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  1. OpenIntro Statistics
    Includes 1st, 2nd, 3rd, and 4th Editions
    OpenIntro, Christopher Barr, Mine Cetinkaya-Rundel, and David Diez

    A complete foundation for Statistics, also serving as a foundation for Data Science. Leanpub revenue supports OpenIntro (US-based nonprofit) so we can provide free desk copies to teachers interested in using OpenIntro Statistics in the classroom and expand the project to support free textbooks in other subjects. More resources: openintro.org.

  2. This book brings the fundamentals of R programming to you, using the same material developed as part of the industry-leading Johns Hopkins Data Science Specialization. The skills taught in this book will lay the foundation for you to begin your journey learning data science. Printed copies of this book are available through Lulu.

  3. The Art of Data Science
    A Guide for Anyone Who Works with Data
    Roger D. Peng and Elizabeth Matsui

    This book describes the process of analyzing data. The authors have extensive experience both managing data analysts and conducting their own data analyses, and this book is a distillation of their experience in a format that is applicable to both practitioners and managers in data science. Printed copies are available through Lulu.

  4. The book covers all the key skills needed for preparing, exploring, and analysing longitudinal data. To facilitate understanding and help readers learn these skills, it interweaves statistical modelling with computer code and visualizations. It does this using real-world data, code, and outputs that readers can replicate.

  5. Windows 11 Field Guide
    24H2 Edition
    Rafael Rivera and Paul Thurrott

    The Windows 11 Field Guide is a full-length e-book about the latest version of Microsoft Windows, aimed at those users who will upgrade from Windows 10 or acquire Windows 11 with a new PC.

  6. This book teaches you to use R to effectively visualize and explore complex datasets. Exploratory data analysis is a key part of the data science process because it allows you to sharpen your question and refine your modeling strategies. This book is based on the industry-leading Johns Hopkins Data Science Specialization.

  7. Data Analysis for the Life Sciences
    Rafael A Irizarry and Michael I Love

    Data analysis is now part of practically every research project in the life sciences. In this book we use data and computer code to teach the necessary statistical concepts and programming skills to become a data analyst. Instead of showing theory first and then applying it to toy examples, we start with actual applications and describe the theory as it becomes necessary to solve specific challenges. The book includes links to computer code that readers can use to follow along as they program.

  8. Statistical inference for data science
    A companion to the Coursera Statistical Inference Course
    Brian Caffo

    This book gives a brief, but rigorous, treatment of statistical inference intended for practicing Data Scientists.

  9. Finally a free, open source book designed to teach Unix to anybody! Unix is over 40 years old yet it's still used to power your phone, the internet, and the latest scientific research. If you know how to use a mouse and keyboard then this book can provide you with the foundation you need to start coding - no previous experience expected!

  10. Thinking with Types
    Type-Level Programming in Haskell
    Sandy Maguire

    This book aims to be the comprehensive manual for type-level programming. It's about getting you from here to there---from a competent Haskell programmer to one who convinces the compiler to do their work for them.

  11. Methods in Biostatistics with R
    A Rigorous and Practical Treatment of Biostatistics Foundations using R
    Brian Caffo, John Muschelli, and Ciprian Crainiceanu

    The book provides a modern look at introductory Biostatistical concepts and the associated computational tools using the latest developments in computation and visualization in the R language environment. The book includes practical data analysis based on datasets that can be downloaded here: https://github.com/muschellij2/biostatmethods.

  12. Methods in Biostatistics with R
    A Rigorous and Practical Treatment of Biostatistics Foundations using R
    Brian Caffo, John Muschelli, and Ciprian Crainiceanu

    The book provides a modern look at introductory Biostatistical concepts and the associated computational tools using the latest developments in computation and visualization in the R language environment. The book includes practical data analysis based on datasets that can be downloaded here: https://github.com/muschellij2/biostatmethods.

  13. Dataflow and Reactive Programming Systems
    A Practical Guide to Developing Dataflow and Reactive Programming Systems
    Matt Carkci

    Explore the theory and application of Reactive Programming with downloadable code of a complete dataflow system.

  14. Updated, useful reference for those involved in plant design, covering all aspects of plant layout in broad detail

  15. Twilight Strategy
    A comprehensive strategy guide to Twilight Struggle
    theory
    No Description Available