B. Burt Gerstman, MPH, PhD, is a Professor of Health Science at San Jose State University.

Basic Biostatistics is a compact introduction text that covers biostatistical principles and concentrates on data types often found in public health and scientific professions. The book emphasizes both exploratory and confirmatory statistical methods. Detailed, comprehensive examples cover sampling, exploratory data analysis, estimation, hypothesis testing, and power and precision.

Basic Biostatistics is organized into three parts: Part I covers foundational concepts and techniques; Part II offers analytic techniques for quantitative response variables; and Part III covers strategies for categorical replies. Many new exercises are included in the Second Edition. This is the ideal introductory biostatistics text for undergraduates and graduates in diverse sectors of public health, with language, examples, and activities that are understandable to those with little mathematics backgrounds.

Throughout Basic Biostatistics, there are illustrative, relevant examples and activities. The answers to the odd-numbered exercises can be found in the back of the book. (Instructors may ask the publisher for answers to even-numbered exercises.) To allow for flexibility in the order of covering, chapters are purposefully brief and limited in scope. Manual computations are given equal weight, as is the use of statistical tools such as StaTable, SPSS, and WinPepi. A comprehensive companion website offering resources for both students and instructors.

Author: B. Burt Gerstman

Link to buy: https://www.amazon.com/Basic-Biostatistics-Statistics-Public-Practice/dp/1284036014/

Ratings: 4.4 out of 5 stars (from 325 reviews)

Best Sellers Rank: #55,204 in Books

#2 in Biostatistics (Books)

#6 in Epidemiology (Books)

John C. Pezzullo, PhD, has held faculty positions at Georgetown University in the departments of biomathematics and biostatistics, pharmacology, nursing, and internal medicine. He is semi-retired and still teaches biostatistics and clinical trial design to Georgetown University students online.

Students studying medicine, epidemiology, forestry, agriculture, bioinformatics, and public health must take biostatistics. In the past, this course was primarily a graduate-level requirement; however, its application is expanding, and undergraduate course offerings are expanding. Biostatistics For Dummies is a wonderful resource for individuals taking a course or looking for a quick reference to this complex subject.

Biostatisticians, or biological data analysts, are tasked with answering some of the world's most important health problems, such as how safe and effective pharmaceuticals on the market today are. What factors contribute to autism? What are the cardiovascular disease risk factors? Are there different risk factors for males and women, or for various ethnic groups? Biostatistics For Dummies investigates these and other issues related to the study of biostatistics.

• To assist, it provides plain-English descriptions of methodologies as well as clinical cases.
• This book is a fantastic course supplement for students who are struggling with the complexity of biostatistics.
• Tracks correspond to a standard basic biostatistics course.

Author: John Pezzullo

Link to buy: https://www.amazon.com/Biostatistics-Dummies-John-Pezzullo/dp/1118553985/

Ratings: 4.8 out of 5 stars (from 352 reviews)

Best Sellers Rank: #55,464 in Books

#3 in Biostatistics (Books)

#5 in Bioinformatics (Books)

Vrije Universiteit Amsterdam awarded Konrad Banachewicz a PhD in statistics. He is a Kaggle Grandmaster and eBay's top data scientist. He worked on a wide range of quantitative data analysis problems in a number of financial firms. As a result, he became an authority on the complete life cycle of a data product.

Luca Massaron, who started Kaggle over ten years ago, is a Kaggle Grandmaster in talks and a Kaggle Master in competitions and notebooks. In Kaggle tournaments, he ranked seventh in the globe. Luca is a data scientist with over a decade of expertise translating data into intelligent artifacts, solving real-world challenges, and delivering value for organizations and stakeholders. He is a machine learning Google Developer Expert (GDE) and the author of best-selling books on AI, machine learning, and algorithms.

Kaggle, the most well-known data science competition website, attracts millions of data lovers from around the world. Participating in Kaggle competitions is a proven way to enhance your data analysis skills, network with an incredible community of data scientists, and acquire significant experience to help you advance in your profession.

The Kaggle Book is the first book of its kind, bringing together all of the tools and abilities you'll need to succeed in contests, data science projects, and beyond. Two Kaggle Grandmasters take you through modeling tactics you won't find anywhere else, as well as the knowledge they've gained along the road. You'll learn more broad approaches for approaching projects based on picture, tabular, textual, and reinforcement learning, in addition to Kaggle-specific suggestions. You'll be able to create better validation schemes and operate more comfortable with various evaluation criteria.

