Biostatistics with Python: Apply Python for biostatistics with hands-on biomedical and biotechnology projects

by Darko Medin

Overview

Learn how to utilize biostatistics with Python for excelling in research and biomedical professions with practical exemplar projects

• Bridge the gap between biostatistics and life sciences with Python
• Work with practical exercises for real-world data analysis in biology and medicine
• Access a portfolio of exemplar projects in the domains of biomedicine, biotechnology, and biology
• Purchase of the print or Kindle book includes a free PDF eBook

What you will learn

• Get to grips with the basics of biostatistics and Python programming
• Clean and describe data using Python
• Familiarize yourself with hypothesis testing and effect size analysis
• Explore predictive modeling in biostatistics
• Understand clinical study design and survival analysis
• Gain a clear understanding of the meta-analysis of clinical research data
• Analyze biological variables with Python
• Discover practical data analysis for biological research

This book is for life science professionals, researchers, biomedical professionals, and aspiring biostatisticians who want to integrate biostatistics into their work or research. A basic understanding of life sciences, biology, or medicine is recommended to fully benefit from this book.

Product Details

ISBN-13:	9781837631834
Publisher:	Packt Publishing
Publication date:	11/29/2024
Sold by:	Barnes & Noble
Format:	eBook
Pages:	374
File size:	18 MB
Note:	This product may take a few minutes to download.

About the Author

Darko Medin is a researcher and a biostatistician who graduated from the Faculty of Mathematics and Natural Sciences, Experimental Biology and Biotechnology, University of Montenegro. Darko is an expert biostatistician, especially in the fields of research and development in the biotech and pharma industries. He is a Python-based data scientist with more than 10 years of experience in the areas of clinical biostatistics and biomedical research. As a biologist and data scientist, he has worked with many research companies and academic institutions around the world and is an experienced machine learning and AI developer.

Table of Contents

Table of Contents

1. Introduction to Biostatistics
2. Getting Started with Python for Biostatistics
3. Exercise 1 – Cleaning and Describing Data Using Python
4. Part 1 Exemplar Project – Load, Clean, and Describe Diabetes Data in Python
5. Introduction to Python for Biostatistics
6. Biostatistical Inference Using Hypothesis Tests and Effect Sizes
7. Predictive Biostatistics Using Python
8. Part 2 Exercise – T-Test, ANOVA, and Linear and Logistic Regression
9. Biostatistical Inference and Predictive Analytics Using Cardiovascular Study Data
10. Clinical Study Design
11. Survival Analysis in Biomedical Research
12. Meta-Analysis – Synthesizing Evidence from Multiple Studies
13. Survival Predictive Analysis and Meta-Analysis Practice
14. Part 3 Exemplar Project – Meta-Analysis of Survival Data in Clinical Research
15. Understanding Biological Variables
16. Data Analysis Frameworks and Performance for Life Sciences Research
17. Part 4 Exercise – Performing Statistics for Biology Studies in Python