Learn fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples.
Overview
Syllabus
- Hypothesis Testing
- In this module, you'll get an introduction to hypothesis testing, a core concept in statistics. We'll cover hypothesis testing for basic one and two group settings as well as power. After you've watched the videos and tried the homework, take a stab at the quiz.
- Two Binomials
- In this module we'll be covering some methods for looking at two binomials. This includes the odds ratio, relative risk and risk difference. We'll discussing mostly confidence intervals in this module and will develop the delta method, the tool used to create these confidence intervals. After you've watched the videos and tried the homework, take a crack at the quiz!
- Discrete Data Settings
- In this module, we'll discuss testing in discrete data settings. This includes the famous Fisher's exact test, as well as the many forms of tests for contingency table data. You'll learn the famous observed minus expected squared over the expected formula, that is broadly applicable.
- Techniques
- This module is a bit of a hodge podge of important techniques. It includes methods for discrete matched pairs data as well as some classical non-parametric methods.
Taught by
Brian Caffo
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Reviews
4.0 rating, based on 4 Class Central reviews
4.3 rating at Coursera based on 133 ratings
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This course was not well taught. There are tons of errors on slides throughout the lectures. It could be though.Brian Caffo clearly knows his stuff and is excited about the subject matter, but needs to zero in his focus. I think this class would have been way better off taught on a chalk board than through slide.
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I think that this course is a little bit more demanding than Mathematical Biostatistics Boot Camp 1(MBBC1). It is not only the fact that you need to know the material in MBBC1 but it takes more time to understand the material represented in this class. This aside, I believe that this course is amazing for learning some more statistics and I like the insights provided by the instructor.
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