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Analysing Quantitative Data: Variable-based and Case-based Approaches to Non-experimental Datasets

Autor Raymond A. Kent
en Limba Engleză Paperback – 29 mar 2015
This innovative book provides a fresh take on quantitative data analysis within the social sciences. It presents variable-based and case-based approaches side-by-side encouraging you to learn a range of approaches and to understand which is the most appropriate for your research. Using two multidisciplinary non-experimental datasets throughout, the book demonstrates that data analysis is really an active dialogue between ideas and evidence.  Each dataset is returned to throughout the chapters enabling you to see the role of the researcher in action; it also showcases the difference between each approach and the significance of researchers’ decisions that must be made as you move through your analysis.
The book is divided into four clear sections:
  • Data and their presentation
  • Variable-based analyses
  • Case-based analyses
  • Comparing and combining approaches
Clear, original and written for students this book should be compulsory reading for anyone looking to conduct non-experimental quantitative data analysis.
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Specificații

ISBN-13: 9781446273418
ISBN-10: 1446273415
Pagini: 376
Dimensiuni: 170 x 242 x 20 mm
Greutate: 0.64 kg
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications Ltd
Locul publicării:London, United Kingdom

Recenzii

This compelling textbook provides a clear view of a broad range of possibilities for quantitative data, complementing the statistical toolbox with configurational methods. A must read for students aiming to get more out of data and move beyond 'push-button analysis'. 



Cuprins

Part 1: Quantitative data: structure, preparation and analysis approaches
Chapter 1: Data structure
Chapter 2: Data preparation
Chapter 3: Approaches to data analysis
Part 2: Variable-based analyses
Chapter 4: Univariate analysis
Chapter 5: Bivariate analysis
Chapter 6: Multivariate analysis
Part 3: Case-based analyses
Chapter 7: Set-theoretic methods and configurational data analysis
Chapter 8: Cluster and discriminant analysis
Part 4: Comparing and communicating results
Chapter 9: Comparing and mixing methods
Chapter 10: Evaluating hypotheses, explaining and communicating results

Notă biografică


Descriere

In covering both traditional and newer approaches, and presenting them alongside each other, and by consistently referring to two data sets throughout, this book provides students with a brand-new way of understanding methods and a tool with which they can think about their own research.