This book is about helping you to choose and use the right statistical technique to analyze your data and write about your results and findings convincingly. It provides a guide to the essential statistical skills needed for success in your assignment, project or dissertation. Berman Brown and Saunders concentrate on particular statistical tests and their three Ws--what, why, and when. They provide you with the tools to choose the graphs and statistics that are suitable for your data, and to understand what the statistical results actually mean. In addition, the book explains why it is impossible to avoid using statistics in analysing data; describes the language of statistics to make it easier to understand the various terms used for statistical techniques; deals with using tables and charts to present data so that they are easy to understand; and explains the statistics used to describe data used to inferdifferences and relationships. The book also includes a handy alphabet of statistics as well as a glossary of key statistical terms. --From publisher's description.
A Guide to the Use of Statistical Methods in the Physical Sciences
Author: R. J. Barlow
Publisher: John Wiley & Sons
The Manchester Physics Series General Editors: D. J. Sandiford; F.Mandl; A. C. Phillips Department of Physics and Astronomy,University of Manchester Properties of Matter B. H. Flowers and E.Mendoza Optics Second Edition F. G. Smith and J. H. ThomsonStatistical Physics Second Edition F. Mandl Electromagnetism SecondEdition I. S. Grant and W. R. Phillips Statistics R. J. BarlowSolid State Physics Second Edition J. R. Hook and H. E. HallQuantum Mechanics F. Mandl Particle Physics Second Edition B. R.Martin and G. Shaw The Physics of Stars Second Edition A.C.Phillips Computing for Scientists R. J. Barlow and A. R. BarnettWritten by a physicist, Statistics is tailored to the needs ofphysical scientists, containing and explaining all they need toknow. It concentrates on parameter estimation, especially themethods of Least Squares and Maximum Likelihood, but othertechniques, such as hypothesis testing, Bayesian statistics andnon-parametric methods are also included. Intended for reasonablynumerate scientists it contains all the basic formulae, theirderivations and applications, together with some more advancedones. Statistics features: * Comprehensive coverage of the essential techniques physicalscientists are likely to need. * A wealth of examples, and problems with their answers. * Flexible structure and organisation allows it to be used as acourse text and a reference. * A review of the basics, so that little prior knowledge isrequired.
In 1946 Paul Halmos studied unbiased estimators of minimum variance, and planted the seed from which the subject matter of the present monograph sprang. The author has undertaken to provide experts and advanced students with a review of the present status of the evolved theory of U-statistics, and
Statistics For Dummies, 2nd Edition (9780470911082) is now being published as Statistics For Dummies, 2nd Edition (9781119293521). While this version features an older Dummies cover and design, the content is the same as the new release and should not be considered a different product. The fun and easy way to get down to business with statistics Stymied by statistics? No fear ? this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life. 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. Tracks to a typical first semester statistics course Updated examples resonate with today's students Explanations mirror teaching methods and classroom protocol Packed with practical advice and real-world problems, Statistics For Dummies gives you everything you need to analyze and interpret data for improved classroom or on-the-job performance.
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.
Concise description of classical statistics, from basic dice probabilities to modern regression analysis. Equal stress on theory and applications. Moderate difficulty; only basic calculus required. Includes problems with answers.
Including an Account of Its Natural, Civil, and Ecclesiastical History ; Together with a Particular Description of Each County, Notices of the Manners and Customs of Its Aboriginal Tribes, and a Correct Map of the State
This book has successfully taught introductory statistics to non-mathematicians who had previously failed two semester of statistics or had completed the courses with no idea of what they had done. It uses a statistical decision model that is easy to understand and apply. Each chapter leads the student through one stats test using Minitab. The book helps the student understand which stat to use and what the results mean to a business person.
"Head First Statistics" brings a typically difficult subject to life, teaching readers everything they 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.
Classic analysis of the foundations of statistics and development of personal probability, one of the greatest controversies in modern statistical thought. Revised edition. Calculus, probability, statistics, and Boolean algebra are recommended.
David Ray Anderson,Dennis J.. Sweeney,Thomas Arthur Williams
Author: David Ray Anderson,Dennis J.. Sweeney,Thomas Arthur Williams
Publisher: Cengage Learning
Category: Commercial statistics
Trust the latest version of this market-leading essentials text to introduce sound statistical methodology in a proven applications setting. FUNDAMENTALS OF BUSINESS STATISTICS, 6e, International Edition includes all of the strengths of the best-selling parent text, with a streamlined focus on the core topics and a concise presentation that is easy for students to follow.This reader-friendly introduction to business statistics offers a wealth of real-world examples, proven methods, and application exercises that clearly demonstrate how statistics can inform decisions and suggest solutions to contemporary business problems. The authors' signature problem-scenario approach and numerous exercises in every chapter show students how to apply statistical methods in practical business situations. In addition, the Sixth Edition includes new case problems, methods, applications, and self-test exercises to help students' master key formulas and apply their knowledge.Optional updated chapter appendices highlight Excel® 2007 and Minitab® 15 popular commercial software, giving you the choice of integrating or omitting computer coverage in your course. This edition's concise approach and comprehensive support package, now including CengageNOW course management system, provides everything you need for an effective statistics course that prepares students for the essentials of statistics success in business today.
