An Introduction To Contemporary Statistics

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Applying Contemporary Statistical Techniques

Author : Rand R. Wilcox
Publisher : Gulf Professional Publishing
ISBN 13 : 9780127515410
Total Pages : 688 pages
Book Rating : 4.5/5 (154 download)

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Book Synopsis Applying Contemporary Statistical Techniques by : Rand R. Wilcox

Download or read book Applying Contemporary Statistical Techniques written by Rand R. Wilcox and published by Gulf Professional Publishing. This book was released on 2003-01-06 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applying Contemporary Statistical Techniques explains why traditional statistical methods are often inadequate or outdated when applied to modern problems. Wilcox demonstrates how new and more powerful techniques address these problems far more effectively, making these modern robust methods understandable, practical, and easily accessible. Highlights: * Assumes no previous training in statistics * Explains when and why modern methods provide more accurate results * Provides simple descriptions of when and why conventional methods can be highly unsatisfactory * Covers the latest developments on multiple comparisons * Includes recent advances in risk-based methods * Features many illustrations and examples using data from real studies * Describes and illustrates easy-to-use s-plus functions for applying cutting-edge techniques "The book is quite unique in that it offers a lot of up-to-date statistical tools. No other book at this level comes close in this aspect." Xuming He -University of Illinois, Urbana

Modern Statistics with R

Author : Måns Thulin
Publisher :
ISBN 13 : 9781032497457
Total Pages : 0 pages
Book Rating : 4.4/5 (974 download)

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Book Synopsis Modern Statistics with R by : Måns Thulin

Download or read book Modern Statistics with R written by Måns Thulin and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. Modern Statistics with R introduces you to key parts of this modern statistical toolkit. It teaches you: Data wrangling - importing, formatting, reshaping, merging, and filtering data in R. Exploratory data analysis - using visualisations and multivariate techniques to explore datasets. Statistical inference - modern methods for testing hypotheses and computing confidence intervals. Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting. Simulation - using simulation techniques for sample size computations and evaluations of statistical methods. Ethics in statistics - ethical issues and good statistical practice. R programming - writing code that is fast, readable, and (hopefully!) free from bugs. No prior programming experience is necessary. Clear explanations and examples are provided to accommodate readers at all levels of familiarity with statistical principles and coding practices. A basic understanding of probability theory can enhance comprehension of certain concepts discussed within this book. In addition to plenty of examples, the book includes more than 200 exercises, with fully worked solutions available at: www.modernstatisticswithr.com.

OpenIntro Statistics

Author : David Diez
Publisher :
ISBN 13 : 9781943450046
Total Pages : pages
Book Rating : 4.4/5 (5 download)

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Book Synopsis OpenIntro Statistics by : David Diez

Download or read book OpenIntro Statistics written by David Diez and published by . This book was released on 2015-07-02 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Modern Statistics for Modern Biology

Author : SUSAN. HUBER HOLMES (WOLFGANG.)
Publisher : Cambridge University Press
ISBN 13 : 1108427022
Total Pages : 407 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Modern Statistics for Modern Biology by : SUSAN. HUBER HOLMES (WOLFGANG.)

Download or read book Modern Statistics for Modern Biology written by SUSAN. HUBER HOLMES (WOLFGANG.) and published by Cambridge University Press. This book was released on 2018 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt:

An Introduction to Statistical Learning

Author : Gareth James
Publisher : Springer Nature
ISBN 13 : 3031387473
Total Pages : 617 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis An Introduction to Statistical Learning by : Gareth James

Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

An Introduction to Contemporary Statistics

Author : Lambert Herman Koopmans
Publisher : Brooks/Cole
ISBN 13 :
Total Pages : 632 pages
Book Rating : 4.:/5 (319 download)

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Book Synopsis An Introduction to Contemporary Statistics by : Lambert Herman Koopmans

Download or read book An Introduction to Contemporary Statistics written by Lambert Herman Koopmans and published by Brooks/Cole. This book was released on 1981 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploratory statistics; Statistical inference - concepts and tools; Statistical inference - methodology.

Business Statistics for Contemporary Decision Making

Author : Ignacio Castillo
Publisher : John Wiley & Sons
ISBN 13 : 1119983223
Total Pages : 850 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Business Statistics for Contemporary Decision Making by : Ignacio Castillo

Download or read book Business Statistics for Contemporary Decision Making written by Ignacio Castillo and published by John Wiley & Sons. This book was released on 2023-05-08 with total page 850 pages. Available in PDF, EPUB and Kindle. Book excerpt: Show students why business statistics is an increasingly important business skill through a student-friendly pedagogy. In this fourth Canadian edition of Business Statistics For Contemporary Decision Making authors Ken Black, Tiffany Bayley, and Ignacio Castillo uses current real-world data to equip students with the business analytics techniques and quantitative decision-making skills required to make smart decisions in today's workplace.

