R for Healthcare Research - Volume I: Basic Statistical Methods

87.89 SGD
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79.11
English

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Product Description

R for Healthcare Research is intended to show healthcare professionals, researchers, and students of healthcare research how to use the open-source statistical software R. It is designed for both novices and experienced users, guiding readers from the fundamentals of installing the software through to a careful and thorough coverage of the most widely used techniques in healthcare research and evidence-based medicine.This textbook is structured to provide readers with a conceptual understanding of the theories, analyses, and models found in healthcare research, and to act as a practical guide for how to program these concepts in R. Volume I covers the basics of statistics, including data types, probability, and sampling, before moving on to survey common measures of disease and the most appropriate ways of displaying data. Readers will gain a solid grounding in how to conduct comparisons between groups, how to evaluate the strength of association, and how to check the accuracy of their tests.Worked examples are consistently provided throughout, and each chapter concludes with exercises to familiarise readers with the topics covered. An R package hosting all of the referenced datasets accompanies this textbook.

R for Healthcare Research is intended to show healthcare professionals, researchers, and students of healthcare research how to use the open-source statistical software R. It is designed for both novices and experienced users, guiding readers from the fundamentals of installing the software through to a careful and thorough coverage of the most widely used techniques in healthcare research and evidence-based medicine.This textbook is structured to provide readers with a conceptual understanding of the theories, analyses, and models found in healthcare research, and to act as a practical guide for how to program these concepts in R. Volume I covers the basics of statistics, including data types, probability, and sampling, before moving on to survey common measures of disease and the most appropriate ways of displaying data. Readers will gain a solid grounding in how to conduct comparisons between groups, how to evaluate the strength of association, and how to check the accuracy of their tests.Worked examples are consistently provided throughout, and each chapter concludes with exercises to familiarise readers with the topics covered. An R package hosting all of the referenced datasets accompanies this textbook.

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