Practical Statistics for Data Scientists: 50 Essential Concepts

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About this Book Data science is a fusion of multiple disciplines, including statistics, computer science, information technology and domain specific fields. As a result, a several different terms could be used to reference a given concept. Key terms and their synonyms will be highlighted throughout the book in a sidebar within the text. This book is aimed at the data scientist with some familiarity with the R programming language, and with some prior (perhaps spotty or ephemeral) exposure to statistics. Both of us came to the world of data science from the world of statistics, and have some appreciation of the contribution that statistics can make to the art of data science. At the same time, we are well aware of the limitations of traditional statistics instruction: statistics as a disciple is a century and a half old, and most statistics textbooks and courses are laden with the momentum and inertia worthy of an ocean liner. Two goals underlie this book: To lay out, in digestible, navigable and easily referenced form, key concepts from statistics that are relevant to data science. To explain which concepts are important and useful from a data science perspective, which are less so, and why. Read more

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🗸 Author(s):
🗸 Title: Practical Statistics for Data Scientists: 50 Essential Concepts
🗸 Rating : 4.5 from 5 stars (396 reviews)
🗸 Languange: English
🗸 Format ebook: PDF, EPUB, Kindle, Audio, HTML and MOBI
🗸 Supported Devices: Android, iOS, PC and Amazon Kindle


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