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Author: Alan Graham
Publisher: Hodder & Stoughton
Published: 2011
Total Pages: 0
ISBN-13: 9781444135039
DOWNLOAD EBOOK →An introduction to statistics covers the concepts of probability, linear regression, correlation, and significance testing.
Author: Daniel Navarro
Publisher: Lulu.com
Published: 2013-01-13
Total Pages: 617
ISBN-13: 1326189727
DOWNLOAD EBOOK →"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
Author: David Spiegelhalter
Publisher: Basic Books
Published: 2019-09-03
Total Pages: 359
ISBN-13: 1541618521
DOWNLOAD EBOOK →In this "important and comprehensive" guide to statistical thinking (New Yorker), discover how data literacy is changing the world and gives you a better understanding of life’s biggest problems. Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence -- and even more so if we hope to participate in the future, rather than being simple bystanders. In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems -- it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and -- perhaps even more importantly -- we learn how to responsibly interpret the answers we receive. Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.
Author: Gareth James
Publisher: Springer Nature
Published: 2023-08-01
Total Pages: 617
ISBN-13: 3031387473
DOWNLOAD EBOOK →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.
Author: M. D. Edge
Publisher: Oxford University Press, USA
Published: 2019-06-13
Total Pages: 318
ISBN-13: 0198827628
DOWNLOAD EBOOK →Researchers across the natural and social sciences find themselves navigating tremendous amounts of new data. Making sense of this flood of information requires more than the rote application of formulaic statistical methods. The premise of Statistical Thinking from Scratch is that students who want to become confident data analysts are better served by a deep introduction to a single statistical method than by a cursory overview of many methods. In particular, this book focuses on simple linear regression-a method with close connections to the most important tools in applied statistics-using it as a detailed case study for teaching resampling-based, likelihood-based, and Bayesian approaches to statistical inference. Considering simple linear regression in depth imparts an idea of how statistical procedures are designed, a flavour for the philosophical positions one assumes when applying statistics, and tools to probe the strengths of one's statistical approach. Key to the book's novel approach is its mathematical level, which is gentler than most texts for statisticians but more rigorous than most introductory texts for non-statisticians. Statistical Thinking from Scratch is suitable for senior undergraduate and beginning graduate students, professional researchers, and practitioners seeking to improve their understanding of statistical methods across the natural and social sciences, medicine, psychology, public health, business, and other fields.
Author: Alan Graham
Publisher: Teach Yourself
Published: 2017-04-06
Total Pages: 320
ISBN-13: 1473652014
DOWNLOAD EBOOK →Do you need to gain confidence with handling numbers and formulae? Do you want a clear, step-by-step guide to the key concepts and principles of statistics? Nearly all aspects of our lives can be subject to statistical analysis. Statistics: An Introduction shows you how to interpret, analyze and present figures. Assuming minimal knowledge of maths and using examples from a wide variety of everyday contexts, this book makes often complex concepts and techniques easy to get to grips with. This new edition has been fully updated. Whether you want to understand the statistics that you are bombarded with every day or are a student or professional coming to statistics from a wide range of disciplines, Statistics: An Introduction covers it all.
Author: Ashish Sen
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 361
ISBN-13: 1461244706
DOWNLOAD EBOOK →An up-to-date, rigorous, and lucid treatment of the theory, methods, and applications of regression analysis, and thus ideally suited for those interested in the theory as well as those whose interests lie primarily with applications. It is further enhanced through real-life examples drawn from many disciplines, showing the difficulties typically encountered in the practice of regression analysis. Consequently, this book provides a sound foundation in the theory of this important subject.
Author: Deborah J. Rumsey
Publisher: John Wiley & Sons
Published: 2009-08-31
Total Pages: 411
ISBN-13: 0470466464
DOWNLOAD EBOOK →The ideal supplement and study guide for students preparing for advanced statistics Packed with fresh and practical examples appropriate for a range of degree-seeking students, Statistics II For Dummies helps any reader succeed in an upper-level statistics course. It picks up with data analysis where Statistics For Dummies left off, featuring new and updated examples, real-world applications, and test-taking strategies for success. This easy-to-understand guide covers such key topics as sorting and testing models, using regression to make predictions, performing variance analysis (ANOVA), drawing test conclusions with chi-squares, and making comparisons with the Rank Sum Test.
Author: Carey Witkov
Publisher: Oxford University Press
Published: 2019-09-17
Total Pages: 112
ISBN-13: 0198847157
DOWNLOAD EBOOK →Recent groundbreaking discoveries in physics, including the discovery of the Higgs Boson and gravitational waves, have relied on chi-squared analysis and model testing, a data analysis method. This is the first book to make chi-squared model testing accessible to students in introductory physics lab courses and others who need to learn this method, such as beginning researchers in astrophysics and particle physics, beginners in data science, and lab students in other experimental sciences. For over a decade, Harvard University's introductory physics lab sequence has made chi-squared model testing its central theme. Written by two faculty members, the book is based on years of experience teaching students learn how to think like scientists by testing their models using chi-squared analysis. By including uncertainties in the curve fitting technique, chi-squared data analysis improves on the centuries old ordinary least squares and linear regression methods and combines best fit parameter estimation and model testing in one method. A toolkit of essential statistical and experimental concepts is developed from the ground up with novel features to interest even those familiar with the material. The presentation of one and two parameter chi-squared model testing, requiring only elementary probability and algebra, is followed by case studies that apply the methods to simple introductory physics lab experiments. More challenging topics requiring calculus are addressed in an advanced topic chapter. This self-contained and student-friendly introduction includes a glossary, end of chapter problems with complete solutions, and software scripts available in several popular programming languages that the reader can use for chi-squared model testing.
Author: Stanley Rothman
Publisher: JHU Press
Published: 2012-11-01
Total Pages: 587
ISBN-13: 1421408678
DOWNLOAD EBOOK →Sandlot Stats uses the national pastime to help students who love baseball learn—and enjoy—statistics. As Derek Jeter strolls toward the plate, the announcer tosses out a smattering of statistics—from hitting streaks to batting averages. But what do the numbers mean? And how can America’s favorite pastime be a model for learning about statistics? Sandlot Stats is an innovative textbook that explains the mathematical underpinnings of baseball so that students can understand the world of statistics and probability. Carefully illustrated and filled with exercises and examples, this book teaches the fundamentals of probability and statistics through the feats of baseball legends such as Hank Aaron, Joe DiMaggio, and Ted Williams—and more recent players such as Barry Bonds, Albert Pujols, and Alex Rodriguez. Exercises require only pen-and-paper or Microsoft Excel to perform the analyses. Sandlot Stats covers all the bases, including • descriptive and inferential statistics • linear regression and correlation • probability • sports betting • probability distribution functions • sampling distributions • hypothesis testing • confidence intervals • chi-square distribution Sandlot Stats offers information covered in most introductory statistics books, yet is peppered with interesting facts from the history of baseball to enhance the interest of the student and make learning fun.
