This book provides a nonmathematical introduction to statistics to medical students, physicians, researchers, and graduate students in biological sciences. The goal has been to explain statistical principles in plain language so one can understand the results published in biological and medical journals. Like all statistical books, this one proves a few mathematical theorems and provides step-by-step methods for some statistical tests. But the emphasis is always on how to interpret the results, not on how to perform the tests. This book differs from other available introductory biostatistics books in several ways: 1)Broader range of topics. Leaf through current issues of major medical and scientific journals and you're sure to see articles whose conclusions are based on advanced statistical techniques not covered in most introductory books: survival curves, logistic regression, proportional hazards regression, nonlinear regression, Bayesian analysis, lod scores. Although it is impossible to discuss all these topics in depth in a short introductory book, this book explains what the tests are used for and how to interpret the results.2 )Emphasis on interpretation, not calculation. Many books devote many pages to step-by-step instructions for calculating statistical tests. This book assumes that the calculations will be done by computer, so places little emphasis on the mechanics of the calculations (and marks those sections, so they can be skipped). Instead, this book emphasizes understanding the assumptions the tests are based on and the interpretation of the results. 3)Emphasis on confidence intervals over P values. This book presents the concepts of confidence intervals before explaining P values. This makes it easier for the student to understand both.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
This book provides a nonmathematical introduction to statistics to medical students, physicians, researchers, and graduate students in biological sciences. The goal has been to explain statistical principles in plain language so one can understand the results published in biological and medical journals. Like all statistical books, this one proves a few mathematical theorems and provides step-by-step methods for some statistical tests. But the emphasis is always on how to interpret the results, not on how to perform the tests. This book differs from other available introductory biostatistics books in several ways: 1)Broader range of topics. Leaf through current issues of major medical and scientific journals and you're sure to see articles whose conclusions are based on advanced statistical techniques not covered in most introductory books: survival curves, logistic regression, proportional hazards regression, nonlinear regression, Bayesian analysis, lod scores. Although it is impossible to discuss all these topics in depth in a short introductory book, this book explains what the tests are used for and how to interpret the results. 2)Emphasis on interpretation, not calculation. Many books devote many pages to step-by-step instructions for calculating statistical tests. This book assumes that the calculations will be done by computer, so places little emphasis on the mechanics of the calculations (and marks those sections, so they can be skipped). Instead, this book emphasizes understanding the assumptions the tests are based on and the interpretation of the results. 3)Emphasis on confidence intervals over P values. This book presents the concepts of confidence intervals before explaining P values. This makes it easier for the student to understand both.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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