The Kaggle Book is for you if you want to climb the Kaggle ranks, learn more about data science, or enhance the accuracy of your existing models.

What you will discover:

• Learn about Kaggle as a competitive platform.
• Utilize Kaggle Notebooks, Datasets, and Discussion Forums to their full potential.
• To advance in your job, create a portfolio of work and ideas.
• Create systems for k-fold and probabilistic validation.
• Learn about popular and never-before-seen evaluation metrics.
• Recognize binary and multi-class classification, as well as object detection
• Improve your approach to NLP and time series tasks.
• On Kaggle, you can compete in simulation and optimization competitions.

This book is appropriate for anyone new to Kaggle, as well as experienced users. This book will be valuable for data analysts/scientists who want to improve their Kaggle scores and land jobs with tech behemoths. This book will be more useful if you have a basic understanding of machine learning ideas.

Author: Konrad Banachewicz and Luca Massaron

Link to buy: https://www.amazon.com/Data-Analysis-Machine-Learning-Kaggle/dp/1801817472/

Ratings: 4.5 out of 5 stars (from 40 reviews)

Best Sellers Rank: #60,443 in Books

#4 in Biostatistics (Books)

#8 in Natural Language Processing (Books)

GraphPad Software, Inc.'s CEO and Founder is Harvey Motulsky. While on the faculty of the Department of Pharmacology at the University of California, San Diego, he wrote the first edition of this text.

Intuitive Biostatistics approaches statistics in a non-technical, non-quantitative manner, emphasizing interpretation of statistical results rather than computing methodologies for creating statistical data. This makes the book especially valuable for people in the health sciences who have never taken a biostatistics course. The text is also a valuable resource for laboratory personnel, serving as a theoretically focused and approachable biostatistics guide. Intuitive Biostatistics, with its engaging and conversational tone, provides a basic introduction to statistics for undergraduate and graduate students, as well as a statistics refresher for working scientists.

Amon gthe best books on biostatistics, Intuitive Biostatistics explains statistical ideas and practical data analysis concerns in layman's terms. The textbook assists the reader in understanding the principles as well as the dangers of data presentation and analysis. It should be on the'must-read' list of clinicians, journal reviewers, editors, and other scientific literature consumers.

Author: Harvey Motulsky

Link to buy: https://www.amazon.com/Intuitive-Biostatistics-Nonmathematical-Statistical-Thinking/dp/0190643560/

Ratings: 4.5 out of 5 stars (from 135 reviews)

Best Sellers Rank: #74,108 in Books

#5 in Biostatistics (Books)

#31 in Medical Research (Books)

Jerrold H. Zar graduated from Northern Illinois University in 1962 with a bachelor's degree in biological sciences. Later, he received his M.S. and Ph.D. in biology and zoology from the University of Illinois at Urbana-Champaign. Zar then returned to Northern Illinois University for the next 34 years, serving in a number of roles. Zar is a member of 17 professional scientific groups, including the American Association for the Advancement of Science, of which he is an elected fellow. His numerous scientific publications cover a wide range of themes, from statistical analysis to animal physiological responses to their surroundings.

Zar's Biostatistical Analysis, Fifth Edition is an excellent textbook for graduate and undergraduate students looking for hands-on covering of statistical analysis methods used by researchers to collect, summarize, evaluate, and draw conclusions from biological research. This best-selling textbook's current edition is both thorough and easy to read. It is appropriate for both beginner students and as a complete reference book for biological researchers and advanced students.

Biostatistical Analysis is suitable for a one- or two-semester, junior or graduate-level course in biostatistics, biometry, quantitative biology, or statistics, and requires algebra as a prerequisite.

Author: Jerrold Zar

Link to buy: https://www.amazon.com/gp/aw/d/0131008463/

Ratings: 4.1 out of 5 stars (from 84 reviews)

Best Sellers Rank: #84,035 in Books

#6 in Biostatistics (Books)

#49 in Biology (Books)

Designing Clinical Research has established the standard as the most practical, authoritative reference for physicians, nurses, pharmacists, and other practitioners working in all types of clinical and public health research for more than 30 years. Drs. Warren S. Browner, Thomas B. Newman, Steven R. Cummings, Deborah G. Grady, Alison J. Huang, Alka M. Kanaya, and Mark J. Pletcher, all of the University of California, San Francisco, provide up-to-date, commonsense approaches to the difficult judgments involved in designing, funding, and implementing a study in a reader-friendly writing style. To bring you up to speed, the fifth edition has new figures, tables, and design, as well as new editors, new information, and completely updated references.

