Statistics slam dunk
Learn statistics by analyzing professional basketball data! In this action-packed book, you'll build your skills in exploratory data analysis by digging into the fascinating world of NBA games and player stats using the R language. Statistics Slam Dunk is an engaging how-to guide for statistica...
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Elektronisch Video |
Sprache: | English |
Veröffentlicht: |
[Place of publication not identified]
Manning Publications
2024
|
Ausgabe: | Video edition. |
Schlagworte: | |
Online-Zugang: | lizenzpflichtig |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
MARC
LEADER | 00000ngm a22000002 4500 | ||
---|---|---|---|
001 | ZDB-30-ORH-102564884 | ||
003 | DE-627-1 | ||
005 | 20240429114546.0 | ||
006 | m o | | | ||
007 | cr uuu---uuuuu | ||
008 | 240429s2024 xx ||| |o o ||eng c | ||
035 | |a (DE-627-1)102564884 | ||
035 | |a (DE-599)KEP102564884 | ||
035 | |a (ORHE)9781633438682VE | ||
035 | |a (DE-627-1)102564884 | ||
040 | |a DE-627 |b ger |c DE-627 |e rda | ||
041 | |a eng | ||
082 | 0 | |a 796.323 |2 23/eng/20240416 | |
100 | 1 | |a Sutton, Gary |e VerfasserIn |4 aut | |
245 | 1 | 0 | |a Statistics slam dunk |c Gary Sutton |
250 | |a Video edition. | ||
264 | 1 | |a [Place of publication not identified] |b Manning Publications |c 2024 | |
300 | |a 1 online resource (1 video file (17 hr., 50 min.)) |b sound, color. | ||
336 | |a zweidimensionales bewegtes Bild |b tdi |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
500 | |a Online resource; title from title details screen (O'Reilly, viewed April 16, 2024) | ||
520 | |a Learn statistics by analyzing professional basketball data! In this action-packed book, you'll build your skills in exploratory data analysis by digging into the fascinating world of NBA games and player stats using the R language. Statistics Slam Dunk is an engaging how-to guide for statistical analysis with R. Each chapter contains an end-to-end data science or statistics project delving into NBA data and revealing real-world sporting insights. Written by a former basketball player turned business intelligence and analytics leader, you'll get practical experience tidying, wrangling, exploring, testing, modeling, and otherwise analyzing data with the best and latest R packages and functions. In Statistics Slam Dunk you'll develop a toolbox of R programming skills including: Reading and writing data Installing and loading packages Transforming, tidying, and wrangling data Applying best-in-class exploratory data analysis techniques Creating compelling visualizations Developing supervised and unsupervised machine learning algorithms Executing hypothesis tests, including t-tests and chi-square tests for independence Computing expected values, Gini coefficients, z-scores, and other measures If you're looking to switch to R from another language, or trade base R for tidyverse functions, this book is the perfect training coach. Much more than a beginner's guide, it teaches statistics and data science methods that have tons of use cases. And just like in the real world, you'll get no clean pre-packaged data sets in Statistics Slam Dunk. You'll take on the challenge of wrangling messy data to drill on the skills that will make you the star player on any data team. About the Technology Statistics Slam Dunk is a data science manual with a difference. Each chapter is a complete, self-contained statistics or data science project for you to work through--from importing data, to wrangling it, testing it, visualizing it, and modeling it. Throughout the book, you'll work exclusively with NBA data sets and the R language, applying best-in-class statistics techniques to reveal fun and fascinating truths about the NBA. About the Book Is losing basketball games on purpose a rational strategy? Which hustle statistics have an impact on wins and losses? Does spending more on player salaries translate into a winning record? You'll answer all these questions and more. Plus, R's visualization capabilities shine through in the book's 300 plots and charts, including Pareto charts, Sankey diagrams, Cleveland dot plots, and dendrograms. What's Inside Transforming, tidying, and wrangling data Applying best-in-class exploratory data analysis techniques Developing supervised and unsupervised machine learning algorithms Executing hypothesis tests and effect size tests About the Reader For readers who know basic statistics. No advanced knowledge of R--or basketball--required. About the Author Gary Sutton is a former basketball player who has built and led high-performing business intelligence and analytics organizations across multiple verticals. Quotes In this journey of exploration, every computer scientist will find a valuable ally in understanding the language of data. - Kim Lok©ıy, areo Transcends other R titles by revealing the hidden narratives that lie within the numbers. - Christian Sutton, Shell International Exploration and Production Seamlessly blending theory and practical insights, this book serves as an indispensable guide for those venturing into the field of data analytics. - Juan Delgado, Sodexo BRS. | ||
