Mathematical Biostatistics Boot Camp 2

Go to Course: https://www.coursera.org/learn/biostatistics-2

Introduction

### Course Review: Mathematical Biostatistics Boot Camp 2 on Coursera If you're looking to deepen your understanding of biostatistics and data analysis, the *Mathematical Biostatistics Boot Camp 2* offered on Coursera is a fantastic choice. This course serves as a comprehensive introduction to key concepts in statistical inference with a special focus on hypothesis testing and discrete data, providing the essential tools you need to tackle real-world problems effectively. #### Overview This course is tailored for individuals who want to enhance their skills in data analysis within the context of biostatistics. It dives deep into foundational concepts that are instrumental in making data-driven decisions, especially when working with biological data. By the end of the course, you will be equipped with the knowledge to conduct hypothesis tests, analyze binomial data, and apply various statistical techniques to real-world scenarios. #### Syllabus Breakdown 1. **Hypothesis Testing** In this introductory module, you'll become acquainted with hypothesis testing—a fundamental pillar in statistics. The course covers testing for one and two group settings, alongside the concept of statistical power. Expect engaging video lectures, hands-on homework, and an opportunity to assess your knowledge through a quiz. 2. **Two Binomials** Moving forward, the course focuses on methods for analyzing two binomials. Here, you’ll learn about the odds ratio, relative risk, and risk differences, along with detailed instruction on constructing confidence intervals using the delta method. This segment emphasizes practical applications and reinforces learning through quizzes that challenge your understanding. 3. **Discrete Data Settings** The third module delves into testing strategies for discrete data. You’ll explore essential tests including Fisher's exact test and various contingency table tests. This module is particularly valuable for those dealing with categorical data and provides insight into the observed minus expected squared over the expected formula, a widely applicable statistical method. 4. **Techniques** The final module is an amalgamation of important statistical techniques, including methods for analyzing discrete matched pairs data and several classical non-parametric methods. This variety enriches your toolkit with versatile options for data analysis. #### Recommendations *Mathematical Biostatistics Boot Camp 2* is recommended for students, researchers, and professionals seeking to solidify their statistical knowledge in a biostatistical framework. The course is suitable for individuals with some background in statistics but it also serves as a great refresher for those who may need to brush up on their skills. One of the standout features of this course is how it balances theory with practical application. The inclusion of quizzes after each module ensures that you are not just passively consuming content, but actively engaging with the material, which is crucial for retention and understanding. Additionally, the instructors are experienced professionals in the field of biostatistics, providing insights that go beyond textbooks and preparing you for real-life applications of the concepts learned. #### Conclusion If you are eager to sharpen your data analysis skills and deepen your understanding of statistical inference in biostatistics, I highly recommend enrolling in *Mathematical Biostatistics Boot Camp 2* on Coursera. The rigorous curriculum, comprehensive material, and interactive assessment methods make it a valuable educational experience. Whether you're preparing for further advanced studies or looking to apply these techniques in your professional life, this course will provide a solid foundation. Give it a try and empower your statistical analysis capabilities!

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.

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!

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.

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.