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
- 5 stars83.24%
- 4 stars13.21%
- 3 stars1.95%
- 2 stars0.63%
- 1 star0.95%
I learnt a lot about inferential statistics from this course. It help me to understand better why I used one inferential method instead of another, and the assumptions and conditions.
Great course. If you put in a little effort, you will come out with a lot of new knowledge. I recommend using the book after you have seen the movies. It gives a deeper picture of how it works. Great!
Very well taught. Student given an opportunity to explore and search for ways to solve problems by themselves. Professor (mentor) and other students always ready to help should you get stuck!
This course by Professor Çetinkaya-Rundel is awesome because it is taught in a very clear and vivid way. Lab section and forum are so dope that I love them so much! Definitely strong recommendation!!!
Cost of the Course
Can I just enroll in a single course? I'm not interested in the entire Specialization.
Will I receive a transcript from Duke University for completing this course?