610 | 1 | 0 | |a National Basketball Association |x Statistical methods |x Computer programs |
650 | 0 | |a Basketball |x Statistical methods |x Computer programs | |
650 | 0 | |a R (Computer program language) | |
650 | 0 | |a Statistics |x Computer programs | |
650 | 4 | |a Basket-ball ; Méthodes statistiques ; Logiciels | |
650 | 4 | |a R (Langage de programmation) | |
650 | 4 | |a Statistique ; Logiciels | |
650 | 4 | |a Instructional films | |
650 | 4 | |a Nonfiction films | |
650 | 4 | |a Internet videos | |
650 | 4 | |a Films de formation | |
650 | 4 | |a Films autres que de fiction | |
650 | 4 | |a Vidéos sur Internet | |
710 | 2 | |a Manning (Firm), |e Verlag |4 pbl | |
856 | 4 | 0 | |l TUM01 |p ZDB-30-ORH |q TUM_PDA_ORH |u https://learning.oreilly.com/library/view/-/9781633438682VE/?ar |m X:ORHE |x Aggregator |z lizenzpflichtig |3 Volltext |
912 | |a ZDB-30-ORH | ||
935 | |c vide | ||
951 | |a BO | ||
912 | |a ZDB-30-ORH | ||
049 | |a DE-91 |
Datensatz im Suchindex
DE-BY-TUM_katkey | ZDB-30-ORH-102564884 |
---|---|
_version_ | 1818767370191110144 |
adam_text | |
any_adam_object | |
author | Sutton, Gary |
author_facet | Sutton, Gary |
author_role | aut |
author_sort | Sutton, Gary |
author_variant | g s gs |
building | Verbundindex |
bvnumber | localTUM |
collection | ZDB-30-ORH |
ctrlnum | (DE-627-1)102564884 (DE-599)KEP102564884 (ORHE)9781633438682VE |
dewey-full | 796.323 |
dewey-hundreds | 700 - The arts |
dewey-ones | 796 - Athletic and outdoor sports and games |
dewey-raw | 796.323 |
dewey-search | 796.323 |
dewey-sort | 3796.323 |
dewey-tens | 790 - Recreational and performing arts |
discipline | Sport |
edition | Video edition. |
format | Electronic Video |
fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>05419ngm a22005172 4500</leader><controlfield tag="001">ZDB-30-ORH-102564884</controlfield><controlfield tag="003">DE-627-1</controlfield><controlfield tag="005">20240429114546.0</controlfield><controlfield tag="006">m o | | </controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240429s2024 xx ||| |o o ||eng c</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)102564884</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KEP102564884</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ORHE)9781633438682VE</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)102564884</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">796.323</subfield><subfield code="2">23/eng/20240416</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Sutton, Gary</subfield><subfield code="e">VerfasserIn</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Statistics slam dunk</subfield><subfield code="c">Gary Sutton</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">Video edition.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">[Place of publication not identified]</subfield><subfield code="b">Manning Publications</subfield><subfield code="c">2024</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (1 video file (17 hr., 50 min.))</subfield><subfield code="b">sound, color.</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">zweidimensionales bewegtes Bild</subfield><subfield code="b">tdi</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Online resource; title from title details screen (O'Reilly, viewed April 16, 2024)</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Learn statistics by analyzing professional basketball data! In this action-packed book, you'll build your skills in exploratory data analysis by digging into the fascinating world of NBA games and player stats using the R language. Statistics Slam Dunk is an engaging how-to guide for statistical analysis with R. Each chapter contains an end-to-end data science or statistics project delving into NBA data and revealing real-world sporting insights. Written by a former basketball player turned business intelligence and analytics leader, you'll get practical experience tidying, wrangling, exploring, testing, modeling, and otherwise analyzing data with the best and latest R packages and functions. In Statistics Slam Dunk you'll develop a toolbox of R programming skills including: Reading and writing data Installing and loading packages Transforming, tidying, and wrangling data Applying best-in-class exploratory data analysis techniques Creating compelling visualizations Developing supervised and unsupervised machine learning algorithms Executing hypothesis tests, including t-tests and chi-square tests for independence Computing expected values, Gini coefficients, z-scores, and other measures If you're looking to switch to R from another language, or trade base R for tidyverse functions, this book is the perfect training coach. Much more than a beginner's guide, it teaches statistics and data science methods that have tons of use cases. And just like in the real world, you'll get no clean pre-packaged data sets in Statistics Slam Dunk. You'll take on the challenge of wrangling messy data to drill on the skills that will make you the star player on any data team. About the Technology Statistics Slam Dunk is a data science manual with a difference. Each chapter is a complete, self-contained statistics or data science project for you to work through--from