Fr. 276.00

Biostatistics for Clinical and Public Health Research

English · Hardback

Shipping usually within 1 to 3 weeks (not available at short notice)

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Informationen zum Autor Melody S. Goodman, is a biostatistician with experience in study design, developing survey instruments, data collection, data management, and data analysis for public health and clinical research projects. She has taught introductory biostatistics to masters of public health and medical students for over ten years at multiple institutions (Stony Brook University School of Medicine, Washington University in St. Louis School of Medicine, New York University - Global Public Health). Klappentext Biostatistics for Clinical and Public Health Research provides a concise overview of statistical analysis methods. Use of SAS and Stata statistical software is illustrated in full, including how to interpret results.Focusing on statistical models without all the theory, the book is complete with exercises, case studies, take-away points, and data sets. Readers will be able to maximize their statistical abilities in hypothesis testing, data interpretation, and application while also learning when and how to consult a biostatistician.This book will be an invaluable tool for students and clinical and public health practitioners. Zusammenfassung This book provides a concise overview of statistical analysis methods for the clinical and public health practitioner. It teaches statistical models without all the theory. Use of SAS software is illustrated in full, including how to interpret results. Includes exercises, case studies, take-away points, and data sets. Inhaltsverzeichnis Descriptive Statistics. Introduction to SAS. Probability. Diagnostics. Discrete Probability Distributions. Continuous Probability Distributions. Probability Distributions. Estimation. One Sample Hypothesis Testing. Two Sample Hypothesis Sample. Nonparametric Statistics. One Sample and Two Sample Hypothesis Testing, Sample Size, and Nonparametric Methods. Categorical Data Sets. ANOVA. Correlation. Linear Regression. Logistic Regression. Survival Analysis. Data Analysis. ...

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