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