Book picks similar to
Fundamentals of Biostatistics (with CD-ROM) by Bernard Rosner
statistics
science
textbooks
non-fiction
Ecology: Concepts and Applications
Manuel C. Molles Jr. - 1999
An evolutionary perspective forms the foundation of the entire discussion. The book begins with the natural history of the planet, considers portions of the whole in the middle chapters, and ends with another perspective of the entire planet in the concluding chapter. Its unique organization of focusing only on several key concepts in each chapter sets it apart from the competition. .
Quantum Computation and Quantum Information
Michael A. Nielsen - 2000
A wealth of accompanying figures and exercises illustrate and develop the material in more depth. They describe what a quantum computer is, how it can be used to solve problems faster than familiar "classical" computers, and the real-world implementation of quantum computers. Their book concludes with an explanation of how quantum states can be used to perform remarkable feats of communication, and of how it is possible to protect quantum states against the effects of noise.
First Aid for the USMLE Step 2 CS
Tao Le - 2006
The top-selling CS review book written by students and IMGs who recently passed 100+ high-yield minicases by chief complaint 30 complete cases simulate the exam experience Contains new Patient Encounters, including telephone interviews Perfect for group or solo study YOUR COMPLETE CS SURVIVAL GUIDE FROM THE AUTHORS OF FIRST AID FOR THE USMLE STEP 1 INSIDER ADVICE FOR STEP 2 CS SUCCESS New miniguide shows US students and IMGs how best to use this book Revised by test veterans to reflect the 2005--2006 exam experience Each complete case features standardized patient checklists and a recommended clinical approach Minicases represent the major chief complaints and diagnoses seen on the Step 2 CS Proven strategies for the patient encounter and patient note High-yield, must-know facts on patient diagnosis and workup.
A Guide To Econometrics
Peter E. Kennedy - 1979
This overview has enabled students to make sense more easily of what instructors are doing when they produce proofs, theorems and formulas.
Planning, Implementing, and Evaluating Health Promotion Programs: A Primer
James F. McKenzie - 1992
The Fifth Edition features updated information throughout, including new theories and models such as the Healthy Action Process Approach (HAPA) and the Community Readiness Model (CRM), sections on grant writing and preparing a budget, real-life examples of marketing principles and processes, and a new classification system for evaluation approaches and designs. Health Education, Health Promotion, Health Educators, and Program Planning, Models for Program Planning in Health Promotion, Starting the Planning Process, Assessing Needs, Measurement, Measures, Measurement Instruments and Sampling, Mission Statement, Goals, and Objectives, Theories and Models Commonly Used for Health Promotion Interventions, Interventions, Community Organizing and Community Building, Identification and Allocation of Resources, Marketing: Making Sure Programs Respond to Wants and Needs of Consumers, Implementation: Strategies and Associated Concerns, Evaluation: An Overview, Evaluation Approaches and Designs, Data Analysis and Reporting. Intended for those interested in learning the basics of planning, implementing, and evaluating health promotion programs
Prescotts Microbiology
Joanne Willey - 2007
Because of this balance, "Microbiology" is appropriate for microbiology majors and mixed majors courses. The new authors have focused on readability, artwork, and the integration of several key themes (including evolution, ecology and diversity) throughout the text, making an already superior text even better.
Time Series Analysis
James Douglas Hamilton - 1994
This book synthesizes these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate text-book treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results.The book is intended to provide students and researchers with a self-contained survey of time series analysis. It starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.-- "Journal of Economics"
Principles of Genetics
D. Peter Snustad - 1997
This clear, concise look at the basic principles and concepts of genetics uses a human genetics perspective to discuss the methods and experiments upon which genetic principles are based, such as DNA replication.
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
Eric Siegel - 2013
Rather than a "how to" for hands-on techies, the book entices lay-readers and experts alike by covering new case studies and the latest state-of-the-art techniques.You have been predicted — by companies, governments, law enforcement, hospitals, and universities. Their computers say, "I knew you were going to do that!" These institutions are seizing upon the power to predict whether you're going to click, buy, lie, or die.Why? For good reason: predicting human behavior combats financial risk, fortifies healthcare, conquers spam, toughens crime fighting, and boosts sales.How? Prediction is powered by the world's most potent, booming unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn.Predictive analytics unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future — lifting a bit of the fog off our hazy view of tomorrow — means pay dirt.In this rich, entertaining primer, former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: -What type of mortgage risk Chase Bank predicted before the recession. -Predicting which people will drop out of school, cancel a subscription, or get divorced before they are even aware of it themselves. -Why early retirement decreases life expectancy and vegetarians miss fewer flights. -Five reasons why organizations predict death, including one health insurance company. -How U.S. Bank, European wireless carrier Telenor, and Obama's 2012 campaign calculated the way to most strongly influence each individual. -How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! -How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. -How judges and parole boards rely on crime-predicting computers to decide who stays in prison and who goes free. -What's predicted by the BBC, Citibank, ConEd, Facebook, Ford, Google, IBM, the IRS, Match.com, MTV, Netflix, Pandora, PayPal, Pfizer, and Wikipedia. A truly omnipresent science, predictive analytics affects everyone, every day. Although largely unseen, it drives millions of decisions, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate.Predictive analytics transcends human perception. This book's final chapter answers the riddle: What often happens to you that cannot be witnessed, and that you can't even be sure has happened afterward — but that can be predicted in advance?Whether you are a consumer of it — or consumed by it — get a handle on the power of Predictive Analytics.
