Addressing a common question posed by researchers, this book introduces readers to power analysis and sample size determination and clearly illustrates why sample sizes need to be sufficiently large to give good power properties and low error rates.

This comprehensive book provides guidelines for applying mixed-methods research in the development of culturally specific intervention programs and the subsequent evaluation.

With step-by-step instructions covering the entire research process, and with an emphasis on meaningful analysis to encourage good judgement, this book provides that ideal stepping stone between learning about research and actually doing it

This book offers insight into how to secure, manage and effectively research funding in the changing order of global economy and competing research priorities.

Systematically explains the concepts that have preoccupied medical sociologists from its inception, and which have shaped the field as it exists today.

Being able to read and interpret tables and graphs is a skill that is frequently tested and where students often lose marks in tests. This Little Quick Fix prepares students to read, interpret and produce tables and graphs with confidence and succeed in their exams.

From selecting appropriate methods to publishing your findings, this second edition offers a multidisciplinary introduction to the qualitative research process built around the authors' Qualitative Research Cycle - consisting of the design, data collection and analytic cycles.

Written with Jean McNiff's trademark enthusiasm and accessibility, this book - complete with a practical workbook - gives readers all they need to be able to do action research in their own context with confidence.

In this engaging and well-illustrated volume of the SAGE Quantitative Research Kit, Peter Martin helps you make the crucial steps towards mastering multivariate analysis of social science data, introducing the fundamental linear and non-linear regression models used in quantitative research. The author covers both the theory and application of statistical models, with the help of illuminating graphs.