Biostatistics for the Biological and Health Sciences, Global Edition -- MyLab Statistics with Pearson eText

Mark 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 focuses on precision education and the use of AI tools to efficiently personalize medical education for individual learners and give new insights to their programs and coaches. His lab develops new learning technologies and AI-driven educational interventions and also works to define educationally sensitive patient and system outcomes that can be used to assess the impact of training. 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, 14th Edition; Essentials of Statistics, 7th Edition; Elementary Statistics Using Excel, 7th Edition; and Elementary Statistics Using the TI-83/84 Plus Calculator, 5th Edition; and he is a co-author of Statistical Reasoning for Everyday Life, 5th Edition. Mario 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. Jason Roy, PhD is a Professor of Biostatistics and Chair of the Department of Biostatistics and Epidemiology at Rutgers University. He is director of Rutgers University Biostatics and Epidemiology Services and co-director of Biostatistics, Epidemiology, and Research Design core, NJ ACTS. Dr. Roy is interested in methodological research in developing flexible Bayesian methods for large, observational studies, especially data from EHR and mobile health. He is particularly interested in causal inference problems, where Bayesian nonparametric methods can be used in conjunction with g-computation. He is also interested in functional clustering methods, which can be very useful for extracting features from intensively collected data (such as from mobile devices). Much of his collaborative research is in pharmacoepidemiology.

Introduction to statistics
Exploring data with tables and graphs
Describing, exploring and comparing data
Probability
Discrete probability distributions
Normal probability distributions
Estimating parameters and determining sample sizes
Hypothesis testing
Inferences from two samples
Correlation and regression
Goodness-of-fit and contingency tables
Analysis of variance
Nonparametric tests
Survival analysis