Clinical research in its various forms, such as clinical trials, observational studies, translational science, and patient-oriented research, are all included.

In a practical and reader-friendly manner, Designing Clinical Research presents epidemiologic terms and principles, as well as advanced conceptual content. The book is one of the best books on biostatistics.

Confounding and directed acyclic graphs, surrogate outcomes and biomarkers, instrumental variables and Mendelian randomization, regression discontinuity designs, alternative data sources, AI and machine learning, pilot studies, and an update on P values and Bayesian analysis are all discussed.

Pre/post, interrupted time series, difference-in-differences, stepped wedge, and cluster randomized designs are all covered, as well as randomized trials in health systems.

New chapters on qualitative methods to clinical research and community-engaged research are included.

Author: Deborah Grady, Thomas B Newman MD MPH, etc

Link to buy: https://www.amazon.com/Designing-Clinical-Research-Warren-Browner/dp/1975174402/

Best Sellers Rank: #88,160 in Books

#7 in Biostatistics (Books)

#10 in Epidemiology (Books)

Geoff Cumming is a retired La Trobe University professor who has taught statistics for over 40 years. Robert Calin-Jageman is a psychology professor and the neuroscience program director at Dominican University, where he has taught and mentored undergraduate students for the past nine years.

Introduction to the New Statistics is the first introductory statistics textbook to begin with an estimating technique to assist readers comprehend effect sizes, confidence intervals (CIs), and meta-analysis ('the new statistics'). It is also the first literature to discuss the exciting new Open Science techniques that stimulate replication and improve study reliability. Furthermore, the book extensively discusses NHST so that students may understand published findings. Throughout, numerous real-world study cases are used. To increase users' understanding of statistics and modern research methods, the book employs today's most successful learning tools and promotes critical thinking, comprehension, and retention. The free ESCI (Exploratory Software for Confidence Intervals) software visualizes topics and allows for calculation and graphing. The book is suitable for usage with or without ESCI.

Other noteworthy features include:

• Discussion of estimate and NHST techniques, as well as how to simply transfer between the two.
• For the greatest understanding of estimate methods, several activities employ ESCI to analyze data and create graphs with CIs.
• Videos of the authors explaining essential ideas and showing ESCI use are a compelling learning tool for regular or flipped courses.
• In-chapter exercises and quizzes with accompanying comments enable students to learn by doing and track their progress.
• End-of-chapter tasks and comments, many of which use real-world data, provide practice in using the new statistics to assess data and using research judgment in practical circumstances.
• Don't fool yourself recommendations assist pupils in avoiding typical blunders.
• Red Flags highlight the definition of "significance" and the implications of p values.
• At exam time, chapter outlines, defined key phrases, sidebars with essential topics, and summarized take-home messages serve as a study tool.
  

Researchers interested in comprehending the new statistics will benefit from Introduction to the New Statistics, which is intended for introduction to statistics, data analysis, or quantitative methods courses in psychology, education, and other social and health sciences. There is no assumption of prior knowledge of introductory statistics.

Author: Geoff Cumming and Robert Calin-Jageman

Link to buy: https://www.amazon.com/Introduction-New-Statistics-Estimation-Science/dp/1138825522/

Ratings: 4.5 out of 5 stars (from 37 reviews)

Best Sellers Rank: #97,925 in Books

#8 in Biostatistics (Books)

#61 in Business Statistics

Frank S. David, MD, PhD, is the founder and managing director of the biotech consultancy Pharmagellan, where he assists firms and investors in unlocking the financial and strategic potential of creative R&D.

If you work in or around biotech, you should be familiar with clinical trial findings. But what if you don't have any experience with research design or biostatistics? When confronted with a journal article, press release, or investor presentation, you may feel out of your element.

Among the best books on biostatistics, The Pharmagellan Guide to Analyzing Biotech Clinical Trials is a thorough primer designed to assist non-experts in evaluating clinical trials of novel treatments.

• A structured path for evaluating the primary components of a biotech study that is either planned or finished.
• Over 100 real-world examples are used to demonstrate clear explanations of the most popular ideas and words in clinical trials.
• P values, sample size calculations, and Kaplan-Meier curves are all covered in depth in plain English for non-statisticians.
• Tips on assessing positive and negative outcomes, comprehending popular figures and tables, and spotting red flags in press releases.

If you are a biotech executive, investor, adviser, or entrepreneur, or aspire to be one, this manual will provide you with the foundation you need to confidently interpret clinical trials.

