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Measuring Behaviour is the established go-to text for anyone interested in scientific methods for studying the behaviour of animals or humans. It is widely used by students, teachers and researchers in a variety of fields, including biology, psychology, the social sciences and medicine. This new fourth edition has been completely rewritten and reorganised to reflect major developments in how behavioural studies are conducted. It includes new sections on the replication crisis, covering Open Science initiatives such as preregistration, as well as fully up-to-date information on the use of remote sensors, big data and artificial intelligence in capturing and analysing behaviour. The sections on the analysis and interpretation of data have been rewritten to align with current practices, with advice on avoiding common pitfalls. Although fully revised and revamped, this new edition retains the simplicity, clarity and conciseness that have made Measuring Behaviour a classic since the first edition appeared more than 30 years ago.
Measuring Behaviour is the established go-to text for anyone interested in scientific methods for studying the behaviour of animals or humans. It is widely used by students, teachers and researchers in a variety of fields, including biology, psychology, the social sciences and medicine. This new fourth edition has been completely rewritten and reorganised to reflect major developments in how behavioural studies are conducted. It includes new sections on the replication crisis, covering Open Science initiatives such as preregistration, as well as fully up-to-date information on the use of remote sensors, big data and artificial intelligence in capturing and analysing behaviour. The sections on the analysis and interpretation of data have been rewritten to align with current practices, with advice on avoiding common pitfalls. Although fully revised and revamped, this new edition retains the simplicity, clarity and conciseness that have made Measuring Behaviour a classic since the first edition appeared more than 30 years ago.
This book is designed for an undergraduate, one-semester course in experimental research, primarily targeting programs in sociology, political science, environmental studies, psychology, and communications. Aimed at those with limited technical background, this introduction to social science experiments takes a practical, hands-on approach. After explaining key features of experimental designs, Green takes students through exercises designed to build appreciation for the nuances of design, implementation, analysis, and interpretation. Using applications and statistical examples from many social science fields, the textbook illustrates the breadth of what may be learned through experimental inquiry. A chapter devoted to research ethics introduces broader ethical considerations, including research transparency. The culminating chapter prepares readers for their own social science experiments, offering examples of studies that can be conducted ethically, inexpensively, and quickly. Replication datasets and R code for all examples and exercises are available online.
This book is designed for an undergraduate, one-semester course in experimental research, primarily targeting programs in sociology, political science, environmental studies, psychology, and communications. Aimed at those with limited technical background, this introduction to social science experiments takes a practical, hands-on approach. After explaining key features of experimental designs, Green takes students through exercises designed to build appreciation for the nuances of design, implementation, analysis, and interpretation. Using applications and statistical examples from many social science fields, the textbook illustrates the breadth of what may be learned through experimental inquiry. A chapter devoted to research ethics introduces broader ethical considerations, including research transparency. The culminating chapter prepares readers for their own social science experiments, offering examples of studies that can be conducted ethically, inexpensively, and quickly. Replication datasets and R code for all examples and exercises are available online.