importing data, to wrangling it, testing it, visualizing it, and modeling it. Throughout the book, you'll work exclusively with NBA data sets and the R language, applying best-in-class statistics techniques to reveal fun and fascinating truths about the NBA. About the Book Is losing basketball games on purpose a rational strategy? Which hustle statistics have an impact on wins and losses? Does spending more on player salaries translate into a winning record? You'll answer all these questions and more. Plus, R's visualization capabilities shine through in the book's 300 plots and charts, including Pareto charts, Sankey diagrams, Cleveland dot plots, and dendrograms. What's Inside Transforming, tidying, and wrangling data Applying best-in-class exploratory data analysis techniques Developing supervised and unsupervised machine learning algorithms Executing hypothesis tests and effect size tests About the Reader For readers who know basic statistics. No advanced knowledge of R--or basketball--required. About the Author Gary Sutton is a former basketball player who has built and led high-performing business intelligence and analytics organizations across multiple verticals. Quotes In this journey of exploration, every computer scientist will find a valuable ally in understanding the language of data. - Kim Lok©ıy, areo Transcends other R titles by revealing the hidden narratives that lie within the numbers. - Christian Sutton, Shell International Exploration and Production Seamlessly blending theory and practical insights, this book serves as an indispensable guide for those venturing into the field of data analytics. - Juan Delgado, Sodexo BRS.</subfield></datafield><datafield tag="610" ind1="1" ind2="0"><subfield code="a">National Basketball Association</subfield><subfield code="x">Statistical methods</subfield><subfield code="x">Computer programs</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Basketball</subfield><subfield code="x">Statistical methods</subfield><subfield code="x">Computer programs</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">R (Computer program language)</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Statistics</subfield><subfield code="x">Computer programs</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Basket-ball ; Méthodes statistiques ; Logiciels</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">R (Langage de programmation)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistique ; Logiciels</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Instructional films</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Nonfiction films</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Internet videos</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Films de formation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Films autres que de fiction</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Vidéos sur Internet</subfield></datafield><datafield tag="710" ind1="2" ind2=" "><subfield code="a">Manning (Firm),</subfield><subfield code="e">Verlag</subfield><subfield code="4">pbl</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="l">TUM01</subfield><subfield code="p">ZDB-30-ORH</subfield><subfield code="q">TUM_PDA_ORH</subfield><subfield code="u">https://learning.oreilly.com/library/view/-/9781633438682VE/?ar</subfield><subfield code="m">X:ORHE</subfield><subfield code="x">Aggregator</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="935" ind1=" " ind2=" "><subfield code="c">vide</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">BO</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-91</subfield></datafield></record></collection> |
id | ZDB-30-ORH-102564884 |
illustrated | Not Illustrated |
indexdate | 2024-12-18T08:48:48Z |
institution | BVB |
language | English |
open_access_boolean | |
owner | DE-91 DE-BY-TUM |
owner_facet | DE-91 DE-BY-TUM |
physical | 1 online resource (1 video file (17 hr., 50 min.)) sound, color. |
psigel | ZDB-30-ORH |
publishDate | 2024 |
publishDateSearch | 2024 |
publishDateSort | 2024 |
publisher | Manning Publications |
record_format | marc |
spelling | Sutton, Gary VerfasserIn aut Statistics slam dunk Gary Sutton Video edition. [Place of publication not identified] Manning Publications 2024 1 online resource (1 video file (17 hr., 50 min.)) sound, color. zweidimensionales bewegtes Bild tdi rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Online resource; title from title details screen (O'Reilly, viewed April 16, 2024) Learn statistics by analyzing professional basketball data! In this action-packed book, you'll build your skills in exploratory data analysis by digging into the fascinating world of NBA games and player stats using the R language. Statistics Slam Dunk is an engaging how-to guide for statistical analysis with R. Each chapter contains an end-to-end data science or statistics project delving into NBA data and revealing real-world sporting insights. Written by a former basketball player turned business intelligence and analytics leader, you'll get practical experience tidying, wrangling, exploring, testing, modeling, and otherwise analyzing data with the best and latest R