Qualitative Data Analysis: An Introduction, Edition 2

SAGE
Free sample

In this fully updated and expanded second edition, Carol Grbich provides a guide through current issues in the analysis of qualitative data. Packed with detailed examples, a glossary, further reading lists and a section on writing up, this book is exactly what you need to get you started in qualitative research.

The new edition covers analytical approaches including:

- grounded theory

- classical, existential and hermeneutic phenomenology

- feminist research including memory work

- classical, auto- and cyberethnography as well as ethnodrama

- content, narrative, conversation and discourse analysis

- visual interpretation

- semiotic, structural and poststructural analyses

A one-stop-shop for students new to qualitative data analysis!


Available with Perusall—an eBook that makes it easier to prepare for class
Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.

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About the author

Carol Grbich is in the Faculty of Health Sciences, The Flinders University of South Australia.

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Additional Information

Publisher
SAGE
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Published on
Nov 19, 2012
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Pages
344
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ISBN
9781446271797
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Language
English
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Genres
Reference / Research
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Content Protection
This content is DRM protected.
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Reading information

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Watch Andy Field's introductory video to Discovering Statistics Using R

Keeping the uniquely humorous and self-deprecating style that has made students across the world fall in love with Andy Field's books, Discovering Statistics Using R takes students on a journey of statistical discovery using R, a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences throughout the world.

The journey begins by explaining basic statistical and research concepts before a guided tour of the R software environment. Next you discover the importance of exploring and graphing data, before moving onto statistical tests that are the foundations of the rest of the book (for example correlation and regression). You will then stride confidently into intermediate level analyses such as ANOVA, before ending your journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help you gain the necessary conceptual understanding of what you're doing, the emphasis is on applying what you learn to playful and real-world examples that should make the experience more fun than you might expect.

Like its sister textbooks, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is augmented by a cast of characters to help the reader on their way, together with hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more.

Given this book's accessibility, fun spirit, and use of bizarre real-world research it should be essential for anyone wanting to learn about statistics using the freely-available R software.

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