inequality
7
Autocorrelation
7.1
Dunning-Kruger is Autocorrelation
8
Causation
8.1
Liang Causality
8.2
Causation in Chaotic Dynamic Systems
8.3
Causal Inference
8.3.1
Causal Inference with Spatio-Temporal Data
8.4
Rethinking Causation in the Social Sciences
9
Hypothesis Testing
9.1
R Testing
9.2
Connecting to Theory
9.3
Placebo Powerless
9.4
GLMM
9.5
Logit
9.5.1
Odd’s Ratio
10
P test
10.1
P-Value Hacking
10.2
Bootstrapping instead of p-values
10.3
Probit
11
Spurious Correlation
11.1
Trending Variables
12
Stationarity
12.1
Record Events
13
Collapse
13.1
AMOC Collapse EWS (Early Warning Signals)
14
Power laws
14.1
Generative Models
14.2
Income Distribution Power Law
14.3
Timescaling Rainfall
14.4
Billionaire Power Law
15
Syntetic Control
16
Econometrics
I Appendices
Appendices
A
About
B
Links
C
NEWS
D
Sitelog
E
Identification
On Github
Statistics
C
NEWS