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Doing Data Science in R

An Introduction for Social Scientists
BuchGebunden
640 Seiten
Englisch
SAGE Publishing Ltderschienen am31.03.2021
This approachable introduction to doing data science in R provides step-by-step advice on using data science tools and statistical methods to carry out data analysis. Introducing the fundamentals of data science and R before moving into more advanced topics like Multilevel Models and Probabilistic Modelling with Stan, it builds knowledge and skills gradually.mehr
Verfügbare Formate
BuchGebunden
EUR242,00
BuchKartoniert, Paperback
EUR115,30
E-BookEPUBDRM AdobeE-Book
EUR61,49
E-BookEPUBDRM AdobeE-Book
EUR61,49

Produkt

KlappentextThis approachable introduction to doing data science in R provides step-by-step advice on using data science tools and statistical methods to carry out data analysis. Introducing the fundamentals of data science and R before moving into more advanced topics like Multilevel Models and Probabilistic Modelling with Stan, it builds knowledge and skills gradually.
Details
ISBN/GTIN978-1-5264-8676-9
ProduktartBuch
EinbandartGebunden
Erscheinungsjahr2021
Erscheinungsdatum31.03.2021
Seiten640 Seiten
SpracheEnglisch
MasseBreite 175 mm, Höhe 250 mm, Dicke 39 mm
Gewicht1269 g
Artikel-Nr.56904492

Inhalt/Kritik

Inhaltsverzeichnis
Chapter 1: Data Analysis And Data ScienceChapter 2: Introduction To RChapter 3: Data WranglingChapter 4: Data VisualizationChapter 5: Exploratory Data AnalysisChapter 6: Programming In RChapter 7: Reproducible Data AnalysisChapter 8: Statistical Models and Statistical InferenceChapter 9: Normal Linear ModelsChapter 10: Logistic RegressionChapter 11: Generalized Linear Models for Count DataChapter 12: Multilevel ModelsChapter 13: Nonlinear RegressionChapter 14: Structural Equation ModellingChapter 15: High Performance Computing with RChapter 16: Interactive Web Apps with ShinyChapter 17: Probabilistic Modelling with Stanmehr

Autor

Mark Andrews (PhD) is Senior Lecturer in the Department of Psychology in Nottingham Trent University. There, he specializes in teaching statistics and data science at all levels from undergraduate to PhD level. Currently, he is the Chair of the British Psychological Society's Mathematics, Statistics, and Computing section. Between 2015 and 2018, Dr Andrews was funded by the UK's Economic and Social Research Council (ESRC) to provide advanced training workshop on Bayesian data analysis to UK based researchers at PhD level and beyond in the social sciences. Dr Andrews's background is in computational cognitive science, particularly focused Bayesian models of human cognition. He has a PhD in Cognitive Science from Cornell University, and was a postdoctoral researcher in the Gatsby Computational Neuroscience Unit in UCL and also in the Department of Psychology in UCL.