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This course demystifies how social scientists from various disciplines generate knowledge about the world and the rationale for their choices on the research design.
This book was initially written as a methodology textbook for sociology courses, but has been increasingly used in the fields of psychology, public administration, urban studies, education, communications, social sciences, and political science. Part One examines the fundamental characteristics and issues that make science- defined as a method of inquiry by Babbie- different from other ways of knowing things. Part Two deals with the posing of proper scientific questions, the structuring of inquiry. Part Three presents various observational techniques available to social scientists. Part Four discusses the analysis of social research data and examines the steps that separate observation from the final reporting of findings.
This second edition provides an introduction to social science methodology relevant to the disciplines of anthropology, economics, history, political science, psychology, and sociology. This book is organized into 4 parts. Part 1 introduces elements of the social science enterprise that are general in purview. Part 2 focuses on description, that is, on empirical propositions that answer what, how, when, whom or in what manner questions. Part 3 focuses on causation, that is, on empirical arguments that answer why questions. Part 4 concludes the book by discussing the problem of unity and diversity, as well as the setting of standards.
This book introduces research methodology that covers the disciplines such as health, education, psychology, social work, nursing, public health, library studies and marketing research, and the approach to research is a combination of both quantitative research and qualitative research. This book is specifically designed for new beginners in this field. It summarizes an eight-step instruction: Formulating a research problem; conceptualizing a research design; constructing an instrument for data collection; selecting a sample; writing a research proposal; collecting data; processing and displaying data; writing a research report. 17 chapters are organized into these 8 steps, which constitute the content of the book.
This book is aimed at engaging scholars in the collective and collaborative process of forwarding qualitative geography in the twenty-first century. The research is situated in broader academic, political, and social currents rather than conceptualizing research. This book is organized into 3 parts. Part 1 introduces the history of qualitative research, and examines the multifaceted positioning of the researcher in social, political, and theoretical contexts. Part 2 introduces particular strategies of qualitative methods. Part 3 embraces and critiques the ways that qualitative research is analyzed, interpreted, and communicated, and shows how those processes might be moved into the future.
This sixth edition provides a complete portal to the world of case study research. It consists of 6 chapters. Chapter 1 discusses how to know whether and when to use the case study as a research method. Chapter 2 focuses on identifying your cases and establishing the logic of your case study. Chapter 3 discusses what you need to do before starting to collect case study data. Chapter 4 discusses the principles you should follow in working with six sources of evidence. Chapter 5 discusses how to start your analysis, your analytic choices, and how they work. Chapter 6 focuses on how and what to compose when reporting case studies.
This book introduces ways of analyzing meaningful matter, texts, images, and voices. It is organized into 3 parts. Part 1 introduces the history of content analysis, discusses the definition of content analysis, and presents the ways in which content analysis has been applied. Part 2 outlines the procedures used in content analysis, beginning with their procedural logic and moving naturally from unitizing, sampling, recording/coding in terms of formal data languages and analytical constructs. Part 3 traces several paths through content analysis protocols, including analytical constructs, the use of computers and computational techniques, and the two principal criteria used in evaluating content analyses: reliability and validity.
This fourth edition presents the tools and concepts used in multivariate data analysis. It surveys the basic principles and emphasizes both exploratory and inferential statistics. It consists of 22 chapters divided in to 4 parts. All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior.
This book develops a unified approach to qualitative and quantitative research in political science, showing how the same logic of inference underlies both. Issues discussed are related to framing research questions, measuring the accuracy of data and the uncertainty of empirical inferences, discovering causal effects, and getting the most out of qualitative research. It addresses topics such as interpretation and inference, comparative case studies, constructing causal theories, dependent and explanatory variables, the limits of random selection, selection bias, and errors in measurement. The book only uses mathematical notation to clarify concepts, and assumes no prior knowledge of mathematics or statistics.
This book is an introduction to content analysis methods from a social science perspective. Readers are expected to have basic knowledge in research methods and in data analysis or social statistics. Chapter 1 briefly introduces what content analysis method is and what purposes it serves. Chapter 2 describes the central idea of content analysis method in detail. Chapter 3 presents a wide range of techniques, with its focus on computer-aided content analysis. Chapter 4 presents the methodological problems in the following categories: measurement, indication, representation, and interpretation. The Appendix discusses several programs for text analysis and includes information on hardware compatibility and software sources.
This book is aimed to describe Q methodology and its techniques. Its contents cover methodological principles, samples and cases, statistical analysis, and subjective-science postscript. The distinctions between Q-methodological research approach based on the measurement and study of subjective phenomena and R-methodological research approach based on the correlation of objective traits are also taken seriously in this book. According to the author, the primary purpose of undertaking a Q study is to discern people’s perceptions of their work from the vantage point of self-reference, and Q projects typically employ small number of respondents, even in-depth studies of single cases.
This book seeks to identify causal connections and to understand their generality. It describes ways in which testing causal propositions can be improved in specific research projects and ways to improve generalizations about causal propositions, with emphasis on field experimentation and on human behavior in nonlaboratory settings. Contents of the book cover experiments and generalized causal inference, statistical conclusion validity and internal validity, construct validity and external validity, quasi-experimental designs, quasi experiments, regression discontinuity designs, randomized experiments, practical problems, generalized causal inference, and a critical assessment of this book’s assumptions.
