Biostatistics with Python: Apply Python for biostatistics with hands-on biomedical and biotechnology projects by Darko Medin
English | November 29, 2024 | ISBN: 1837630968 | 374 pages | PDF | 10 Mb
Learn how to utilize biostatistics with Python for excelling in research and biomedical professions with practical exemplar projects
Key FeaturesBridge the gap between biostatistics and life sciences with PythonWork with practical exercises for real-world data analysis in biology and medicineAccess a portfolio of exemplar projects in the domains of biomedicine, biotechnology, and biologyPurchase of the print or Kindle book includes a free PDF eBookBook Description
This book leverages the author's decade-long experience in biostatistics and data science to simplify the practical use of biostatistics with Python. The chapters show you how to clean and describe your data effectively, setting a solid foundation for accurate analysis and proficiency in biostatistical inference to help you draw meaningful conclusions from your data through hypothesis testing and effect size analysis.
The book walks you through predictive modeling to harness the power of Python to create robust predictive analytics that can drive your research and professional projects forward. You'll explore clinical biostatistics, learn how to design studies, conduct survival analysis, and synthesize evidence from multiple studies with meta-analysis - skills that are crucial for making informed decisions based on comprehensive data reviews. The concluding chapters will enhance your ability to analyze biological variables, enabling you to perform detailed and accurate data analysis for biological research. This book's unique blend of biostatistics and Python helps you find practical solutions that make complex concepts easy to grasp and apply.
By the end of this biostatistics book, you'll have moved from theoretical knowledge to practical experience, allowing you to perform biostatistical analysis confidently and accurately.
What you will learnGet to grips with the basics of biostatistics and Python programmingClean and describe data using PythonFamiliarize yourself with hypothesis testing and effect size analysisExplore predictive modeling in biostatisticsUnderstand clinical study design and survival analysisGain a clear understanding of the meta-analysis of clinical research dataAnalyze biological variables with PythonDiscover practical data analysis for biological researchWho this book is for
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.
Table of ContentsIntroduction to BiostatisticsGetting Started with Python for BiostatisticsExercise 1 - Cleaning and Describing Data Using PythonPart 1 Exemplar Project - Load, Clean, and Describe Diabetes Data in PythonIntroduction to Python for BiostatisticsBiostatistical Inference Using Hypothesis Tests and Effect SizesPredictive Biostatistics Using PythonPart 2 Exercise - T-Test, ANOVA, and Linear and Logistic RegressionBiostatistical Inference and Predictive Analytics Using Cardiovascular Study DataClinical Study DesignSurvival Analysis in Biomedical ResearchMeta-Analysis - Synthesizing Evidence from Multiple StudiesSurvival Predictive Analysis and Meta-Analysis PracticePart 3 Exemplar Project - Meta-Analysis of Survival Data in Clinical ResearchUnderstanding Biological Variables(N.B. Please use the Read Sample option to see further chapters)
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Links are Interchangeable - Single Extraction
escribes the basic and applied aspects of bioreactor in food processingGathers information on bioreactors that is scattered in different journals and monographs as reviews and research articlesCovers various types of bioreactors including stirred tank, airlift, photo-bioreactor, and disposable bioreactorsGives a broad overview of what exactly is involved in designing a bioreactor and optimizing its performance and finally their applications in the food processing industryThe broad interdisciplinary approach of this book will certainly make your reading very interesting, and we hope that it can contribute to knowledge and instigate creative thinking to overcome the challenges that food bioprocessing brings us.
