Expect The Unexpected: A First Course In Biostatistics (Second Edition)

by Raluca Balan

Author	: Raluca Balan
Publisher	: World Scientific Publishing Company
Total Pages	: 315
Release	: 2017-05-25
Genre	: Medical
ISBN	: 9813209089

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This textbook introduces the basic concepts from probability theory and statistics which are needed for statistical analysis of data encountered in the biological and health sciences. No previous study is required. Advanced mathematical tools, such as integration and differentiation, are kept to a minimum. The emphasis is put on the examples. Probabilistic methods are discussed at length, but the focus of this edition is on statistics.The examples are kept simple, so that the reader can learn quickly and see the usefulness of various statistical and probabilistic methods. Some of the examples used in this book draw attention to various problems related to environmental issues, climate change, loss of bio-diversity, and their impact on wildlife and humans.In comparison with the first edition of the book, this second edition contains additional topics such as power, sample size computation and non-parametric methods, and includes a large collection of new problems, as well as the answers to odd-numbered problems. Several sections of this edition are accompanied by instructions using the programming language R for statistical computing and graphics.The Solution Manual is available upon request for all instructors who adopt this book as a course text. Please send your request to [email protected].

Expect the Unexpected

by Raluca Balan

Author	: Raluca Balan
Publisher	:
Total Pages	: 315
Release	: 2017
Genre	: Electronic books
ISBN	: 9789813209077

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The Book of R

by Tilman M. Davies

Author	: Tilman M. Davies
Publisher	: No Starch Press
Total Pages	: 833
Release	: 2016-07-16
Genre	: Computers
ISBN	: 1593276516

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The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.

Elementary Probability

by David Stirzaker

Author	: David Stirzaker
Publisher	: Cambridge University Press
Total Pages	: 540
Release	: 2003-08-18
Genre	: Mathematics
ISBN	: 1139441035

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Now available in a fully revised and updated second edition, this well established textbook provides a straightforward introduction to the theory of probability. The presentation is entertaining without any sacrifice of rigour; important notions are covered with the clarity that the subject demands. Topics covered include conditional probability, independence, discrete and continuous random variables, basic combinatorics, generating functions and limit theorems, and an introduction to Markov chains. The text is accessible to undergraduate students and provides numerous worked examples and exercises to help build the important skills necessary for problem solving.

OpenIntro Statistics

by David Diez

Author	: David Diez
Publisher	:
Total Pages	:
Release	: 2015-07-02
Genre	:
ISBN	: 9781943450046

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The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.

Information Theory, Inference and Learning Algorithms

by David J. C. MacKay

Author	: David J. C. MacKay
Publisher	: Cambridge University Press
Total Pages	: 694
Release	: 2003-09-25
Genre	: Computers
ISBN	: 9780521642989

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Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.

Why Nobody Believes the Numbers

by Al Lewis

Author	: Al Lewis
Publisher	: John Wiley & Sons
Total Pages	: 178
Release	: 2012-06-11
Genre	: Business & Economics
ISBN	: 1118332067

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Why Nobody Believes the Numbers introduces a unique viewpoint to population health outcomes measurement: Results/ROIs should be presented as they are, not as we wish they would be. This viewpoint contrasts sharply with vendor/promoter/consultant claims along two very important dimensions: (1) Why Nobody Believes presents outcomes/ROIs achievable right here on this very planet... (2) ...calculated using actual data rather than controlled substances. Indeed, nowhere in healthcare is it possible to find such sharply contrasting worldviews, methodologies, and grips on reality. Why Nobody Believes the Numbers includes 12 case studies of vendors, carriers, and consultants who were apparently playing hooky the day their teacher covered fifth-grade math, as told by an author whose argument style can be so persuasive that he was once able to convince a resort to sell him a timeshare. The book's lesson: no need to believe what your vendor tells you -- instead you can estimate your own savings using “ingredients you already have in your kitchen.” Don't be intimidated just because you lack a PhD in biostatistics, or even a Masters, Bachelor's, high-school equivalency diploma or up-to-date inspection sticker. Why Nobody Believes the Numbers explains how to determine if the ROIs are real...and why they usually aren't. You'll learn how to: Figure out whether you are "moving the needle" or just crediting a program with changes that would have happened anyway Judge whether the ROIs your vendors report are plausible or even arithmetically possible Synthesize all these insights into RFPs and contracts that truly hold vendors accountable for results

Principal Component Analysis

by I.T. Jolliffe

Author	: I.T. Jolliffe
Publisher	: Springer Science & Business Media
Total Pages	: 283
Release	: 2013-03-09
Genre	: Mathematics
ISBN	: 1475719043

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Principal component analysis is probably the oldest and best known of the It was first introduced by Pearson (1901), techniques ofmultivariate analysis. and developed independently by Hotelling (1933). Like many multivariate methods, it was not widely used until the advent of electronic computers, but it is now weIl entrenched in virtually every statistical computer package. The central idea of principal component analysis is to reduce the dimen sionality of a data set in which there are a large number of interrelated variables, while retaining as much as possible of the variation present in the data set. This reduction is achieved by transforming to a new set of variables, the principal components, which are uncorrelated, and which are ordered so that the first few retain most of the variation present in all of the original variables. Computation of the principal components reduces to the solution of an eigenvalue-eigenvector problem for a positive-semidefinite symmetrie matrix. Thus, the definition and computation of principal components are straightforward but, as will be seen, this apparently simple technique has a wide variety of different applications, as weIl as a number of different deri vations. Any feelings that principal component analysis is a narrow subject should soon be dispelled by the present book; indeed some quite broad topics which are related to principal component analysis receive no more than a brief mention in the final two chapters.

Statistics Done Wrong

by Alex Reinhart

Author	: Alex Reinhart
Publisher	: No Starch Press
Total Pages	: 177
Release	: 2015-03-01
Genre	: Mathematics
ISBN	: 1593276206

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Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: –Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan –How to think about p values, significance, insignificance, confidence intervals, and regression –Choosing the right sample size and avoiding false positives –Reporting your analysis and publishing your data and source code –Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong.