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Author: William E. Magnusson Publisher: Sinauer Associates Incorporated ISBN: 9780878935062 Category : Science Languages : en Pages : 136
Book Description
Statistics without Math is not your typical statistics book; nor is it designed to serve as a substitute for conventional statistical texts. Experience with ecology students and researchers has shown that too much mathematical detail diverts attention away from basic logical concepts, resulting in errors in sampling design, data analysis, and comprehension of the ecological literature. Hence, this book starts with real-world observations and explains how statistics may be used as a practical tool to answer questions about them, and to clearly communicate these results. The book targets intermediate-level statistics (given short shrift in most books and courses), and teaches concepts with a minimum of mathematical detail, instead using simple graphs and, where necessary, analogy. This approach, class-tested for many years by the authors, has revolutionized students' ability to understand statistics.
Author: William E. Magnusson Publisher: Sinauer Associates Incorporated ISBN: 9780878935062 Category : Science Languages : en Pages : 136
Book Description
Statistics without Math is not your typical statistics book; nor is it designed to serve as a substitute for conventional statistical texts. Experience with ecology students and researchers has shown that too much mathematical detail diverts attention away from basic logical concepts, resulting in errors in sampling design, data analysis, and comprehension of the ecological literature. Hence, this book starts with real-world observations and explains how statistics may be used as a practical tool to answer questions about them, and to clearly communicate these results. The book targets intermediate-level statistics (given short shrift in most books and courses), and teaches concepts with a minimum of mathematical detail, instead using simple graphs and, where necessary, analogy. This approach, class-tested for many years by the authors, has revolutionized students' ability to understand statistics.
Author: Christine P. Dancey Publisher: Pearson Education ISBN: 9780131249417 Category : Computers Languages : en Pages : 644
Book Description
'Statistics Without Maths for Psychology' provides an accessible description of key statistical concepts and techniques needed by psychology students, avoiding as much maths as possible.
Author: David J. Bartholomew Publisher: SAGE ISBN: 1473934338 Category : Social Science Languages : en Pages : 193
Book Description
This is a book about the ideas that drive statistics. It is an ideal primer for students who need an introduction to the concepts of statistics without the added confusion of technical jargon and mathematical language. It introduces the intuitive thinking behind standard procedures, explores the process of informal reasoning, and uses conceptual frameworks to provide a foundation for students new to statistics. It showcases the expertise we have all developed from living in a data saturated society, increases our statistical literacy and gives us the tools needed to approach statistical mathematics with confidence. Key topics include: Variability Standard Distributions Correlation Relationship Sampling Inference An engaging, informal introduction this book sets out the conceptual tools required by anyone undertaking statistical procedures for the first time or for anyone needing a fresh perspective whilst studying the work of others.
Author: Larry Wasserman Publisher: Springer Science & Business Media ISBN: 0387217363 Category : Mathematics Languages : en Pages : 446
Book Description
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Author: Will Kurt Publisher: No Starch Press ISBN: 1593279566 Category : Mathematics Languages : en Pages : 258
Book Description
Fun guide to learning Bayesian statistics and probability through unusual and illustrative examples. Probability and statistics are increasingly important in a huge range of professions. But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that. This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples. By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to: - How to measure your own level of uncertainty in a conclusion or belief - Calculate Bayes theorem and understand what it's useful for - Find the posterior, likelihood, and prior to check the accuracy of your conclusions - Calculate distributions to see the range of your data - Compare hypotheses and draw reliable conclusions from them Next time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.
