Practical Statistics for Data Scientists
50 Essential Concepts
(Paperback)

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"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

"

AuthorPeter Bruce
BindingPaperback
EAN9789352135653
EditionFirst
ISBN9352135652
Height59 mm
Length900 mm
Width700 mm
Weight100 g
LanguageEnglish
Language TypePublished
Number Of Pages320
Product GroupBook
Publication Date2017-06-15
PublisherShroff/O'Reilly
StudioShroff/O'Reilly
Sales Rank36270

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