Schedule

The schedule is approximate. Course material will be updated here throughout the week.

Day 1

• Course introduction (PDF)
• Introduction to hypothesis testing
• Significance and p-values
• Statistical tests I (parametric tests)

Day 2

• Intro to reproducibility (PDF)
• Github (optional tutorial)
• Distributions and functions in R
• Statistical tests II (non-parametric tests)
• Using chatGTP for stats

Day 3

• Which test should you use?
• R examples (parametric and non-parametric tests)
  • Bryozoan data
  • Sampling proxy data
  • t-test
  • ANOVA
  • Shapiro-Wilk’s test
  • Wilcoxon test
  • Kruskal-Wallis test
  • Tukey HSD test
  • Steel-Dwass test
  • Correlation
• Summary

Day 4

• Presentations (date to be decided)