The Resource Practical statistics for data scientists : 50 essential concepts, Peter Bruce and Andrew Bruce
Practical statistics for data scientists : 50 essential concepts, Peter Bruce and Andrew Bruce
Resource Information
The item Practical statistics for data scientists : 50 essential concepts, Peter Bruce and Andrew Bruce represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.This item is available to borrow from 2 library branches.
Resource Information
The item Practical statistics for data scientists : 50 essential concepts, Peter Bruce and Andrew Bruce represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.
This item is available to borrow from 2 library branches.
- 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
- Language
- eng
- Edition
- First edition.
- Extent
- 1 online resource (298 pages)
- Contents
-
- Exploratory data analysis
- Data and sampling distributions
- Statistical experiments and significance testing
- Regression and prediction
- Classification
- Statistical machine learning
- Unsupervised learning
- Isbn
- 9781491952917
- Label
- Practical statistics for data scientists : 50 essential concepts
- Title
- Practical statistics for data scientists
- Title remainder
- 50 essential concepts
- Statement of responsibility
- Peter Bruce and Andrew Bruce
- Title variation
-
- 50 essential concepts
- Fifty essential concepts
- Language
- eng
- 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
- Cataloging source
- N$T
- http://library.link/vocab/creatorDate
- 1953-
- http://library.link/vocab/creatorName
- Bruce, Peter C.
- Dewey number
- 001.4/226
- Illustrations
- illustrations
- Index
- index present
- LC call number
- QA276.4
- Literary form
- non fiction
- Nature of contents
-
- dictionaries
- bibliography
- http://library.link/vocab/relatedWorkOrContributorDate
- 1958-
- http://library.link/vocab/relatedWorkOrContributorName
- Bruce, Andrew
- http://library.link/vocab/subjectName
-
- Mathematical analysis
- Quantitative research
- Big data
- REFERENCE
- Statistics
- Statistics
- Data Mining
- Datenanalyse
- Statistik
- Label
- Practical statistics for data scientists : 50 essential concepts, Peter Bruce and Andrew Bruce
- Antecedent source
- unknown
- Bibliography note
- Includes bibliographical references and index
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- multicolored
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Exploratory data analysis -- Data and sampling distributions -- Statistical experiments and significance testing -- Regression and prediction -- Classification -- Statistical machine learning -- Unsupervised learning
- Control code
- 987251007
- Dimensions
- unknown
- Edition
- First edition.
- Extent
- 1 online resource (298 pages)
- File format
- unknown
- Form of item
- online
- Isbn
- 9781491952917
- Level of compression
- unknown
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- illustrations
- http://library.link/vocab/ext/overdrive/overdriveId
- 96961a23-c486-4329-885d-86cc1f77a2ff
- Quality assurance targets
- not applicable
- Reformatting quality
- unknown
- Sound
- unknown sound
- Specific material designation
- remote
- System control number
- (OCoLC)987251007
- Label
- Practical statistics for data scientists : 50 essential concepts, Peter Bruce and Andrew Bruce
- Antecedent source
- unknown
- Bibliography note
- Includes bibliographical references and index
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- multicolored
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Exploratory data analysis -- Data and sampling distributions -- Statistical experiments and significance testing -- Regression and prediction -- Classification -- Statistical machine learning -- Unsupervised learning
- Control code
- 987251007
- Dimensions
- unknown
- Edition
- First edition.
- Extent
- 1 online resource (298 pages)
- File format
- unknown
- Form of item
- online
- Isbn
- 9781491952917
- Level of compression
- unknown
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- illustrations
- http://library.link/vocab/ext/overdrive/overdriveId
- 96961a23-c486-4329-885d-86cc1f77a2ff
- Quality assurance targets
- not applicable
- Reformatting quality
- unknown
- Sound
- unknown sound
- Specific material designation
- remote
- System control number
- (OCoLC)987251007
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.library.missouri.edu/portal/Practical-statistics-for-data-scientists--50/7rhtFhj-K2w/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.missouri.edu/portal/Practical-statistics-for-data-scientists--50/7rhtFhj-K2w/">Practical statistics for data scientists : 50 essential concepts, Peter Bruce and Andrew Bruce</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.missouri.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.missouri.edu/">University of Missouri Libraries</a></span></span></span></span></div>
