Learn fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples.
Mathematical Biostatistics Boot Camp 2
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Mathematical Biostatistics Boot Camp 2
This course is part of Advanced Statistics for Data Science Specialization
Instructor: Brian Caffo, PhD
20,836 already enrolled
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Gain insight into a topic and learn the fundamentals.
4.3
(132 reviews)
11 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
Skills you'll gain
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Assessments
8 assignments
Taught in English
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This course is part of the Advanced Statistics for Data Science Specialization
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There are 4 modules in this course
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.
What's included
12 videos1 reading2 assignments
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!
What's included
8 videos2 assignments
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.
What's included
7 videos2 assignments
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.
What's included
16 videos2 assignments
Instructor
Instructor ratings
4.6 (19 ratings)Offered by
Recommended if you're interested in Probability and Statistics
Stanford University
DeepLearning.AI
University of California, Santa Cruz
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