Statistical Rethinking

Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today's model-based statistics, the book pushes you to perform step-by-step calculations that are usually automated. This unique computational approach ensures that you

Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers

This important collection of essays is a synthesis of foundational studies in Bayesian decision theory and statistics. An overarching topic of the collection is understanding how the norms for Bayesian decision making should apply in settings with more than one rational decision maker and then tracing out some of the

'Rethinking Social Inquiry' offers a cohesive set of reflections on the quest for common standards drawn from quantitative methodology. The contributors argue that these standards must be drawn from exemplary qualitative research as well as the best quantitative studies.

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Books about Proceedings of the Indian Science Congress

Books about Proceedings of the ... Indian Science Congress

Rethinking Risk and the Precautionary Principle challenges the claim that the precautionary principle is an appropriate guide to public policy decision-making in the face of uncertainty. The precautionary principle is frequently invoked as a justification for regulating human activities. From bans on the use of growth hormones in cattle to

Offering a philosophical perspective to the educational improvement agenda, this engaging text provides a new language for research into educational improvement, bringing leading-edge philosophy to current practice. Drawing on philosophical work, including that of Derrida, Foucault and Heidegger, the authors deconstruct the ethic of improvement before exploring key dimensions of

This book examines how the discipline of statistics should respond to the changing environment in which statisticians work. What does the academic, industry, and government customer need? How can the content of courses and of the overall statistics educational experience be arranged to address the customer's needs? Interdisciplinary needs are