Course Summary
Learn biostatistics and how to apply statistical methods to analyze data in health sciences with this course. Gain a deeper understanding of the concepts and techniques used in statistical analysis of clinical trials, epidemiology, and more.Key Learning Points
- Master the fundamental concepts of biostatistics
- Learn how to apply statistical methods to analyze data in health sciences
- Understand the concepts and techniques used in statistical analysis of clinical trials, epidemiology, and more
Related Topics for further study
Learning Outcomes
- Understand the fundamental concepts of biostatistics
- Apply statistical methods to analyze data in health sciences
- Master the techniques used in statistical analysis of clinical trials, epidemiology, and more
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of statistics
- Familiarity with Microsoft Excel
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Biostatistics in Public Health
- Statistical Analysis in Epidemiology
- Data Analysis and Statistical Inference
Related Education Paths
Notable People in This Field
- David Spiegelhalter
- Nate Silver
- Florence Nightingale
Related Books
Description
Learn fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples.
Outline
- Hypothesis Testing
- Hypothesis Testing
- More Hypothesis Testing
- General Rules of Hypothesis Testing
- Two-sided Tests
- Confidence Intervals & P Values
- Power
- Calculating Power
- T Tests & Monte Carlo
- Two Sample Tests - Matched Data I
- Two Sample Tests - Matched Data II
- Two Sample Tests - Regression to the Mean
- Two Sample Tests - Two Independent Groups
- Syllabus
- Module 1 Homework (Not counted toward final grade)
- Module 1 Quiz
- Two Binomials
- Two Sample Binomial Tests - Score Statistic
- Two Sample Binomial Tests - Exact Tests
- Two Sample Binomial Tests - Comparing 2 Binomial Proportions
- Relative Risks & Odds Ratios - Relative Measures
- Relative Risks & Odds Ratios - The Relative Risk
- Relative Risks & Odds Ratios - The Odds Ratio
- Delta Method
- Delta Method & Derivation
- Module 2 Homework
- Module 2 Quiz
- Discrete Data Settings
- Fisher's Exact Test
- Hyper-Geometric Distribution
- Fisher's Exact Text in Practice & Monte Carlo
- Chi Squared Testing
- Testing Independence
- Generalization
- Goodness of Fit Testing
- Module 3 Homework
- Module 3 Quiz
- Techniques
- Simpson's Paradox
- Simpson's Paradox, more examples
- Weighting
- CMH test
- Case Control Sampling
- Exact inference for The Odds Ratio
- Matched 2x2 Tables
- Dependence and Marginal Homogeneity
- Estimation of the Marginal Difference in Proportions
- Odds and Ends for Matched 2x2 Tables
- the sign test
- the sign rank test
- the rank sum test
- Poisson distribution
- Poisson likelihood
- Poisson P-value calculation
- Module 4 Homework
- Module 4 Quiz
Summary of User Reviews
Find out what users are saying about Biostatistics 2 on Coursera. Overall, the course is highly rated and praised for its comprehensive content. Many users appreciate the course's ability to break down complex statistical concepts into easy-to-understand lessons.Key Aspect Users Liked About This Course
Comprehensive content that breaks down complex statistical concepts into easy-to-understand lessonsPros from User Reviews
- Excellent course for beginners and advanced learners in biostatistics
- Great pacing and structure of the course
- Instructors are knowledgeable and provide clear explanations
- Hands-on exercises and real-life examples help to reinforce the concepts learned
- Great support from the course community and teaching assistants
Cons from User Reviews
- Some users found the course too challenging without prior statistical knowledge
- The course can be quite time-consuming
- Some users feel that the assessments are too difficult and not representative of the course material
- The course doesn't cover certain topics in depth
- Some users experienced technical difficulties with the platform during the course
Brian Caffo, PhD
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