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Mark Andrews - Doing Data Science in R: An Introduction for Social Scientists

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Mark Andrews Doing Data Science in R: An Introduction for Social Scientists
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This approachable introduction to doing data science in R provides step-by-step advice on using the 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.
This book:

  • Focuses on providing practical guidance for all aspects, helping readers get to grips with the tools, software, and statistical methods needed to provide the right type and level of analysis their data requires
  • Explores the foundations of data science and breaks down the processes involved, focusing on the link between data science and practical social science skills
  • Introduces R at the outset and includes extensive worked examples and R code every step of the way, ensuring students see the value of R and its connection to methods while providing hands-on practice in the software
  • Provides examples and datasets from different disciplines and locations demonstrate the widespread relevance, possible applications, and impact of data science across the social sciences

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Doing Data Science in R
Doing Data Science in R An Introduction for Social Scientists Mark Andrews - photo 1
Doing Data Science in R

An Introduction for Social Scientists

  • Mark Andrews
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  • Los Angeles
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SAGE Publications Ltd

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Mark Andrews 2021

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act, 1988, this publication may be reproduced, stored or transmitted in any form, or by any means, only with the prior permission in writing of the publishers, or in the case of reprographic reproduction, in accordance with the terms of licences issued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers.

Library of Congress Control Number: 2020945072

British Library Cataloguing in Publication data

A catalogue record for this book is available from the British Library

ISBN 978-1-5264-8676-9

ISBN 978-1-5264-8677-6 (pbk)

Editor: Aly Owen

Assistant editor: Lauren Jacobs

Production editor: Ian Antcliff

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Proofreader: Neville Hankins

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Cover design: Shaun Mercier

Typeset by: C&M Digitals (P) Ltd, Chennai, India

Printed in the UK

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About the Author
Mark Andrews (PhD) is Senior Lecturer in the Department of Psychology at 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 Societys Mathematics, Statistics, and Computing section. Between 2015 and 2018, Dr Andrews was funded by the UKs Economic and Social Research Council (ESRC) to provide advanced training workshops on Bayesian data analysis to UK-based researchers at PhD level and beyond in the social sciences. Dr Andrews 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.
Online Resources
Lecturers can visit httpsstudysagepubcomandrews to find a range of - photo 4

Lecturers can visit https://study.sagepub.com/andrews to find a range of additional resources to support teaching and aid your students study.

Instructor resources
  • PowerPoint slidescovering key themes and topics from every chapter, which are available for you to download and tailor in support of your teaching.
  • An instructors manual, providing a guide to using the book in teaching and resources for teaching, including ideas for student activities and assessments.
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