Modern Mathematical Statistics with Applications

Author : Jay L. Devore
Publisher : Springer Nature
ISBN 13 : 3030551563
Total Pages : 981 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Modern Mathematical Statistics with Applications by : Jay L. Devore

Download or read book Modern Mathematical Statistics with Applications written by Jay L. Devore and published by Springer Nature. This book was released on 2021-04-29 with total page 981 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 3rd edition of Modern Mathematical Statistics with Applications tries to strike a balance between mathematical foundations and statistical practice. The book provides a clear and current exposition of statistical concepts and methodology, including many examples and exercises based on real data gleaned from publicly available sources. Here is a small but representative selection of scenarios for our examples and exercises based on information in recent articles: Use of the “Big Mac index” by the publication The Economist as a humorous way to compare product costs across nations Visualizing how the concentration of lead levels in cartridges varies for each of five brands of e-cigarettes Describing the distribution of grip size among surgeons and how it impacts their ability to use a particular brand of surgical stapler Estimating the true average odometer reading of used Porsche Boxsters listed for sale on www.cars.com Comparing head acceleration after impact when wearing a football helmet with acceleration without a helmet Investigating the relationship between body mass index and foot load while running The main focus of the book is on presenting and illustrating methods of inferential statistics used by investigators in a wide variety of disciplines, from actuarial science all the way to zoology. It begins with a chapter on descriptive statistics that immediately exposes the reader to the analysis of real data. The next six chapters develop the probability material that facilitates the transition from simply describing data to drawing formal conclusions based on inferential methodology. Point estimation, the use of statistical intervals, and hypothesis testing are the topics of the first three inferential chapters. The remainder of the book explores the use of these methods in a variety of more complex settings. This edition includes many new examples and exercises as well as an introduction to the simulation of events and probability distributions. There are more than 1300 exercises in the book, ranging from very straightforward to reasonably challenging. Many sections have been rewritten with the goal of streamlining and providing a more accessible exposition. Output from the most common statistical software packages is included wherever appropriate (a feature absent from virtually all other mathematical statistics textbooks). The authors hope that their enthusiasm for the theory and applicability of statistics to real world problems will encourage students to pursue more training in the discipline.

An Introduction to Statistical Genetic Data Analysis

Author : Melinda C. Mills
Publisher : MIT Press
ISBN 13 : 0262357445
Total Pages : 433 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis An Introduction to Statistical Genetic Data Analysis by : Melinda C. Mills

Download or read book An Introduction to Statistical Genetic Data Analysis written by Melinda C. Mills and published by MIT Press. This book was released on 2020-02-18 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to modern applied statistical genetic data analysis, accessible to those without a background in molecular biology or genetics. Human genetic research is now relevant beyond biology, epidemiology, and the medical sciences, with applications in such fields as psychology, psychiatry, statistics, demography, sociology, and economics. With advances in computing power, the availability of data, and new techniques, it is now possible to integrate large-scale molecular genetic information into research across a broad range of topics. This book offers the first comprehensive introduction to modern applied statistical genetic data analysis that covers theory, data preparation, and analysis of molecular genetic data, with hands-on computer exercises. It is accessible to students and researchers in any empirically oriented medical, biological, or social science discipline; a background in molecular biology or genetics is not required. The book first provides foundations for statistical genetic data analysis, including a survey of fundamental concepts, primers on statistics and human evolution, and an introduction to polygenic scores. It then covers the practicalities of working with genetic data, discussing such topics as analytical challenges and data management. Finally, the book presents applications and advanced topics, including polygenic score and gene-environment interaction applications, Mendelian Randomization and instrumental variables, and ethical issues. The software and data used in the book are freely available and can be found on the book's website.

Introduction to Statistical Physics

Author : Silvio Salinas
Publisher : Springer Science & Business Media
ISBN 13 : 9780387951195
Total Pages : 400 pages
Book Rating : 4.9/5 (511 download)

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Book Synopsis Introduction to Statistical Physics by : Silvio Salinas

Download or read book Introduction to Statistical Physics written by Silvio Salinas and published by Springer Science & Business Media. This book was released on 2001-02-08 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook covers the basic principles of statistical physics and thermodynamics. The text is pitched at the level equivalent to first-year graduate studies or advanced undergraduate studies. It presents the subject in a straightforward and lively manner. After reviewing the basic probability theory of classical thermodynamics, the author addresses the standard topics of statistical physics. The text demonstrates their relevance in other scientific fields using clear and explicit examples. Later chapters introduce phase transitions, critical phenomena and non-equilibrium phenomena.

Introductory Statistics

Author : Sheldon M. Ross
Publisher : Academic Press
ISBN 13 : 0080922104
Total Pages : 841 pages
Book Rating : 4.0/5 (89 download)

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Book Synopsis Introductory Statistics by : Sheldon M. Ross

