One of the "six best books for data geeks" - Financial TimesWith over 200 images and extensive how-to and how-not-to examples, this new edition has everything students and scholars need to understand and create effective data visualisations. Combining 'how to think' instruction with a 'how to produce' mentality, this book takes readers step-by-step through analysing, designing, and curating information into useful, impactful tools of communication. With this book and its extensive collection ...

A Super Quick guide to planning an academic essay, from setting your structure and developing an argument to staying on topic.

Ideal for those new to teaching Research Methods, as well as more experienced instructors looking for new ways to engage their students, this applied resource places 100 activities - each accompanied by tutor notes and students handouts (also downloadable) - right at the instructor's fingertips.

With a strong focus on using less traditional forms of data, the Third Edition provides a new perspective on issues such as the role of the researcher and the impact they have on data, and also considers the impact of social, cultural and political complexities across a range of disciplines.

Focused on the needs of the new classroom researcher and those studying education on Masters-level courses, this is a thorough and thoughtful guide to the research process, covering qualitative, quantitative and mixed research methods.

Discover how to write winning essays and improve your grades, with this tried and tested guide to essay writing.

A sophisticated introduction to the diversity and interconnectivity of digital space, technology, objects, people and data. It sets out the theory and methods needed to understand digital life and then links them to real world data showcasing their strengths and challenges.Â

A step-by-step on five different qualitative approaches - thematic analysis, interpretative phenomenological analysis, grounded theory, narrative analysis and discourse analysis.

An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied regression analysis.

Drawing on the expertise of major names in the field, this text provides comprehensive coverage of the key methods for analyzing, interpreting, and writing up qualitative research in a single volume.