This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data

Inferential Statistics

Inferential Statistics
This course is part of Data Analysis with R Specialization
Instructor: Mine Çetinkaya-Rundel
Access provided by Guyana Online Academy of Learning - GOAL
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Reviewed on Aug 16, 2016
The teaching is good, the course is a little heavy and a lot to take in in the later weeks. But, as a further grounding for statistics and R, I would very much recommend it.
Reviewed on Jan 21, 2019
The concepts are explained in a very simple and effective manner with the help of a case study. Background knowledge of R will be very handy if one wants to cover the topics at a faster rate.
Reviewed on Jan 7, 2021
The final project does not help, for example someone used discrete data 1,2,3,4,5 .... ,40 to compute a p.value as if it was normal. It is too general and does not fill the purpose of the course.
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