Quantitative Social Science Data with R
SAGE Publications Ltd (Verlag)
978-1-5264-1150-1 (ISBN)
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"One of the few books that provide an accessible introduction to quantitative data analysis with R. A particular strength of the text is the focus on ′real world′ examples which help students to understand why they are learning these methods."
- Dr Roxanne Connelly, University of York
Relevant, engaging, and packed with student-focused learning features, this book provides the step-by-step introduction to quantitative research and data every student needs.
Gradually introducing applied statistics and R, it uses examples from across the social sciences to show you how to apply abstract statistical and methodological principles to your own work. At a student-friendly pace, it enables you to:
- Understand and use quantitative data to answer questions
- Approach surrounding ethical issues
- Collect quantitative data
- Manage, write about, and share the data effectively
Supported by incredible digital resources with online tutorials, videos, datasets, and multiple choice questions, this book gives you not only the tools you need to understand statistics, quantitative data, and R software, but also the chance to practice and apply what you have learned.
Brian Fogarty is Director of and Associate Professor of the Practice at the Center for Social Science Research, within the Center for Research Computing, at the University of Notre Dame, US. He is also concurrent research assistant professor in the Department of Political Science. As director of the CSSR, he works with social science researchers to support their project research design, data, and quantitative analysis needs. His current research focuses on the news media as a strategic actor in politics and understanding perceptions of voter and electoral fraud. Before joining Notre Dame, he was a lecturer in quantitative social science at the University of Glasgow’s Q-Step Centre. Prior to joining Glasgow, he was an associate professor of political science at the University of Missouri – St. Louis. He received his Ph.D. in political science from the University of North Carolina – Chapel Hill.
Chapter 1: Introduction
Chapter 2: Introduction to R and R Studio
Chapter 3: Finding Data
Chapter 4: Data Management
Chapter 5: Variables & Manipulation
Chapter 6: Developing Hypotheses
Chapter 7: Univariate & Descriptive Statistics
Chapter 8: Visualising Data
Chapter 9: Hypothesis Testing
Chapter 10: Bivariate Analysis
Chapter 11: Linear Regression & Model Building
Chapter 12: OLS Assumptions & Diagnostic Testing
Chapter 13: Putting it all Together
| Erscheinungsdatum | 09.01.2019 |
|---|---|
| Verlagsort | London |
| Sprache | englisch |
| Maße | 189 x 246 mm |
| Gewicht | 730 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra |
| Sozialwissenschaften ► Soziologie ► Empirische Sozialforschung | |
| ISBN-10 | 1-5264-1150-4 / 1526411504 |
| ISBN-13 | 978-1-5264-1150-1 / 9781526411501 |
| Zustand | Neuware |
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