Student Solutions Manual for Biostatistics for the Biological and Health Sciences

Biostatistics for the Biological and Health Sciences uses a variety of real-world applications to bring statistical theories and methods to life for the biological, life, medical, and health sciences. This title ensures that you understand concepts and develop skills in critical thinking, technology, and communication.

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. Dr. Triola and IIME have been funded by the NIH, the IAIMS program, the NSF Advanced Learning Technologies Program, the Josiah Macy, Jr. Foundation, the U. S. Department of Education, and the AMA 'Accelerating Change' program. He chairs numerous committees at the state and national level focused on the future of health professions educational technology development and research.

Mario F. Triola is a Professor Emeritus of Mathematics at Dutchess Community College, where he has taught statistics for over 30 years. Marty is the author of Elementary Statistics, 13th edition, Essentials of Statistics, 5th edition, Elementary Statistics Using Excel, 6th edition, Elementary Statistics Using the TI-83/84 Plus Calculator, 4th edition, and he is a co-author of Statistical Reasoning for Everyday Life, 5th edition. Elementary Statistics is currently available as an International Edition, and it has been translated into several foreign languages. 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, analyzing data in medical malpractice lawsuits, identifying salary inequities based on gender, and analyzing disputed election results. He has also used statistical methods in analyzing medical school surveys, and analyzing survey results for the New York City Transit Authority. Marty has testified as an expert witness in New York State Supreme Court.

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. He was recipient of the 2002 David P. Byar Young Investigator Award from the American Statistical Association Biometrics Section. 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 analyzing data from large healthcare databases. He collaborates in many different disease areas, including chronic kidney disease, cardiovascular disease, and liver diseases. Dr Roy is Associate Editor of Biometrics, Journal of the American Statistical Association, and Pharmacoepidemiology & Drug Safety, and has over 90 peer-reviewed publications.

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

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