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The idea that simplicity matters in science is as old as science itself, with the much cited example of Ockham's Razor. A problem with Ockham's Razor is that nearly everybody seems to accept it, but few are able to define its exact meaning and to make it operational in a non-arbitrary way. Using a ...

The idea that simplicity matters in science is as old as science itself, with the much cited example of Ockham's Razor. A problem with Ockham's Razor is that nearly everybody seems to accept it, but few are able to define its exact meaning and to make it operational in a non-arbitrary way. Using a multidisciplinary perspective including philosophers, mathematicians, econometricians and economists, this monograph examines simplicity by asking six questions: What is meant by simplicity? How is simplicity measured? Is there an optimum trade-off between simplicity and goodness-of-fit? What is the relation between simplicity and empirical modelling? What is the relation between simplicity and prediction? What is the connection between simplicity and convenience?

While heated arguments between practitioners of qualitative and quantitative research have begun to test the very integrity of the social sciences, Gary King, Robert Keohane, and Sidney Verba have produced a farsighted and timely book that promises to sharpen and strengthen a wide range of research ...

While heated arguments between practitioners of qualitative and quantitative research have begun to test the very integrity of the social sciences, Gary King, Robert Keohane, and Sidney Verba have produced a farsighted and timely book that promises to sharpen and strengthen a wide range of research performed in this field. These leading scholars, each representing diverse academic traditions, have developed a unified approach to valid descriptive and causal inference in qualitative research, where numerical measurement is either impossible or undesirable. Their book demonstrates that the same logic of inference underlies both good quantitative and good qualitative research designs, and their approach applies equally to each.Providing precepts intended to stimulate and discipline thought, the authors explore issues related to framing research questions, measuring the accuracy of data and uncertainty of empirical inferences, discovering causal effects, and generally improving qualitative research. Among the specific topics they address are interpretation and inference, comparative case studies, constructing causal theories, dependent and explanatory variables, the limits of random selection, selection bias, and errors in measurement. Mathematical notation is occasionally used to clarify concepts, but no prior knowledge of mathematics or statistics is assumed. The unified logic of inference that this book explicates will be enormously useful to qualitative researchers of all traditions and substantive fields.

How do we go about weighing evidence, testing hypotheses, and making inferences? According to the model of Inference to the Best Explanation , we work out what to infer from the evidence by thinking about what would actually explain that evidence, and we take the ability of a hypothesis to explain ...

How do we go about weighing evidence, testing hypotheses, and making inferences? According to the model of Inference to the Best Explanation , we work out what to infer from the evidence by thinking about what would actually explain that evidence, and we take the ability of a hypothesis to explain the evidence as a sign that the hypothesis is correct. In Inference to the Best Explanation , Peter Lipton gives this important and influential idea the development and assessment it deserves.The second edition has been substantially enlarged and reworked, with a new chapter on the relationship between explanation and Bayesianism, and an extension and defence of the account of contrastive explanation. It also includes an expanded defence of the claims that our inferences really are guided by diverse explanatory considerations, and that this pattern of inference can take us towards the truth. This edition of Inference to the Best Explanation has also been updated throughout and includes a new bibliography.