# Biostatistics: An Applied Introduction for the Public Health Practitioner

Cengage Learning, Aug 17, 2011 - Education - 608 pages
BIOSTATISTICS: AN APPLIED INTRODUCTION FOR THE PUBLIC HEALTH PRACTITIONER is designed to help public health researchers, practitioners, and students understand and apply essential biostatistics concepts. This innovative new text emphasizes real-world public health problems and the research questions they inspire. This text provides a unique introduction to statistical concepts and methods used by working professionals during investigations. Unlike other texts that assume a strong knowledge of mathematics or rely heavily on formulas, BIOSTATISTICS consistently emphasizes the public health context, making even complex material both accessible and relevant. The first chapter introduces common statistical terminology by explaining them in clear language, while subsequent chapters explore the most useful and versatile statistical methods for a variety of public health research questions. For each type of question, the author presents a range of applicable methods, from descriptions of data to simple statistical tests, generalized linear models, and multiple variable regression. The text's step-by-step coverage of fundamental concepts is perfect for students new to the field, but its depth and detail also make it ideal for two-course series in M.P.H. or M.H.A. programs, or for working professionals. Readers at all stages of their professional lives can draw on this invaluable resource to help them interpret and conduct statistical studies and support effective evidence-based practice.
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### Contents

 List of Tables Using this Text to Implement Data Analysis in Public Health About the Series About the Author Acknowledgments An Overview of Statistical Concepts Continuous Data Making Comparisons Continuous Data Correlation and Regression
 A Dichotomous Outcome Confounding Regression Count Data TimetoEvent Analysis Additional Topics Glossary of Key Terms References Index Copyright

 Categorical Data Comparisons and Associations