Biostatistics with Python : Apply Python for Biostatistics with Hands-On Biomedical and Biotechnology Projects

Von:

Medin, Darko [VerfasserIn]

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Verlag: Birmingham : Packt Publishing, Limited, 2024Copyright-Datum: ©2024Auflage: 1st edBeschreibung: 1 online resource (374 pages)ISBN:

9781837631834

Andere physische Formen: 9781837630967 | Erscheint auch als: 9781837630967 Druck-AusgabeLocal classification: Lokale Notation: inf 3.25Online-Ressourcen:

Zugang im Netz des KIT

Zusammenfassung: Cover -- Title Page -- Copyright and Credits -- Contributors -- Table of Contents -- Preface -- Part 1: Introduction to Biostatistics and Getting Started with Python -- Chapter 1: Introduction to Biostatistics -- Why do we need biostatistics in life sciences? -- Biostatistics in human life sciences -- Biostatistics for biology -- Biostatistics in epidemiology and public health -- Biostatistics in medicine and biomedical research -- Biostatics in zoology and botany -- Biostatistics in ecology -- Biostatistics in pharmaceutical research and design -- Biostatistics in bioinformatics and genetics -- Formulating the scientific questions in life sciences and research -- How to formulate scientific questions related to diabetes -- How to formulate scientific questions related to cardiovascular disease -- How to formulate scientific questions in biology -- How computation can help answer different questions in life sciences -- Biostatistics and Python -- Answers for Chapter 1 -- Summary -- Chapter 2: Getting Started with Python for Biostatistics -- Launching Jupyter Notebook and navigating its interfaces -- Using Jupyter Notebook to write Python code and a brief introduction to programming -- Launching the Spyder IDE and using its interfaces -- Selecting and running code in Spyder -- Installing packages in Python -- Loading data in Python - how to load the Iris dataset -- Exploring the Iris dataset -- Exploring the data and the associated variable names -- Summary -- Chapter 3: Exercise 1 - Cleaning and Describing Data Using Python -- Technical requirements -- Data types -- Terms and metrics in EDA -- Loading the Exercise 1 data using Python -- Cleaning missing values and invalid data -- Finding NaN values and invalid data types and addressing them -- Identifying the wrong species name -- Performing descriptive statistics analysis in Python.PPN: PPN: 1909894141Package identifier: Produktsigel: ZDB-30-PQE

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