Biostatistics for the Biological and Health Sciences brings statistical theories and methods to life with real applications, emphasis on real data, and a friendly writing style. It suits a variety of students in their first statistics course and uses minimal algebra. Abundant examples and emphasis on real data help you develop skills in critical thinking, technology and communication. This collaboration from 2 biological sciences experts and the author of the #1 statistics book is an excellent introduction that is also highly readable, understandable and relevant. The 3rd Edition incorporates the latest methods used by professional statisticians. It offers a wealth of new data sets, examples, and exercises (such as those involving clinical trials, COVID-19, biometrics, and anthropometrics) and includes features that address all recommendations included in the Guidelines for Assessment and Instruction in Statistics Education (GAISE) as recommended by the American Statistical Association.
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INTRODUCTION TO STATISTICS 1-1 Statistical and Critical Thinking1-2 Types of Data1-3 Collecting Sample Data1-4 Ethics in Statistics (download only)EXPLORING DATA WITH TABLES AND GRAPHS2-1 Frequency Distributions for Organizing and Summarizing Data2-2 Histograms2-3 Graphs That Enlighten and Graphs That Deceive2-4 Scatterplots, Correlation, and Regression DESCRIBING, EXPLORING, AND COMPARING DATA 3-1 Measures of Center3-2 Measures of Variation3-3 Measures of Relative Standing and BoxplotsPROBABILITY 4-1 Basic Concepts of Probability4-2 Addition Rule and Multiplication Rule4-3 Complements, Conditional Probability, and Bayes' Theorem4-4 Risks and Odds4-5 Rates of Mortality, Fertility, and Morbidity4-6 CountingDISCRETE PROBABILITY DISTRIBUTIONS 5-1 Probability Distributions5-2 Binomial Probability Distributions5-3 Poisson Probability DistributionsNORMAL PROBABILITY DISTRIBUTIONS 6-1 The Standard Normal Distribution6-2 Real Applications of Normal Distributions6-3 Sampling Distributions and Estimators6-4 The Central Limit Theorem6-5 Assessing Normality6-6 Normal as Approximation to Binomial (download only)ESTIMATING PARAMETERS AND DETERMINING SAMPLE SIZES 7-1 Estimating a Population Proportion7-2 Estimating a Population Mean7-3 Estimating a Population Standard Deviation or Variance7-4 Bootstrapping: Using Technology for EstimatesHYPOTHESIS TESTING 8-1 Basics of Hypothesis Testing8-2 Testing a Claim About a Proportion8-3 Testing a Claim About a Mean8-4 Testing a Claim About a Standard Deviation or Variance8-5 Resampling: Using Technology for Hypothesis TestingINFERENCES FROM TWO SAMPLES 9-1 Two Proportions9-2 Two Means: Independent Samples9-3 Matched Pairs9-4 Two Variances or Standard Deviations9-5 Resampling: Using Technology for InferencesCORRELATION AND REGRESSION 10-1 Correlation10-2 Regression10-3 Prediction Intervals and Variation10-4 Multiple Regression10-5 Dummy Variables and Logistic RegressionGOODNESS-OF-FIT AND CONTINGENCY TABLES 11-1 Goodness-of-Fit11-2 Contingency TablesANALYSIS OF VARIANCE 12-1 One-Way ANOVA12-2 Two-Way ANOVANONPARAMETRIC TESTS 13-1 Basics of Nonparametric Tests13-2 Sign Test13-3 Wilcoxon Signed-Ranks Test for Matched Pairs13-4 Wilcoxon Rank-Sum Test for Two Independent Samples13-5 Kruskal-Wallis Test for Three or More Samples13-6 Rank CorrelationSURVIVAL ANALYSIS 14-1 Life Tables14-2 Kaplan-Meier Survival Analysis APPENDICES A: Tables and Formulas B: Data Sets C: Websites and Bibliography of Books D: Answers to Odd-Numbered Section Exercises (and all Quick Quizzes, all Review Exercises, and all Cumulative Review Exercises) Subject Index
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Hallmark features of this title Carefully selected real data: 92% of examples and 92% of exercises are based on real data.Margin essays illustrate uses and abuses of statistics in real, practical and interesting applications.Flow charts throughout simplify and clarify more complex concepts and procedures.Easy-to-assign exercises are graded by difficulty. Exercises that are particularly difficult or involve a new concept appear at the end of exercise sets and are marked by an asterisk for instructors' convenience.End-of-chapter features include chapter reviews, review exercises, From Data to Decision: Critical Thinking capstone problems, group activities, and more.The latest and best methods used by professional statisticians are incorporated.
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New and updated features of this title New exercises and examples: 54% of exercises and 58% of examples are new to the 3rd Edition.New and updated real data sets throughout provide relevant, interesting statistical applications, such as COVID-19 clinical trials and tracking, biometric security, body measurements, brain sizes and IQ scores, and data on births. An expanded data set library in Appendix B provides ready access to real and interesting data (28 data sets, from 18 in the previous edition).Larger data sets include 465,506; 70,942; 22,385; 6068; 5755; and 3982 cases. Working with such large data sets is essential in an age of big data and data science.New exercise types: Cumulative Review Exercises near the end of Chapters 9, 10 and 11 include open-ended questions that present students with a data set, then ask them to pose a key question relevant to the data, identify a procedure for addressing that question, and analyze the data to form a conclusion.New Big (or Very Large) Data Projects near the end of each chapter ask students to think critically while using large data sets.A new Chapter Problem Icon highlights Examples that relate to the Chapter Problem, to show how different statistical concepts and procedures can be applied to the real-world issue highlighted in the chapter.
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Produktdetaljer

ISBN
9781292452012
Publisert
2023-07-25
Utgave
3. utgave
Utgiver
Vendor
Pearson Education Limited
Vekt
1580 gr
Høyde
278 mm
Bredde
216 mm
Dybde
29 mm
Aldersnivå
U, 05
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
784

Om bidragsyterne

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. Dr. Triola and IIME have been funded by the National Institutes of Health, the Josiah Macy Jr. Foundation, the Department of Education, the Department of Defense, and the American Medical Association's Accelerating Change in Medical Education program.

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. 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 and 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 to analyze medical school surveys, survey results for the New York City Transit Authority, and COVID-19 virus data for government officials. Marty has testified as an expert witness in the New York State Supreme Court. As of this writing, Marty's Elementary Statistics has been the #1 statistics text in the United States for 27 consecutive years.

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. Previously, he was Professor of Biostatistics in the Department of Biostatistics, Epidemiology, and Informatics at the University of Pennsylvania. He received his PhD in Biostatistics in 2000 from the University of Michigan. He was the recipient of the 2002 David P. Byar Young Investigator Award from the American Statistical Association Biometrics Section. 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.