Textbooks
Explore our diverse range of digital textbooks designed for course adoption and recommended reading at universities and colleges. We publish over 140 textbooks across the social sciences, and an annual subscription to digital textbooks is possible via BUP Digital.
Our content is fully searchable and can be accessed on and off-campus through Shibboleth, OpenAthens or an institutional authenticated IP. For any questions on digital textbook pricing and subscription information, please contact simon.bell@bristol.ac.uk.
We are happy to provide digital samples of any of our coursebooks by completing this form. To see the full collection of all our core textbooks, browse our main website.
Books: Textbooks
Qualitative data comes in a variety of forms: text, images, sound and so on, which can be difficult for researchers to analyse confidently. This chapter begins by setting out how qualitative data can be prepared, for example by transcribing interview or focus group data, converting pictorial data to text or creating metadata records ready for analysis. This is followed by guidance on how to code the prepared data, using a coding frame or emergent coding, and an overview of the pros and cons of each method. Next, various ways of analysing qualitative data including content analysis, thematic analysis, discourse analysis and narrative analysis are outlined, followed by a real-life example of qualitative data analysis. Data synthesis is discussed briefly, and the chapter concludes with an update of the case studies followed by exercises, discussion questions and a debate topic.
All researchers should have a grasp of both quantitative and qualitative data analysis methods as most projects will involve both to some degree. This chapter provides advice on the preparation of quantitative data and information about how to code this data. It then examines ways of analysing quantitative data using descriptive and inferential statistics. The statistics methods described include frequency distributions (tables, graphs or pie charts), measures of central tendency (mode, median, and mean or average) measures of variability (correlation coefficient and chi-square test). It also describes the most common parametric tests (t-test, F-test, analysis of variance (ANOVA), cluster analysis, factor analysis and regression analysis) and lists the non-parametric equivalents. Univariate and bivariate statistics are covered including and explanation of covariant and independent data relationships. The chapter closes with an update of the case studies followed by exercises, discussion questions and a debate topic.
Every researcher will encounter ethical dilemmas as social research has the capacity to do great harm, to individuals, groups, and society as a whole, if it is unethically managed. This chapter, which is new to this third edition, explores research and evaluation ethics. It begins with an overview of ethics, then explains the current system of research ethics management including the process of obtaining ethical approval from research ethics committees. Emphasis is given to the importance of researchers thinking and acting ethically throughout the research process. The chapter gives an overview of ethics considerations for each stage of a research project from conception to dissemination of results. Researcher wellbeing is another important ethical consideration and one that is often neglected by researchers and ethics committees alike. Factors affecting researcher wellbeing are outlined along with strategies for managing and reducing stress. The chapter concludes with an update of the case studies followed by exercises, discussion questions and a debate topic.
Research doesn’t exist in a bubble but co-exists with a multitude of other tasks and commitments, yet there is more need for people to save time than ever before.
Brilliantly attuned to the demands placed on researchers, this book considers how students, academics and professionals alike can save time and stress without compromising the quality of their research or its outcomes. This third edition:
- is fully revised with new chapters on research and evaluation ethics, creative methods of collecting data and how research can make a positive difference;
-includes illustrative case studies throughout the book and each chapter concludes with exercises, discussion questions and a debate topic;
- is accompanied by a fully updated companion website.
This supportive book is designed for any student or practitioner who wants to know how to do research on top of their main job and still have a life.
Secondary data is data which has been collected by someone else, for a purpose other than a researcher’s own research or evaluation project, and has been made available for re-use. Due to great efforts to make data available to the public, there is now a huge amount of secondary data freely available online, and more is being added all the time. Secondary data is also held in libraries, museums and archives. This chapter explains the advantages and disadvantages of working with secondary data and shows how to find online data sources. It provides information about open data worldwide and looks at application programming interfaces (APIs). It discusses large-scale and international surveys, alongside examples. It includes advice on working with secondary data and concludes with an update of the case studies followed by exercises, discussion questions and a debate topic.
A good research project is built on solid foundations and this chapter begins with some advice on choosing a research or evaluation topic. Information is provided about how to refine your topic into a question followed by a discussion of how to use your research question to guide your data collection. Consideration is then given to how much data is needed and whether it should be quantitative or qualitative. An outline of sampling techniques follows including probability and non-probability sampling. Next, the issue of what constitutes evidence for research is discussed including the ‘hierarchy of evidence’. Guidance on writing a proposal is provided including a suggested list of contents and this is followed by some information about research funders. The chapter concludes with an update of the case studies followed by exercises, discussion questions and a debate topic.
Writing is not a discrete activity which happens late in the research or evaluation process. It starts at conception and continues through every stage of research and often beyond the end of the project. This chapter begins by identifying and dispelling some myths about the writing process. This is followed by a guide to the writing process including how to get started, the non-linear nature of writing, rules for plain English, example report structures and how to avoid common pitfalls. The topics of structure, plagiarism and citation are covered in detail and the difference between findings and recommendations is explained. Text editing is covered including how and when to seek external feedback and how to use this constructively. Guidance is given on how to polish writing, and this is followed by an update of the case studies followed by exercises, discussion questions and a debate topic.