Over Half a Million Copies Sold--an Honest-to-Goodness Bestseller Darrell Huff runs the gamut of every popularly used type of statistic, probes such things as the sample study, the tabulation method, the interview technique, or the way the results are derived from the figures, and points up the countless number of dodges which are used to full rather than to inform.
In this classic of statistical mathematical theory, Harald Cramér joins the two major lines of development in the field: while British and American statisticians were developing the science of statistical inference, French and Russian probabilitists transformed the classical calculus of probability into a rigorous and pure mathematical theory. The result of Cramér's work is a masterly exposition of the mathematical methods of modern statistics that set the standard that others have since sought to follow. For anyone with a working knowledge of undergraduate mathematics the book is self contained. The first part is an introduction to the fundamental concept of a distribution and of integration with respect to a distribution. The second part contains the general theory of random variables and probability distributions while the third is devoted to the theory of sampling, statistical estimation, and tests of significance.
This fully updated edition of Statistics for Research explains statistical concepts in a straight-forward and accessible way using practical examples from a variety of disciplines. If you're looking for an easy-to-read, comprehensive introduction to statistics with a guide to SPSS, this is the book for you! The new edition features: - Clear explanations of all the main techniques of statistical analysis - A brand new student-friendly, easy-to-navigate design - Even more step-by-step screenshots of SPSS commands and outputs - An extensive glossary of terms, ideal for those new to statistics - End of chapter exercises to help you put your learning into practice - A new, fully updated companion website (www.uk.sagepub.com/argyrous3) with comprehensive student and lecturer resources including additional, discipline specific examples and online readings and WebCT/Blackboard quizzes. This is the ideal textbook for any course in statistical methods across the health and social sciences and a perfect starter book for students, researchers and professionals alike.
Byron W. Brown,Byron Wm. Brown, Jr.,Myles Hollander
Author: Byron W. Brown,Byron Wm. Brown, Jr.,Myles Hollander
Publisher: John Wiley & Sons
Elementary rules of probability; Populations, samples, and the distribution of the sample mean; Analysis of matched pairs using sample means; Analysis of the two-sample location problem using sample means; Surveys and experiments in medical research; Statistical inference for dichotomous variables; Comparing two success probabilities; Chi-squared tests; Analysis of k-sample problems; Linear regression and correlation; Analysis of matched pairs using ranks; Analysis of the two-sample location problem using ranks; Methods for censored data.
Basic Statistics Covers A Wide Range Of Statistical Theory Taught In Almost All Faculties. Theory Followed By Relevant Formulae Is Fully Explicated Through Solved Numerical Problems. Mathematical Derivations And Proofs Of The Formulae Are Largely Absent. The Book Presupposes No Advance Knowledge Of Mathematics.Basic Statistics Fully Covers The Syllabi Of Statistics Courses Running In Various Universities In The Faculties Of Commerce, Arts, Master Of Business Management, Agriculture, Home Science, Pharmacy, And For Students Appearing In C.A. (P.E.-I), I.C.W.A. (Inter.), Etc. This Book Provides Exhaustive Matter In A Simple, Lucid And Exact Manner For Inquisitive Minds.Fourth Edition Of Basic Statistics Is Fully Revised And Enlarged. The Addition Of Two Chapters Entitled Research Processes And Experimental Research Designs Has Made The Book Complete In Its Own Sense. Variety Of Large Number Of Theory And Numerical Questions At The End Of Each Chapter Is A Boon To Achieve One S Own Goal. A Reader Will Find The Book Very Useful And Better Than His Expectations.
Traditional texts in mathematical statistics can seem - to some readers-heavily weighted with optimality theory of the various flavors developed in the 1940s and50s, and not particularly relevant to statistical practice. Mathematical Statistics stands apart from these treatments. While mathematically rigorous, its focus is on providing a set of useful tools that allow students to understand the theoretical underpinnings of statistical methodology. The author concentrates on inferential procedures within the framework of parametric models, but - acknowledging that models are often incorrectly specified - he also views estimation from a non-parametric perspective. Overall, Mathematical Statistics places greater emphasis on frequentist methodology than on Bayesian, but claims no particular superiority for that approach. It does emphasize, however, the utility of statistical and mathematical software packages, and includes several sections addressing computational issues. The result reaches beyond "nice" mathematics to provide a balanced, practical text that brings life and relevance to a subject so often perceived as irrelevant and dry.