Mindstorms: Children, Computers, And Powerful Ideas
Seymour Papert - 1980
We have Mindstorms to thank for that. In this book, pioneering computer scientist Seymour Papert uses the invention of LOGO, the first child-friendly programming language, to make the case for the value of teaching children with computers. Papert argues that children are more than capable of mastering computers, and that teaching computational processes like de-bugging in the classroom can change the way we learn everything else. He also shows that schools saturated with technology can actually improve socialization and interaction among students and between students and teachers.
Lippincott's Illustrated Reviews: Microbiology
Richard A. HarveyVictor Stollar - 2001
The book has the hallmark features for which Lippincott's Illustrated Reviews volumes are so popular: an outline format, over 600 full-color illustrations, end-of-chapter summaries, review questions, plus an entire section of clinical case studies with full-color illustrations. This edition's medical/clinical focus has been sharpened to provide a high-yield review. Five additional case studies have been included, bringing the total to nineteen. Review questions have been reformatted to comply with USMLE Step 1 style, with clinical vignettes.
Neuroscience
George J. Augustine - 1996
Created primarily for medical and premedical students, 'Neuroscience' emphasizes the structure of the nervous system, the correlation of structure and function, and the structure/function relationships particularly pertinent to the practice of medicine.
Probability and Statistics
Morris H. DeGroot - 1975
Other new features include a chapter on simulation, a section on Gibbs sampling, what you should know boxes at the end of each chapter, and remarks to highlight difficult concepts.
Bayes Theorem: A Visual Introduction For Beginners
Dan Morris - 2016
Bayesian statistics is taught in most first-year statistics classes across the nation, but there is one major problem that many students (and others who are interested in the theorem) face. The theorem is not intuitive for most people, and understanding how it works can be a challenge, especially because it is often taught without visual aids. In this guide, we unpack the various components of the theorem and provide a basic overview of how it works - and with illustrations to help. Three scenarios - the flu, breathalyzer tests, and peacekeeping - are used throughout the booklet to teach how problems involving Bayes Theorem can be approached and solved. Over 60 hand-drawn visuals are included throughout to help you work through each problem as you learn by example. The illustrations are simple, hand-drawn, and in black and white. For those interested, we have also included sections typically not found in other beginner guides to Bayes Rule. These include: A short tutorial on how to understand problem scenarios and find P(B), P(A), and P(B|A). For many people, knowing how to approach scenarios and break them apart can be daunting. In this booklet, we provide a quick step-by-step reference on how to confidently understand scenarios.A few examples of how to think like a Bayesian in everyday life. Bayes Rule might seem somewhat abstract, but it can be applied to many areas of life and help you make better decisions. It is a great tool that can help you with critical thinking, problem-solving, and dealing with the gray areas of life. A concise history of Bayes Rule. Bayes Theorem has a fascinating 200+ year history, and we have summed it up for you in this booklet. From its discovery in the 1700’s to its being used to break the German’s Enigma Code during World War 2, its tale is quite phenomenal.Fascinating real-life stories on how Bayes formula is used in everyday life.From search and rescue to spam filtering and driverless cars, Bayes is used in many areas of modern day life. We have summed up 3 examples for you and provided an example of how Bayes could be used.An expanded definitions, notations, and proof section.We have included an expanded definitions and notations sections at the end of the booklet. In this section we define core terms more concretely, and also cover additional terms you might be confused about. A recommended readings section.From The Theory That Would Not Die to a few other books, there are a number of recommendations we have for further reading. Take a look! If you are a visual learner and like to learn by example, this intuitive booklet might be a good fit for you. Bayesian statistics is an incredibly fascinating topic and likely touches your life every single day. It is a very important tool that is used in data analysis throughout a wide-range of industries - so take an easy dive into the theorem for yourself with a visual approach!If you are looking for a short beginners guide packed with visual examples, this booklet is for you.