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Practical Statistics for Data Scientists: 50 Essential Concepts

Amazon.com Price:  $20.76 (as of 05/05/2019 15:04 PST- Details)

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Description

Statistical methods are a key a part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science point of view. This practical guide explains tips on how to apply more than a few statistical the best way to data science, tells you tips on how to keep away from their misuse, and will give you advice on what’s important and what is not.

Many data science resources incorporate statistical methods but lack a deeper statistical point of view. If you happen to’re acquainted with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.

With this book, you’ll learn:

  • Why exploratory data analysis is a key preliminary step in data science
  • How random sampling can reduce bias and yield a higher quality dataset, even with big data
  • How the principles of experimental design yield definitive answers to questions
  • How to use regression to estimate outcomes and detect anomalies
  • Key classification techniques for predicting which categories a record belongs to
  • Statistical machine learning methods that “learn” from data
  • Unsupervised learning methods for extracting meaning from unlabeled data

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