Author: Frank S. David MD PhD

Link to buy: https://www.amazon.com/Pharmagellan-Analyzing-Biotech-Clinical-Trials/dp/0998407526/

Ratings: 4.5 out of 5 stars (from 16 reviews)

Best Sellers Rank: #105,479 in Books

#9 in Biostatistics (Books)

#37 in Pharmaceutical & Biotechnology Industry (Books)

Ramona Nelson PhD, BC-RN, ANEF, FAAN graduated from Duquesne University with a baccalaureate degree in nursing and a master's degree in both nursing and information science, as well as a PhD in education. Ramona was Professor and Chair of the Department of Nursing at Slippery Rock University prior to her current role as president of her own consulting firm.

Awarded second place in the Information Technology category in the 2017 AJN Book of the Year Awards. Discover how information technology and health care connect! The second edition of Health Informatics: An Interprofessional Approach prepares you for success in today's technologically advanced healthcare practice. Comprehensive coverage encompasses electronic health records, clinical decision support, telehealth, ePatients, and social media technologies, as well as system deployment. Topics new to this edition include data science and analytics, mHealth, project management principles, and contract negotiations. This edition, written by professional informatics educators Ramona Nelson and Nancy Staggers, expands on the book that was named American Journal of Nursing Book of the Year in 2013!

Author: Ramona Nelson and Nancy Staggers

Link to buy: https://www.amazon.com/Health-Informatics-Ramona-Nelson-RN-BC/dp/0323402313/

Ratings: 4.5 out of 5 stars (from 543 reviews)

Best Sellers Rank: #109,031 in Books

#10 in Biostatistics (Books)

#28 in Medical Informatics (Books)

Nicholas J. Gotelli is a Professor of Biology at the University of Vermont. He received his B.A. in 1980 from the University of California, Berkeley, and his Ph.D. in 1985 from Florida State University. He also wrote Null Models in Ecology (with Gary R. Graves; 1996), A Field Guide to the Ants of New England (with Aaron M. Ellison, Elizabeth J. Farnsworth, and Gary D. Alpert; 2012), and EcoSim, an ecological software tool.

Aaron M. Ellison is a Senior Research Fellow in Ecology at the Harvard Forest and an Adjunct Professor at the University of Massachusetts at Amherst's Graduate Program in Organismic and Evolutionary Biology.

A Primer of Ecological Statistics, Second Edition, is a primer for ecologists and environmental scientists on probability theory, experimental design, and parameter estimates. The book focuses on a broad introduction to probability theory as well as a detailed examination of specific designs and analyses used in ecology and environmental science. The Primer is suitable for use as a stand-alone or supplementary text for upper-division undergraduate or graduate courses in ecological and environmental statistics, ecology, environmental science, environmental studies, or experimental design. It is also useful for environmental professionals who must use and interpret statistics on a daily basis but have little or no formal training in the subject.

The novel is broken into four sections. Part I covers the basics of probability and statistical thinking. It describes common statistical distributions used in ecology (Chapter 2) and important measures of central tendency and spread (Chapter 3), explains P-values, hypothesis testing, and statistical errors (Chapter 4), and introduces frequentist, Bayesian, and Monte Carlo methods of analysis (Chapter 5).

Part II addresses how to develop and carry out successful field experiments and sampling investigations. Design strategies (Chapter 6), a "bestiary" of experimental designs (Chapter 7), and transformations and data management are among the topics covered (Chapter 8).

Part III explores specific analyses and covers the content included in the majority of statistics textbooks. Regression (Chapter 9), analysis of variance (Chapter 10), categorical data analysis (Chapter 11), and multivariate analysis are all covered (Chapter 12).

Part IV, which is new to this version, covers two critical themes in estimating essential ecological parameters. Quantification of biological variety (Chapter 13) and calculating occupancy, detection probability, and population sizes from marked and unmarked populations are among the topics covered (Chapter 14).

A complete vocabulary, a mathematical appendix on matrix algebra, and extensively annotated tables and illustrations are included in the book. Footnotes introduce advanced and auxiliary material: some are essentially historical, some provide mathematical/statistical proofs or details, and still others address current ecological literature problems. The book is considered one of the best books on biostatistics.

Author: Nicholas J. Gotelli and Aaron M. Ellison

Link to buy: https://www.amazon.com/Primer-Ecological-Statistics-Nicholas-Gotelli/dp/1605350648/

Ratings: 4.4 out of 5 stars (from 59 reviews)

Best Sellers Rank: #197,714 in Books

#17 in Ecology (Books)

#18 in Biostatistics (Books)