About this course: 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
Taught by: Mine Çetinkaya-Rundel, Assistant Professor of the Practice
Department of Statistical Science
| Basic Info |
Course 2 of 5 in the
Statistics with R Specialization.
|
| Level | Beginner |
| Commitment | 5 weeks of study, 5-7 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
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| Audit | Purchase Course | |
|---|---|---|
| Access to course materials | Available | Available |
| Access to graded materials | Not available | Available |
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| Earn a shareable Course Certificate | Not available | Available |
Course materials are interesting and engaging.
Excellent course, great videos and supplemental material was extremely helpful.
While there is a lot of material in this course, it was taught very well and had good learning material in the accompanying book and practice problems.
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HH
What I learned best is not the formula, but the approach to test the conditions, the discussion of source of potential bias, the selection of inferential statistics methods.