Advanced stats and Open Science

BIO8940

Julien Martin

BIO 8940

2025-01-08

A bit about …

… me

  • Evolutionary ecologist

  • Not a statisticians by training

  • Complex data

  • Enjoy coding

  • Humour of a 5 years old

… you

  • Name

  • PI

  • Subject

  • R knowledge

  • Expectation from the course

Structure of the course

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

Teaching style

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

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

Assessment

In class (50%)

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

Project (50%)

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

Software and accounts

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

Accounts

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

What is expected from you

What is expected from you

  • Weekly Reading

  • In class participation

  • Do the praticals