Models for Non-Modelers focuses not on how to design models, but on how to understand and critically appraise them. Data and statistical models are widely used in disciplines such as epidemiology, climate science and systems design, but it can be difficult for those without the necessary training to understand and implement them.
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Göran Djurfeldt is Emeritus Professor, Department of Sociology, Lund University, Sweden. He has had a long career in sociology and development studies and a career-long interest in methodological issues. Djurfeldt has worked with all types of methods, such as historical studies and other qualitative methods, as well as field work in Scandinavia, in South Asia and in sub-Saharan Africa.
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Paperback. Condición: new. Paperback. Models for Non-Modelers focuses not on how to design models but on how to understand and critically appraise them. Data and statistical models are widely used in disciplines such as epidemiology, climate science and systems design, but it can be difficult for those without the necessary training to understand and implement them.This book is for non-modelers, especially social scientists. Through extensive examination of some common models both in visual and text form, this book shows these non-modellers how to understand the problems, both in the logic and implementation of such models. It includes in-depth worked examples and boxed text for more technical aspects. It does not require the reader to have in-depth mathematical knowledge. Also working through some common models in epidemiology and climate change scholarship, it examines AI and the problem of causality.This book will be suitable for graduate students and researchers in the social sciences who would like to learn more about how to assess models and the steps they need to take to apply them in their own research, as well as for those taking first courses in quantitative methods and statistical analysis for research data analysis. Models for Non-Modelers focuses not on how to design models, but on how to understand and critically appraise them. Data and statistical models are widely used in disciplines such as epidemiology, climate science and systems design, but it can be difficult for those without the necessary training to understand and implement them. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9781032357379
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Paperback. Condición: New. Models for Non-Modelers focuses not on how to design models but on how to understand and critically appraise them. Data and statistical models are widely used in disciplines such as epidemiology, climate science and systems design, but it can be difficult for those without the necessary training to understand and implement them.This book is for non-modelers, especially social scientists. Through extensive examination of some common models both in visual and text form, this book shows these non-modellers how to understand the problems, both in the logic and implementation of such models. It includes in-depth worked examples and boxed text for more technical aspects. It does not require the reader to have in-depth mathematical knowledge. Also working through some common models in epidemiology and climate change scholarship, it examines AI and the problem of causality.This book will be suitable for graduate students and researchers in the social sciences who would like to learn more about how to assess models and the steps they need to take to apply them in their own research, as well as for those taking first courses in quantitative methods and statistical analysis for research data analysis. Nº de ref. del artículo: LU-9781032357379
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Paperback. Condición: New. Models for Non-Modelers focuses not on how to design models but on how to understand and critically appraise them. Data and statistical models are widely used in disciplines such as epidemiology, climate science and systems design, but it can be difficult for those without the necessary training to understand and implement them.This book is for non-modelers, especially social scientists. Through extensive examination of some common models both in visual and text form, this book shows these non-modellers how to understand the problems, both in the logic and implementation of such models. It includes in-depth worked examples and boxed text for more technical aspects. It does not require the reader to have in-depth mathematical knowledge. Also working through some common models in epidemiology and climate change scholarship, it examines AI and the problem of causality.This book will be suitable for graduate students and researchers in the social sciences who would like to learn more about how to assess models and the steps they need to take to apply them in their own research, as well as for those taking first courses in quantitative methods and statistical analysis for research data analysis. Nº de ref. del artículo: LU-9781032357379
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