Basic Probability Theory (Dover Books on Mathematics)

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Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information. This book builds theoretical statistics from the first principles of probability theory.

Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. Intended for first-year graduate students, this book can be used for students majoring in statistics who have a solid mathematics background.

It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations. Drawing upon over 40 years of experience, the authors of Statistics, 10th Edition provide business professionals with a clear and methodical approach to essential statistical procedures.

A Graduate Course in Probability (Dover Books on Mathematics) - Harvard Book Store

The text clearly explains the basic concepts and procedures of descriptive and inferential statistical analysis. It features an emphasis on expressions involving sums of squares and degrees of freedom as well as a strong stress on the importance of variability. This accessible approach will help business professionals tackle such perennially mystifying topics as the standard deviation, variance interpretation of the correlation coefficient, hypothesis tests, degrees of freedom, p-values, and estimates of effect size.

But statistical analysis is tricky to get right, even for the best and brightest of us. 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. This is the hardcover format of Statistics For Dummies, 2nd Edition. The fun and easy way to get down to business with statistics Stymied by statistics? No fear? Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more.

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Statistics in a Nutshell is a clear and concise introduction and reference for anyone new to the subject. Thoroughly revised and expanded, this edition helps you gain a solid understanding of statistics without the numbing complexity of many college texts. Each chapter presents easy-to-follow descriptions, along with graphics, formulas, solved examples, and hands-on exercises. If you want to perform common statistical analyses and learn a wide range of techniques without getting in over your head, this is your book.

Aimed at high school and college students who need to take statistics to fulfill a degree requirement, this book follows a standard statistics curriculum with topics that include frequency distributions, probability, binomial distribution, poisson distribution, normal distribution, hypothesis testing, simple regression analysis, and more. Drawing on his experience as a medical researcher, Vickers blends insightful explanations and humor, with minimal math, to help readers understand and interpret the statistics they read every day. The Cartoon Guide to Statistics covers all the central ideas of modern statistics: the summary and display of data, probability in gambling and medicine, random variables, Bernoulli Trials, the Central Limit Theorem, hypothesis testing, confidence interval estimation, and much more—all explained in simple, clear, and yes, funny illustrations.

Never again will you order the Poisson Distribution in a French restaurant!

  • An Authors Nightmare.
  • Introduction to Probability?
  • Nonlinear Fracture Mechanics for Engineers.

How can we catch schools that cheat on standardized tests? What is causing the rising incidence of autism?

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As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more. For those who slept through Stats , this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.

Head First Statistics brings this typically dry subject to life, teaching you everything you want and need to know about statistics through engaging, interactive, and thought-provoking material, full of puzzles, stories, quizzes, visual aids, and real-world examples. There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis tractable and accessible to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS, is for first year graduate students or advanced undergraduates and provides an accessible approach, as all mathematics is explained intuitively and with concrete examples.

Unlike other textbooks, this book begins with the basics, including essential concepts of probability and random sampling. The book gradually climbs all the way to advanced hierarchical modeling methods for realistic data. The text provides complete examples with the R programming language and BUGS software both freeware , and begins with basic programming examples, working up gradually to complete programs for complex analyses and presentation graphics.

These templates can be easily adapted for a large variety of students and their own research needs. The textbook bridges the students from their undergraduate training into modern Bayesian methods. This introductory textbook provides an inexpensive, brief overview of statistics to help readers gain a better understanding of how statistics work and how to interpret them correctly. Each chapter describes a different statistical technique, ranging from basic concepts like central tendency and describing distributions to more advanced concepts such as t tests, regression, repeated measures ANOVA, and factor analysis.

Each chapter begins with a short description of the statistic and when it should be used. This is followed by a more in-depth explanation of how the statistic works. Finally, each chapter ends with an example of the statistic in use, and a sample of how the results of analyses using the statistic might be written up for publication. A glossary of statistical terms and symbols is also included. Renowned for its clear prose and no-nonsense emphasis on core concepts, Statistics covers fundamentals using real examples to illustrate the techniques. Polk October 6, Facebook Twitter Instagram Pinterest.

Titles Appear On 1 List Each. A Course in Probability Theory. Big Data Made Simple. Peter L. Analysis and Adjustment of Survey Measurements. Mikhail E. Antifragile: Things That Gain from Disorder. Nassim Nicholas Taleb. Applied Multivariate Statistical Analysis. Richard A. Applied Predictive Modeling. Applied Statistics and Probability for Engineers.

Douglas C.

Martin Sternstein Ph. Wall Street Mojo. Flashlight Worthy. Bayesian Data Analysis. Robert Sedgewick. Business Statistics — 5th Edition-.

Basic Probability Theory (Dover Books on Mathematics)

Douglas Downing Ph. Calculus Made Easy. Thompson, Gardner. Causality: Models, Reasoning, and Inference. Choice and Chance. CliffsQuickReview Statistics. David H. Voelker, Peter Z. Orton, Scott Adams.

Contributions to a General Asymptotik Statistical Theory. Pfanzagl Wefelmeyer. Data Analysis with Open Source Tools. Data Analysis: a Bayesian Tutorial. Dataclysm: Who We Are. Christian Rudder.

Basic Probability Theory

Elements of Statistical Learning. Hastie, Tibshirani. Envisioning Information. Essentials of Statistics for Business and Economics. David R. Anderson, Dennis J. Sweeney and Thomas A. Experimental Design for Biologists. Fifty Challenging Problems in Probability with Solutions. Frederick Mosteller. First Course in Probability. Steven D. How animals work.

Knut Schmidt-Nielsen.