packages and functions. In Statistics Slam Dunk you'll develop a toolbox of R programming skills including: Reading and writing data Installing and loading packages Transforming, tidying, and wrangling data Applying best-in-class exploratory data analysis techniques Creating compelling visualizations Developing supervised and unsupervised machine learning algorithms Executing hypothesis tests, including t-tests and chi-square tests for independence Computing expected values, Gini coefficients, z-scores, and other measures If you're looking to switch to R from another language, or trade base R for tidyverse functions, this book is the perfect training coach. Much more than a beginner's guide, it teaches statistics and data science methods that have tons of use cases. And just like in the real world, you'll get no clean pre-packaged data sets in Statistics Slam Dunk. You'll take on the challenge of wrangling messy data to drill on the skills that will make you the star player on any data team. About the Technology Statistics Slam Dunk is a data science manual with a difference. Each chapter is a complete, self-contained statistics or data science project for you to work through--from importing data, to wrangling it, testing it, visualizing it, and modeling it. Throughout the book, you'll work exclusively with NBA data sets and the R language, applying best-in-class statistics techniques to reveal fun and fascinating truths about the NBA. About the Book Is losing basketball games on purpose a rational strategy? Which hustle statistics have an impact on wins and losses? Does spending more on player salaries translate into a winning record? You'll answer all these questions and more. Plus, R's visualization capabilities shine through in the book's 300 plots and charts, including Pareto charts, Sankey diagrams, Cleveland dot plots, and dendrograms. What's Inside Transforming, tidying, and wrangling data Applying best-in-class exploratory data analysis techniques Developing supervised and unsupervised machine learning algorithms Executing hypothesis tests and effect size tests About the Reader For readers who know basic statistics. No advanced knowledge of R--or basketball--required. About the Author Gary Sutton is a former basketball player who has built and led high-performing business intelligence and analytics organizations across multiple verticals. Quotes In this journey of exploration, every computer scientist will find a valuable ally in understanding the language of data. - Kim Lok©ıy, areo Transcends other R titles by revealing the hidden narratives that lie within the numbers. - Christian Sutton, Shell International Exploration and Production Seamlessly blending theory and practical insights, this book serves as an indispensable guide for those venturing into the field of data analytics. - Juan Delgado, Sodexo BRS. National Basketball Association Statistical methods Computer programs Basketball Statistical methods Computer programs R (Computer program language) Statistics Computer programs Basket-ball ; Méthodes statistiques ; Logiciels R (Langage de programmation) Statistique ; Logiciels Instructional films Nonfiction films Internet videos Films de formation Films autres que de fiction Vidéos sur Internet Manning (Firm), Verlag pbl TUM01 ZDB-30-ORH TUM_PDA_ORH https://learning.oreilly.com/library/view/-/9781633438682VE/?ar X:ORHE Aggregator lizenzpflichtig Volltext |
spellingShingle | Sutton, Gary Statistics slam dunk National Basketball Association Statistical methods Computer programs Basketball Statistical methods Computer programs R (Computer program language) Statistics Computer programs Basket-ball ; Méthodes statistiques ; Logiciels R (Langage de programmation) Statistique ; Logiciels Instructional films Nonfiction films Internet videos Films de formation Films autres que de fiction Vidéos sur Internet |
title | Statistics slam dunk |
title_auth | Statistics slam dunk |
title_exact_search | Statistics slam dunk |
title_full | Statistics slam dunk Gary Sutton |
title_fullStr | Statistics slam dunk Gary Sutton |
title_full_unstemmed | Statistics slam dunk Gary Sutton |
title_short | Statistics slam dunk |
title_sort | statistics slam dunk |
topic | National Basketball Association Statistical methods Computer programs Basketball Statistical methods Computer programs R (Computer program language) Statistics Computer programs Basket-ball ; Méthodes statistiques ; Logiciels R (Langage de programmation) Statistique ; Logiciels Instructional films Nonfiction films Internet videos Films de formation Films autres que de fiction Vidéos sur Internet |
topic_facet | National Basketball Association Statistical methods Computer programs Basketball Statistical methods Computer programs R (Computer program language) Statistics Computer programs Basket-ball ; Méthodes statistiques ; Logiciels R (Langage de programmation) Statistique ; Logiciels Instructional films Nonfiction films Internet videos Films de formation Films autres que de fiction Vidéos sur Internet |
url | https://learning.oreilly.com/library/view/-/9781633438682VE/?ar |
work_keys_str_mv | AT suttongary statisticsslamdunk AT manningfirm statisticsslamdunk |