### Table of Contents

# Statistics

Statistics are the useful numbers that get called upon in any number of situations. Sadly they're often misused and abused mainly by politicians, spin-doctors and the media who have an agenda. Statisticians *per se* are a fairly honest bunch (at least those I've met, and I'm including myself in that!).

# Regression

# Visualisation

# Bayesian

Worthy of its own page.

# Probably Approximately Correct

# Software Tips and Tricks

I used to use Stata and the Open Source R, but these days I also use Python. Increasingly these days Stata sees little look in as I've become quite enamoured with the R ecosystem, but will often cross-validate work done in one package by repeating it in the other or revert to Stata if something isn't available in R (increasingly rare). Whilst statistical packages are great at analysing data databases are far more suited to the task, particularly when there is a large amount of data and multiple tables and I've opted to use PostgreSQL. Detailed below are tips and tricks on getting things done in these software packages.

Notes on using either package can be found at…

# Links

## Software

### Frameworks

## PPDAC

## Statistical Methods/Concepts

- Understanding Statistics shows various statistical issues in a graphical manner (particularly useful for dichotomisation).

### Markov Chains

### PAC

### Visualisations

- Visualizations | R Psychologist interactive graphs demonstrating statistical principles.

## Deep Learning

### Interpretability

## Online Courses/Resources

## Statisticians

- Edward Tufte : Proponent of clear presentation styles, particularly with graphs.

## Communication

- Statcheck detecting errors in published results.

## Datasets

## Papers

## GIS

## Neural Networks

### Generative Adversarial Networks

These can be used to generate new images such as faces, MPs, dicks…

- TDPDNE (NSFW!!!)

## Free Books

- An Introduction to Statistical Learning same material using the tidymodels ISLR tidymodels Labs
- Statistical Analysis Handbook which is particularly useful for its PPDAC section.

### R

## Bayesian Statistics

## Podcasts

statistics R stata ess howto tips programming