Quantitative Behavior Analysis
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Beschreibung
This book collects the major theories of quantitative analyses and applies them in a useful and meaningful way. Given the widespread use of quantitative analyses of behavior across disciplines, as its focus as a scientific approach to learning theories, this volume will be of great value to students, instructors, and researchers. This volume could also serve as a primary text for undergraduate courses in learning theory, and graduate courses in related disciplines.
One goal of behavioral science is to understand and predict human and animal behavior by studying how organisms interact with their environment. These predictions can be quite general and descriptive, or more precise and quantifiable. Quantitative analysis of behavior involves understanding behavior mathematically, relying on statistical models to study the relationship between behavior and environment. One advantage of this approach is that it allows for the experimental testing of behavioral theories, as well as how such theories generalize to the lives of people. These techniques also enable scientists to examine complex relationships by predicting how humans and animals behave with greater accuracy. Quantitative analyses of behavior are adopted in various disciplines and subfields of behavioral science including psychology, sociology, neuroscience, pharmacology, criminology, ethology, and behavioral medicine.
Quantitative approaches to understanding behavior have been prominent since as early as the 1950s. However, despite considerable advancement in precisely predicting and understanding behavior-environment relationships, different quantitative approaches and theories of behavior have not been collected in a single volume. This has led to researchers, scholars, academics, and even practitioners to struggle with learning about this scientific method, or the conditions under which quantitative models of behavior are useful. Moreover, although the quantitative analysis of behavior is often taught to graduate students in fields of behavioral science, instructors are often faced with relying on individual (often outdated) published articles to provide students, as no definitive text on this approach exists. As methods of quantitative analyses grow, this has become increasingly difficult and challenging for graduate program instructors.
In summary, the core principles of quantitative analysis of behavior are foundational to a broad spectrum of disciplines within behavioral science, and this book fosters interdisciplinary collaboration that shapes and expands each field's capabilities and applications. Moreover, this book aims to better prepare and enable students of behavioral science to explore behavior in increasingly sophisticated ways, addressing complex real-world questions.
This book collects the major theories of quantitative analyses and applies them in a useful and meaningful way. Given the widespread use of quantitative analyses of behavior across disciplines, as its focus as a scientific approach to learning theories, this volume will be of great value to students, instructors, and researchers. This volume could also serve as a primary text for undergraduate courses in learning theory, and graduate courses in related disciplines.
One goal of behavioral science is to understand and predict human and animal behavior by studying how organisms interact with their environment. These predictions can be quite general and descriptive, or more precise and quantifiable. Quantitative analysis of behavior involves understanding behavior mathematically, relying on statistical models to study the relationship between behavior and environment. One advantage of this approach is that it allows for the experimental testing of behavioral theories, as well as how such theories generalize to the lives of people. These techniques also enable scientists to examine complex relationships by predicting how humans and animals behave with greater accuracy. Quantitative analyses of behavior are adopted in various disciplines and subfields of behavioral science including psychology, sociology, neuroscience, pharmacology, criminology, ethology, and behavioral medicine.
Quantitative approaches to understanding behavior have been prominent since as early as the 1950s. However, despite considerable advancement in precisely predicting and understanding behavior-environment relationships, different quantitative approaches and theories of behavior have not been collected in a single volume. This has led to researchers, scholars, academics, and even practitioners to struggle with learning about this scientific method, or the conditions under which quantitative models of behavior are useful. Moreover, although the quantitative analysis of behavior is often taught to graduate students in fields of behavioral science, instructors are often faced with relying on individual (often outdated) published articles to provide students, as no definitive text on this approach exists. As methods of quantitative analyses grow, this has become increasingly difficult and challenging for graduate program instructors.
In summary, the core principles of quantitative analysis of behavior are foundational to a broad spectrum of disciplines within behavioral science, and this book fosters interdisciplinary collaboration that shapes and expands each field's capabilities and applications. Moreover, this book aims to better prepare and enable students of behavioral science to explore behavior in increasingly sophisticated ways, addressing complex real-world questions.
Represents the first definitive guide to quantitative analysis of behavior in one place Collects decades of behavioral research and behavioral theory which may otherwise be difficult to discern independently Bridges the gap between experimental and applied theories of behavior and unifies theories of animal and human behavior
Autor*in
Valdeep Saini
Themen in »Quantitative Behavior Analysis«
behavior analysis quantitative behavior analysis behavioral psychology quantitative modelling applied behavioral science learning theory