Author: Christine Dancey Publisher: SAGE ISBN: 1446291235 Category : Social Science Languages : en Pages : 584
Book Description
Statistics for the Health Sciences is a highly readable and accessible textbook on understanding statistics for the health sciences, both conceptually and via the SPSS programme. The authors give clear explanations of the concepts underlying statistical analyses and descriptions of how these analyses are applied in health science research without complex maths formulae. The textbook takes students from the basics of research design, hypothesis testing and descriptive statistical techniques through to more advanced inferential statistical tests that health science students are likely to encounter. The strengths and weaknesses of different techniques are critically appraised throughout, and the authors emphasise how they may be used both in research and to inform best practice care in health settings. Exercises and tips throughout the book allow students to practice using SPSS. The companion website provides further practical experience of conducting statistical analyses. Features include: • multiple choice questions for both student and lecturer use • full Powerpoint slides for lecturers • practical exercises using SPSS • additional practical exercises using SAS and R This is an essential textbook for students studying beginner and intermediate level statistics across the health sciences.
Author: Jordan Ellenberg Publisher: Penguin ISBN: 0143127535 Category : Mathematics Languages : en Pages : 482
Book Description
“Witty, compelling, and just plain fun to read . . ." —Evelyn Lamb, Scientific American The Freakonomics of math—a math-world superstar unveils the hidden beauty and logic of the world and puts its power in our hands The math we learn in school can seem like a dull set of rules, laid down by the ancients and not to be questioned. In How Not to Be Wrong, Jordan Ellenberg shows us how terribly limiting this view is: Math isn’t confined to abstract incidents that never occur in real life, but rather touches everything we do—the whole world is shot through with it. Math allows us to see the hidden structures underneath the messy and chaotic surface of our world. It’s a science of not being wrong, hammered out by centuries of hard work and argument. Armed with the tools of mathematics, we can see through to the true meaning of information we take for granted: How early should you get to the airport? What does “public opinion” really represent? Why do tall parents have shorter children? Who really won Florida in 2000? And how likely are you, really, to develop cancer? How Not to Be Wrong presents the surprising revelations behind all of these questions and many more, using the mathematician’s method of analyzing life and exposing the hard-won insights of the academic community to the layman—minus the jargon. Ellenberg chases mathematical threads through a vast range of time and space, from the everyday to the cosmic, encountering, among other things, baseball, Reaganomics, daring lottery schemes, Voltaire, the replicability crisis in psychology, Italian Renaissance painting, artificial languages, the development of non-Euclidean geometry, the coming obesity apocalypse, Antonin Scalia’s views on crime and punishment, the psychology of slime molds, what Facebook can and can’t figure out about you, and the existence of God. Ellenberg pulls from history as well as from the latest theoretical developments to provide those not trained in math with the knowledge they need. Math, as Ellenberg says, is “an atomic-powered prosthesis that you attach to your common sense, vastly multiplying its reach and strength.” With the tools of mathematics in hand, you can understand the world in a deeper, more meaningful way. How Not to Be Wrong will show you how.
Author: Robert W. Keener Publisher: Springer Science & Business Media ISBN: 0387938397 Category : Mathematics Languages : en Pages : 538
Book Description
Intended as the text for a sequence of advanced courses, this book covers major topics in theoretical statistics in a concise and rigorous fashion. The discussion assumes a background in advanced calculus, linear algebra, probability, and some analysis and topology. Measure theory is used, but the notation and basic results needed are presented in an initial chapter on probability, so prior knowledge of these topics is not essential. The presentation is designed to expose students to as many of the central ideas and topics in the discipline as possible, balancing various approaches to inference as well as exact, numerical, and large sample methods. Moving beyond more standard material, the book includes chapters introducing bootstrap methods, nonparametric regression, equivariant estimation, empirical Bayes, and sequential design and analysis. The book has a rich collection of exercises. Several of them illustrate how the theory developed in the book may be used in various applications. Solutions to many of the exercises are included in an appendix.
Author: William E. Magnusson
Author: William E. Magnusson
Author: Christine P. Dancey
Author: David J. Bartholomew
Author: Larry Wasserman
Author: Will Kurt
Author: Christine Dancey
Author: Jordan Ellenberg
Author: Robert W. Keener
Author: Derek Rowntree
Author: Marty Sapp