# Hypothesis testing using R

The main purpose of this hands-on workshop is to familiarize participants with key concepts of inferential statistics using the R software environment, a powerful, popular and free statistical and graphical programming language. Participants will learn about how to compute, report, and interpret hypothesis tests using R for popular statistical models such as correlation, contingency tables, chi-square test, t-test and ANOVA. To facilitate the learning process the main concepts will be illustrated by concrete examples and exercises.

## Recommended Participants

This workshop is relevant to biologists, researchers, psychologists, economist and generally any student who wishes to understand how to choose the right statistical test depending on the context/condition and to conduct the analysis by themselves using R. The workshop is relevant for all disciplines, although examples and exercises will focus on biological datasets. Prior knowledge of R is required (Introduction to R workshop is strongly recommended) as the basics of R will not be covered.

## Learning Objectives

- This one-day workshop will provide attendees with a friendly, gentle introduction to the theory behind hypothesis testing with R.

## Syllabus

- Choose the right statistical test appropriate for the data and the research questions
- Carry out inferential statistics in R
- Generate plots, figures and tables using specific R packages to illustrate the results
- Interpret the output and report the results