• New examples, exercises, and Chapter Problems provide relevant and interesting real-world statistical applications, including biometric security, self-driving cars, smartphone data speeds, and the use of drones for delivery.
• More than 1,600 exercises are included in the text, and nearly 85% are brand new!
• More than 200 examples are scattered throughout the book, and almost 85% are new!
• Chapter Objectives provide summaries of key learning goals for each section in the chapter.
• Larger data sets give students a more comprehensive look at concepts. Full data sets in Appendix B can be downloaded at www.TriolaStats.com
• Real Data Sets: 89% of the exercises in the text use real data, and 87% of the examples feature real statistics.

• Content Updates:
• • Chapter 1 includes a new section about statistical and critical thinking, and a new subsection about big data.
  • Chapter 2 features a new section about scatterplots, linear correlation, and linear regression. It has also been divided into Chapters 2 and 3 for a deeper analysis of topics.
  • Chapter 3 covers statistics for describing, exploring, and comparing data, which was formerly part of Chapter 2.
  • Chapter 4 includes a new section about Bayes’ Theorem.
  • Chapter 5 features a section that combines binomial probability and mean, variance, and standard deviation.
  • Chapter 6’s order has been modified so content flows more effectively for students.
  • Chapter 7 features a new section about how to use technology for estimates.
  • Chapter 8 includes a combined section about testing a claim about a population mean.
  • Chapter 10 incorporates a new section about logistic regression.
  • Chapter 11 features a new subsection about the Test of Homogeneity, Fisher’s Exact Test, and McNemar’s Test for Matched Pairs.
  • Chapter 14 includes a new section about the Kaplan-Meier Method.

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.

• Exercises with immediate feedback– Assignable exercises are based on the textbook exercises, and regenerate algorithmically to give students unlimited opportunity for practice and mastery. MyLab Statistics provides helpful feedback when students enter incorrect answers and includes optional learning aids including Help Me Solve This, View an Example, videos, and an eText.
• UPDATED! Tech Tutorial Study Cards and Videos are effective tutorial learning aids and updated for Excel 2016 and Minitab 17 functionality.
• Learning Catalytics^™ helps generate class discussion, customize lectures, and promote peer-to-peer learning with real-time analytics. As a student response tool, Learning Catalytics uses students’ smartphones, tablets, or laptops to engage them in more interactive tasks and thinking.
• • NEW! Learning Catalytics Questions cover the book-specific statistical content from the new edition of Biostatistics for the Biological and Health Sciences.
  • NEW! Upload a full PowerPoint^® deck for easy creation of slide questions.
  • NEW! Team names are no longer case sensitive.Help your students develop critical thinking skills.
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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.