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Author: Hadley Wickham Publisher: "O'Reilly Media, Inc." ISBN: 1491910364 Category : Computers Languages : en Pages : 521
Book Description
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Author: Hadley Wickham Publisher: "O'Reilly Media, Inc." ISBN: 1491910364 Category : Computers Languages : en Pages : 521
Book Description
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Author: W.F. McComas Publisher: Springer Science & Business Media ISBN: 0306472155 Category : Science Languages : en Pages : 337
Book Description
This is the first book to blend a justification for the inclusion of the history and philosophy of science in science teaching with methods by which this vital content can be shared with a variety of learners. It contains a complete analysis of the variety of tools developed thus far to assess learning in this domain. This book is relevant to science methods instructors, science education graduate students and science teachers.
Author: R. J. Shephard Publisher: John Wiley & Sons ISBN: 0470694823 Category : Medical Languages : en Pages : 1008
Book Description
Endurance in Sport is a comprehensive and authoritative work on all aspects of this major component of sports science. The book also embraces medical and sport-specific issues of particular relevance to those interested in endurance performance. The scientific basis and mechanisms of endurance - physiological, psychological, genetic and environmental - are all considered in depth. Measurement of endurance is extensively reviewed as is preparation and training for physical activities requiring endurance.
Author: Alberto Cañas Publisher: Springer ISBN: 331945501X Category : Education Languages : en Pages : 342
Book Description
This book constitutes the refereed proceedings of the 7th International Conference on Concept Mapping, CMC 2016, held in Tallinn, Estonia, in September 2016. The 25 revised full papers presented were carefully reviewed and selected from 135 submissions. The papers address issues such as facilitation of learning; eliciting, capturing, archiving, and using “expert” knowledge; planning instruction; assessment of “deep” understandings; research planning; collaborative knowledge modeling; creation of “knowledge portfolios”; curriculum design; eLearning, and administrative and strategic planning and monitoring.
Author: Hadley Wickham
Author: Hadley Wickham
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Author: W.F. McComas
Author: R. J. Shephard
Author: E. A. Newsholme
Author: Santiago Ramón y Cajal
Author: Alberto Cañas