Practical Statistics for Data Scientists: 50 Essential Concepts 1st Edition [NulledPremium]

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Book details
Format: pdf
File Size: 13 MB
Print Length: 318 pages
Simultaneous Device Usage: Unlimited
Publisher: O’Reilly Media; 1 edition (10 May 2017)
Sold by: Amazon Asia-Pacific Holdings Private Limited
Language: English
ASIN: B071NVDFD6

Statistical methods are a key part 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 perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not.

Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar 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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