Summary and Schedule
This is a new lesson built with The Carpentries Workbench.
| Setup Instructions | Download files required for the lesson | |
| Duration: 00h 00m | 1. Introduction to Categorical Data | What is categorical data and how is it usually represented? |
| Duration: 00h 10m | 2. Quantifying association | |
| Duration: 00h 30m | 3. Visualizing categorical data | How can I visualize categorical data in R? |
| Duration: 00h 40m | 4. Sampling schemes and probabilities |
Question 1 :::::::::::::::::::::::::::::::::::::::::::::::: |
| Duration: 00h 50m | 5. The Chi-Square test |
What are the null and alternative hypothesis of the chi-square
test? What are the expected counts under the null hypothesis? What is the test statistic for the chi-square test? How can I run the chi-square test in R? :::::::::::::::::::::::::::::::::::::::::::::::: |
| Duration: 01h 00m | 6. Categorical data and statistical power |
What determines the power of a chi-square test? Why is it difficult to determine significance for discrete data? What is the Fisher test and when should I use it? |
| Duration: 01h 10m | 7. Complications with biological data |
When are Fisher and Chisquare test not applicable for biological data? What are alternative methods? |
| Duration: 01h 20m | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
Learning goals for this lession
In this lesson, you’ll learn
- how to handle data sets containing categorical data in R,
- how to visualize categorical data,
- how to calculate effect sizes, and
- how to test for a difference in proportions.
Prerequisites
- Data handling and visualization using the
tidyversein R. We recommend- completing this tutorial (crash course, if you already have some experience in R)
- the carpentries R for ecologists (if you’re starting from scratch)
- Basics on statistical distributions (covered in this lecture)
- Basics on hypothesis testing (covered in this lesson)