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Data Management in R: A Guide for Social Scientists

Autor Martin Elff
en Limba Engleză Paperback – 23 dec 2020
An invaluable, step-by-step guide to data management in R for social science researchers. 

This book will show you how to recode data, combine data from different sources, document data, and import data from statistical packages other than R. It explores both qualitative and quantitative data and is packed with a range of supportive learning features such as code examples, overview boxes, images, tables, and diagrams.
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Specificații

ISBN-13: 9781526459978
ISBN-10: 1526459973
Pagini: 272
Dimensiuni: 170 x 242 x 19 mm
Greutate: 0.44 kg
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications Ltd
Locul publicării:London, United Kingdom

Cuprins

1. Introduction
2. Building Blocks of Data
3. Data Frames
4. Data Tables and Tidyverse
5. Handling Data from Social Science Surveys
6. Managing Data from Complex Samples
7. Dates, Times, and Time Series
8. Spatial/Geographical data
9. Text as Data

Notă biografică

I am a political scientist with research interests in political sociology, political behaviour, comparative politics, and political methodology. In the first two areas I focus on electoral behaviour, political attitudes and behaviour in Germany, the relation between social structure and politics, and on political knowledge and political sophistication. My methodological research interests focus on the spatial modelling of party manifestos, survey research methodology in general, computational statistics and ecological inference. On these topics I have published a monograph, a variety of book chapters as well as research articles inActa Politica,Electoral Studies, theEuropean Journal of Political Research,German Politics,Perspectives on Politics, andPolitical Analysis.

Descriere

An invaluable step-by-step, pedagogically engaging guide to data management in R for social science researchers. This book shows students how to recode and document data, as well as how to combine data from different sources, or import from statistical packages other than R.