An Introduction to Data Analysis: Quantitative, Qualitative and Mixed Methods

by Tiffany Bergin

Covering the general process of data analysis to finding, collecting, organizing, and presenting data, this book offers a complete introduction to the fundamentals of data analysis.

Using real-world case studies as illustrations, it helps readers understand theories behind and develop techniques for conducting quantitative, qualitative, and mixed methods data analysis. With an easy-to-follow organization and clear, jargon-free language, it helps readers not only become proficient data analysts, but also develop the critical thinking skills necessary to assess analyses presented by others in both academic research and the popular media.

It includes advice

- Data analysis frameworks

- Validity and credibility of data

- Sampling techniques  

- Data management

- The big data phenomenon  

- Data visualisation

- Effective data communication

Whether you are new to data analysis or looking for a quick-reference guide to key principles of the process, this book will help you uncover nuances, complexities, patterns, and relationships among all types of data.

296 pages, Kindle Edition

Published October 15, 2018

Reviews

[William Axtell · Rating 4 out of 5]

This book is a good all-round introduction to data analysis. It is well written and illustrated and is comprehensive is scope, taking the reader from formulating research questions through to presenting results. What is less good, and perhaps inevitable, is that there could be more depth on many of the topics. For instance, in the chapters on quantitative anaylsis, there is no mention of confidence intervals or margins of error, which are pretty basic statistics work. Consequently, the book will not turn you into a data analyst. What it will do is give you a strong overview of the discipline to springboard into more detailed learning. It will also give those who don't work in data but rely on it to inform their decisions a good insight into how it works so they can better sort good research from bad.

[Erica Michaelson · Rating 5 out of 5]

This is a wonderful introduction to the very broad field of data analysis. The author clearly understands the landscape and writes in a very natural teaching style. This sounds odd but the one thing I never (ever) saw mentioned is the concept, purpose, and how to craft research objectives. The author instead focused on research questions or goals. I find objectives to be the cornerstone of my work and then derive my research questions/metrics (and pretty much everything else) from those objectives.

Regardless, this is a great and easy to read book.

[Christine Edwards · Rating 5 out of 5]

Excellent resource. Provides great guidance from beginning of the process to sharing the findings of your research. Structured well, easy to understand, and includes examples throughout.