This is the first post for the blog Stats and R, just to introduce it. This blog aims at helping academics and professionals working with data to grasp important concepts in statistics and to apply them in R.
The goal of this website is to make statistics easy to understand by illustrating with examples and using plain English. When possible, for all statistical concepts covered here, I also write an article on how to apply these concepts in R.
If you are new to this blog and to R, I invite you to start with the following articles:
- How to install R and RStudio
- How to import an Excel file in RStudio
- Descriptive statistics by hand or in R
You can also:
- See all articles or articles by categories for more advanced articles
- Learn more about who is behind this blog
- Follow me on Medium or Twitter
- Subscribe to this blog to receive updates every time a new article is published
- Contribute by writing a guest post
- See the most recent comments so you can follow the discussion
Thanks in advance for reading.
As always, if you have a question or a suggestion related to the topic covered in this article, please add it as a comment so other readers can benefit from the discussion.
- Correlogram in R: how to highlight the most correlated variables in a dataset
- An efficient way to install and load R packages
- Do my data follow a normal distribution ? A note on the most widely used distribution and how to test for normality in R
- Fisher’s exact test in R: independence test for a small sample
- Chi-square test of independence by hand
Originally published at https://statsandr.com on December 16, 2019.