Statistics

Welcome to our sixth practical experience in R. Throughout the following notes, I will introduce you to a couple of simple parametric test. Whilst parametric tests are used extremely often in biological statistics, they can be somewhat challenging to fit to your data as you will see soon. To do so, I will enlist the sparrow data set we handled in our first exercise. Additionally, todays seminar is showing plotting via base plot instead of `ggplot2` to highlight the usefulness of base plot and show you the base notation.

Answers and solutions to the exercises belonging to chapter 13 in [Satistical Rethinking 2](https://xcelab.net/rm/statistical-rethinking/) by Richard McElreath.

Answers and solutions to the exercises belonging to chapter 14 in [Satistical Rethinking 2](https://xcelab.net/rm/statistical-rethinking/) by Richard McElreath.

Answers and solutions to the exercises belonging to chapter 15 in [Satistical Rethinking 2](https://xcelab.net/rm/statistical-rethinking/) by Richard McElreath.

Answers and solutions to the exercises belonging to chapter 16 in [Satistical Rethinking 2](https://xcelab.net/rm/statistical-rethinking/) by Richard McElreath.

My personal musings on statistical education for biologists.

An exploration of bayesian networks as a tool for identification of causal relationships.

First steps in macroecological analyses in `R` using cluster analyses on remote sensing data and tracking shifting biomes through time.

BioStat 101 material which ought to serve as an introduction to the basics of biostatistics using `R` for B.Sc. students of biology.

A collection of talks predominantly aimed at M.Sc. students and related to general topics of biostatistical concern I have given throughout the years.