Biostatistics for the Biological and Health Sciences / Edition 2

by Marc Triola, Mario Triola, Jason Roy

Overview

For courses in Introductory Statistics

Real-world applications connect statistical concepts to everyday life.

Biostatistics for the Biological and Health Sciences uses a variety of real-world applications to bring statistical theories and methods to life. Through these examples and a friendly writing style, the 2nd Edition ensures that you understand concepts and develop skills in critical thinking, technology, and communication. The result of collaboration between a biological sciences expert and the author of the #1 statistics book in the country, Biostatistics for the Biological and Health Sciences provides an excellent introduction to statistics for readers interested in the biological, life, medical, and health sciences.

Also available with MyLab Statistics

MyLab™ Statistics is an online homework, tutorial, and assessment program designed to work with this text to engage students and improve results. Within its structured environment, students practice what they learn, test their understanding, and pursue a personalized study plan that helps them absorb course material and understand difficult concepts.

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0134768345 / 9780134768342 Biostatistics for the Biological and Health Sciences Plus MyLab Statistics with Pearson eText — Title-Specific Access Card Package, 2/e

Package consists of:

• 0134039017 / 9780134039015 Biostatistics for the Biological and Health Sciences
• 0134748875 / 9780134748870 MyLab Statistics with Pearson eText — Standalone Access Card — for Biostatistics for the Biological and Health Sciences

Product Details

ISBN-13:	9780134039015
Publisher:	Pearson Education
Publication date:	01/01/2017
Edition description:	New Edition
Pages:	720
Product dimensions:	8.60(w) x 11.00(h) x 1.20(d)

About the Author

Marc Triola, MD, FACP is the Associate Dean for Educational Informatics at NYU School of Medicine, the founding director of the NYU Langone Medical Center Institute for Innovations in Medical Education (IIME), and an Associate Professor of Medicine. Dr. Triola’s research experience and expertise focuses on the disruptive effects of the present revolution in education, driven by technological advances, big data, and learning analytics. Dr. Triola has worked to create a “learning ecosystem” that includes inter-connected computer-based e-learning tools and new ways to effectively integrate growing amounts of electronic data in educational research.

Mario F. Triola is a Professor Emeritus of Mathematics at Dutchess Community College, where he has taught statistics for over 30 years. Marty designed the original Statdisk statistical software, and he has written several manuals and workbooks for technology supporting statistics education. He has been a speaker at many conferences and colleges. Marty’s consulting work includes the design of casino slot machines, the design of fishing rods, and he has worked with attorneys in determining probabilities in paternity lawsuits, analysing data in medical malpractice lawsuits, identifying salary inequities based on gender, and analysing disputed election results.

Jason Roy, PhD, is Associate Professor of Biostatistics in the Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania. He received his PhD in Biostatistics in 2000 from the University of Michigan. His statistical research interests are in the areas of causal inference, missing data, and prediction modeling. He is especially interested in the statistical challenges with analysing data from large healthcare databases. He collaborates in many different disease areas, including chronic kidney disease, cardiovascular disease, and liver diseases.

Table of Contents

• 1. Introduction to Statistics
• 2. Exploring Data with Tables and Graphs
• 3. Describing, Exploring, and Comparing Data
• 4. Probability
• 5. Discrete Probability Distributions
• 6. Normal Probability Distributions
• 7. Estimating Parameters and Determining Sample Sizes
• 8. Hypothesis Testing
• 9. Inferences from Two Samples
• 10. Correlation and Regression
• 11. Goodness-of-Fit and Contingency Tables
• 12. Analysis of Variance
• 13. Nonparametric Tests
• 14. Survival Analysis