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
About this Course
Skills you will gain
- 5 stars83.12%
- 4 stars13.30%
- 3 stars1.94%
- 2 stars0.63%
- 1 star0.99%
TOP REVIEWS FROM INFERENTIAL STATISTICS
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.
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!
The course is very well explained I had to refer other materials for ANOVA technique to understand it better hence that part can be either improved OR more reference material be provided
Very good course on basic understanding of inferential statistics. Instructor was very clear in delivering the content. The lab work is very helpful in developing R knowledge.
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