Download or read book Introductory Statistics written by Sheldon M. Ross and published by Academic Press. This book was released on 2010-01-19 with total page 841 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introductory Statistics, Third Edition, presents statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also to understand why these procedures should be used. This book offers a unique historical perspective, profiling prominent statisticians and historical events in order to motivate learning. To help guide students towards independent learning, exercises and examples using real issues and real data (e.g., stock price models, health issues, gender issues, sports, scientific fraud) are provided. The chapters end with detailed reviews of important concepts and formulas, key terms, and definitions that are useful study tools. Data sets from text and exercise material are available for download in the text website. This text is designed for introductory non-calculus based statistics courses that are offered by mathematics and/or statistics departments to undergraduate students taking a semester course in basic Statistics or a year course in Probability and Statistics. - Unique historical perspective profiling prominent statisticians and historical events to motivate learning by providing interest and context - Use of exercises and examples helps guide the student towards indpendent learning using real issues and real data, e.g. stock price models, health issues, gender issues, sports, scientific fraud. - Summary/Key Terms- chapters end with detailed reviews of important concepts and formulas, key terms and definitions which are useful to students as study tools

Statistics: A Very Short Introduction

Author : David J. Hand
Publisher : Oxford University Press
ISBN 13 : 019923356X
Total Pages : 137 pages
Book Rating : 4.1/5 (992 download)

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Book Synopsis Statistics: A Very Short Introduction by : David J. Hand

Download or read book Statistics: A Very Short Introduction written by David J. Hand and published by Oxford University Press. This book was released on 2008-10-23 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics has evolved into an exciting discipline which uses deep theory and powerful software to shed light on the world around us: from clinical trials in medicine, to economics, sociology, and countless other subjects vital to understanding modern life. This Very Short Introduction explores and explains how statistics works today.

A Modern Introduction to Probability and Statistics

Author : F.M. Dekking
Publisher : Springer Science & Business Media
ISBN 13 : 1846281687
Total Pages : 485 pages
Book Rating : 4.8/5 (462 download)

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Book Synopsis A Modern Introduction to Probability and Statistics by : F.M. Dekking

Download or read book A Modern Introduction to Probability and Statistics written by F.M. Dekking and published by Springer Science & Business Media. This book was released on 2006-03-30 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books

Modern Data Science with R

Author : Benjamin S. Baumer
Publisher : CRC Press
ISBN 13 : 0429575394
Total Pages : 830 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Modern Data Science with R by : Benjamin S. Baumer

Download or read book Modern Data Science with R written by Benjamin S. Baumer and published by CRC Press. This book was released on 2021-03-31 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.

Online Statistics Education

Author : David M Lane
Publisher :
ISBN 13 : 9781687894250
Total Pages : 406 pages
Book Rating : 4.8/5 (942 download)

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Book Synopsis Online Statistics Education by : David M Lane

Download or read book Online Statistics Education written by David M Lane and published by . This book was released on 2014-12-02 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Online Statistics: An Interactive Multimedia Course of Study is a resource for learning and teaching introductory statistics. It contains material presented in textbook format and as video presentations. This resource features interactive demonstrations and simulations, case studies, and an analysis lab.This print edition of the public domain textbook gives the student an opportunity to own a physical copy to help enhance their educational experience. This part I features the book Front Matter, Chapters 1-10, and the full Glossary. Chapters Include:: I. Introduction, II. Graphing Distributions, III. Summarizing Distributions, IV. Describing Bivariate Data, V. Probability, VI. Research Design, VII. Normal Distributions, VIII. Advanced Graphs, IX. Sampling Distributions, and X. Estimation. Online Statistics Education: A Multimedia Course of Study (http: //onlinestatbook.com/). Project Leader: David M. Lane, Rice University.

All of Statistics

Author : Larry Wasserman
Publisher : Springer Science & Business Media
ISBN 13 : 0387217363
Total Pages : 446 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis All of Statistics by : Larry Wasserman

Download or read book All of Statistics written by Larry Wasserman and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Bernoulli's Fallacy

Author : Aubrey Clayton
Publisher : Columbia University Press
ISBN 13 : 0231553358
Total Pages : 641 pages
Book Rating : 4.2/5 (315 download)

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Book Synopsis Bernoulli's Fallacy by : Aubrey Clayton

Download or read book Bernoulli's Fallacy written by Aubrey Clayton and published by Columbia University Press. This book was released on 2021-08-03 with total page 641 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a logical flaw in the statistical methods used across experimental science. This fault is not a minor academic quibble: it underlies a reproducibility crisis now threatening entire disciplines. In an increasingly statistics-reliant society, this same deeply rooted error shapes decisions in medicine, law, and public policy with profound consequences. The foundation of the problem is a misunderstanding of probability and its role in making inferences from observations. Aubrey Clayton traces the history of how statistics went astray, beginning with the groundbreaking work of the seventeenth-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics. Clayton recounts the feuds among rival schools of statistics, exploring the surprisingly human problems that gave rise to the discipline and the all-too-human shortcomings that derailed it. He highlights how influential nineteenth- and twentieth-century figures developed a statistical methodology they claimed was purely objective in order to silence critics of their political agendas, including eugenics. Clayton provides a clear account of the mathematics and logic of probability, conveying complex concepts accessibly for readers interested in the statistical methods that frame our understanding of the world. He contends that we need to take a Bayesian approach—that is, to incorporate prior knowledge when reasoning with incomplete information—in order to resolve the crisis. Ranging across math, philosophy, and culture, Bernoulli’s Fallacy explains why something has gone wrong with how we use data—and how to fix it.