Advanced stats and Open Science

BIO8940

Author

Affiliation

Julien Martin

BIO 8940 - Lecture 1

1 A bit about …

1.1 … me

• Evolutionary ecologist

• Not a statisticians by training

• Complex data

• Enjoy coding

• Humour of a 5 years old

1.2 … you

• Name

• PI

• Subject

• R knowledge

• Expectation from the course

2 Structure of the course

2.1 Topics

• Intro to github with exercises
• Intro to Open science
• Intro to rmarkdown and to workflowr
• Mixed models
  • Intro, why, when and how
  • Non gaussian, non-linear ?
  • multivariate ?
• p-values and their limits

2.2 Teaching style

• Minimum slides from myself
• flipped classroom or learning by problems
• Session = mixed of lecture, discussion and exercises

2.3 Schedule

Week	Theme
1	Intro
2	Github
3	Markdown / Quarto
4	Lm & glm
5	Causal structure
6	Lmm
7	Bayesian approach
8	Glmm
9	to
10	be
11	decided
12	together

3 Assessment

3.1 In class (50%)

• participation to discussion (20%)
• presentation on a given topic in small teams (30%)

3.2 Project (50%)

• analysis of data using techniques from courses or beyond
• Report written using Rmarkdown
• posted on Github classroom

4 Software and accounts

4.1 Softwares

• R (version 4.0 or higher)
• Text editor: Rstudio or VSCode
• R packages (up to date)
  • open science: rmarkdown, tinytex
  • mixed models: lme4, gremlin, glmmTMB, MCMCglmm
  • latex: full version or tinytex

4.2 Accounts

• github (https://github.com/)
• Open Science Framework (OSF, https://osf.io/)

5 What is expected from you

5.1 What is expected from you

• Weekly Reading

• In class participation

• Do the praticals