This book is a systematic, flexible guide to using biographical narrative methods as part of a research project, featuring a diverse range of case studies that show students how methods can be adapted to a range of international contexts and disciplines.

This book gets you up and running with doing complex Bayesian statistics, focussing on applied analysis rather than maths.

This book walks you step-by-step through the entire research process, covering everything you need to successfully conduct a sports research project in the real world.

Data archives provide rich and expansive sources of information for researchers. Part of the SAGE Qualitative Research Kit, this book highlights the utility of secondary data analyses whilst showing you how to select the right datasets for your study, and in turn get the most out of your research.

If you're a first-time researcher, this book covers everything you need to successfully complete your business research project, increase your employability and develop transferable skills.

If you're a first-time researcher, this book covers everything you need to successfully complete your business research project, increase your employability and develop transferable skills.

This book is a systematic, eight-step guide to qualitative content analysis, supporting you through each stage of your research project, no matter the type or amount of data.

An accessible, positive study guide for students with dyslexia, this book uses tried-and-tested learning strategies to empower students to achieve their academic goals.

A practical, up-to-date, step-by-step guidance on causal analysis; which features worked example datasets throughout to see methods in action. McBee clearly demonstrates techniques such as Rubin causal model, direct acyclic graphs and propensity score analysis.

Secondary Data in Mixed Methods Research by Daphne C. Watkins, is the latest contribution to the Mixed Methods Research Series. This brief text offers step-by-step procedures for incorporating existing data into mixed methods research designs, as well as identifying characteristics of datasets that make them good candidates for mixed methods projects.