DataCamp
FreeInference for Numerical Data in R
4.9(107)14k studentsADVANCEDEnglish
Korshub's take
Overview
This course covers inferential techniques for numerical data in R using dual methodologies: resampling approaches (bootstrapping and permutation) alongside classical theoretical techniques based on the t-distribution. You examine when and how to implement hypothesis testing routines accurately.
Who It Is For
Advanced researchers and data analysts looking to master resample-based and theoretical numerical inference in R.
Key Takeaways
- Utilize bootstrapping and permutation for resample-based testing.
- Calculate confidence intervals and perform t-tests.
- Execute ANOVA to analyze variance across numerical data groups.
About this course
In this course, you'll learn how to use statistical techniques to make inferences and estimations using numerical data. This course uses two approaches to these common tasks. The first makes use of bootstrapping and permutation to create resample based tests and confidence intervals. The second uses theoretical results and the t-distribution to achieve the same result. You'll learn how (and when) to perform a t-test, create a confidence interval, and do an ANOVA!
Advertisement
