Presents the fundamentals of regression analysis, from its meaning to uses, in a concise, easy-to-read, and non-technical style.

This is the ideal introduction for students seeking to collect and analyze textual data from online sources. It covers the most critical issues that they must take into consideration at all stages of their research projects.

Offering a clear set of workable examples with data and explanations, Interaction Effects in Linear and Generalized Linear Models is a comprehensive and accessible text that provides a unified approach to interpreting interaction effects.

Fundamental Statistics is designed not to just teach students how to calculate statistics, but how to interpret the results of statistical analyses in light of a research hypothesis, and to communicate the results and interpretations to a broader audience.

Now in a fully updated third edition, The Sociology of Work draws on the work of classic and contemporary theorists, to provide readers with a thorough exploration of all aspects of work and employment, including paid and unpaid work, standard and non-standard employment, and even unemployment.

Programming with Python for Social Scientists offers a vital foundation to one of the most popular programming tools in computer science, specifically for social science researchers, assuming no prior coding knowledge.

With a calming, reassuring tone, Nicholas Walliman gives students the ability and confidence to plan, design, and prepare for a research project.

This book provides a balanced foundation in the principles and practices of social research, suitable for undergraduate and postgraduate students. It will be popular with lecturers who want to get their students thinking.

Proposing a post-positivist, interviewee-centred approach, Giampietro Gobo and Sergio Mauceri's new book offers students and researchers a practical introduction to the process of collecting and analyzing survey data.