Saved in:
| Main Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Sebastopol, CA
O'Reilly Media, Inc.
[2017]
|
| Edition: | First edition. |
| Subjects: | |
| Links: | https://learning.oreilly.com/library/view/-/9781491952955/?ar |
| Summary: | "Statistical methods are a key 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 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"--Provided by publisher. |
| Item Description: | Includes bibliographical references and index. - Print version record |
| Physical Description: | 1 online resource (298 pages) illustrations |
| ISBN: | 9781491952931 1491952938 9781491952917 1491952911 9781491952955 1491952954 |
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| spelling | Bruce, Peter C. 1953- VerfasserIn aut Practical statistics for data scientists 50 essential concepts Peter Bruce and Andrew Bruce 50 essential concepts First edition. Sebastopol, CA O'Reilly Media, Inc. [2017] ©2017 1 online resource (298 pages) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index. - Print version record "Statistical methods are a key 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 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"--Provided by publisher. Mathematical analysis Statistical methods Quantitative research Statistical methods Big data Mathematics Analyse mathématique ; Méthodes statistiques Recherche quantitative ; Méthodes statistiques Données volumineuses ; Mathématiques REFERENCE ; Questions & Answers Statistics Statistics ; Data processing Data Mining Datenanalyse Statistik Bruce, Andrew 1958- VerfasserIn aut 9781491952962 Erscheint auch als Druck-Ausgabe 9781491952962 |
| spellingShingle | Bruce, Peter C. 1953- Bruce, Andrew 1958- Practical statistics for data scientists 50 essential concepts Mathematical analysis Statistical methods Quantitative research Statistical methods Big data Mathematics Analyse mathématique ; Méthodes statistiques Recherche quantitative ; Méthodes statistiques Données volumineuses ; Mathématiques REFERENCE ; Questions & Answers Statistics Statistics ; Data processing Data Mining Datenanalyse Statistik |
| title | Practical statistics for data scientists 50 essential concepts |
| title_alt | 50 essential concepts |
| title_auth | Practical statistics for data scientists 50 essential concepts |
| title_exact_search | Practical statistics for data scientists 50 essential concepts |
| title_full | Practical statistics for data scientists 50 essential concepts Peter Bruce and Andrew Bruce |
| title_fullStr | Practical statistics for data scientists 50 essential concepts Peter Bruce and Andrew Bruce |
| title_full_unstemmed | Practical statistics for data scientists 50 essential concepts Peter Bruce and Andrew Bruce |
| title_short | Practical statistics for data scientists |
| title_sort | practical statistics for data scientists 50 essential concepts |
| title_sub | 50 essential concepts |
| topic | Mathematical analysis Statistical methods Quantitative research Statistical methods Big data Mathematics Analyse mathématique ; Méthodes statistiques Recherche quantitative ; Méthodes statistiques Données volumineuses ; Mathématiques REFERENCE ; Questions & Answers Statistics Statistics ; Data processing Data Mining Datenanalyse Statistik |
| topic_facet | Mathematical analysis Statistical methods Quantitative research Statistical methods Big data Mathematics Analyse mathématique ; Méthodes statistiques Recherche quantitative ; Méthodes statistiques Données volumineuses ; Mathématiques REFERENCE ; Questions & Answers Statistics Statistics ; Data processing Data Mining Datenanalyse Statistik |
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