Download or read book Distributional Analysis Using Sample Data written by F. A. Cowell and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Analysis of Distributional Data written by Paula Brito and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a time when increasingly larger and complex data collections are being produced, it is clear that new and adaptive forms of data representation and analysis have to be conceived and implemented. Distributional data, i.e., data where a distribution rather than a single value is recorded for each descriptor, on each unit, come into this framework. Distributional data may result from the aggregation of large amounts of open/collected/generated data, or it may be directly available in a structured or unstructured form, describing the variability of some features. This book provides models and methods for the representation, analysis, interpretation, and organization of distributional data, taking into account its specific nature, and not relying on a reduction to single values, to be conform to classical paradigms. --
Download or read book Distributional Analysis with L moment Statistics Using the R Environment for Statistical Computing written by William H. Asquith and published by Createspace Independent Publishing Platform. This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph (2nd printing) is the most complete account to date of L-moment statistics in the context of distributional analysis using an open-source programming environment-the R environment for statistical computing. The target audience are engineers/scientists with limited backgrounds in statistics and computer programming but with responsibilities in analyzing highly non-Normal, skewed, or heavy-tailed data. The monograph is written in continuous narrative and is oriented around the software package "lmomco" previously written by the author but tremendously expanded and refined for the monograph. The monograph covers an introduction to R and cites the extensive book-literature on computational and statistical analysis using R. Note, an errata can be found in the text file ERRATA_FOR_ISBN9781463508418.txt that is distributed with the lmomco package.The monograph covers, by a large-scale coupling of source code to typeset mathematics, a myriad of topics including quantile functions, order statistics, product moments, probability-weighted moments (PWMs), censored PWMs, L-moments (censored/trimmed), L-comoments, and numerous probability distributions including the two-parameter Cauchy, Exponential, Normal, Gamma, Gumbel, reverse Gumbel, Kumaraswamy, Rayleigh, and Rice; the three-parameter Generalized Extreme Value, Generalized Logistic, Generalized Normal, Generalized Pareto (GPA), right-censored (RC) GPA, trimmed GPA, Pearson Type III, and Weibull; four- and more parameter distributions including the Kappa, Generalized Lambda (GLD), trimmed GLD, and Wakeby; and the method of L-moments and method of PWMs for these distributions.The monograph thoroughly describes L-moment ratio diagrams. Venerable statistics such as Sen weighted mean and Gini mean difference also are considered as are emergent statistical functions such as copulas. Extensive simulation studies are shown through code examples and the results are often depicted in figures; these studies demonstrate the reliability of the examples and lmomco by demonstrating consistency with results with the literature. Topical case studies of regional distributional analysis of hydrometeorologic data are shown to guide readers.The monograph presents new developments by the author or following prior literature results that include censored PWMs and L-moments by censoring fraction, threshold, and indicator; the Cauchy, Kumaraswamy, Rayleigh, Rice, trimmed GPA, and RC-GPA distributions; L-comoments in context of copulas; and theoretical (non-sample) computation of L-moments.The monograph provides more than 245 code examples, about 515 numbered equations, a thorough topical index, and an index of about 425 R functions used in the examples. Approximately 100 figures are provided and virtually all of the figures can be created from the code in the text.
Download or read book Distributional Cost Effectiveness Analysis written by Richard Cookson and published by Handbooks in Health Economic Evaluation. This book was released on 2020-09-30 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Health inequalities blight lives, generate enormous costs, and exist everywhere. This book is the definitive all-in-one guide for anyone who wishes to learn about, commission, and use distributional cost-effectiveness analysis to promote both equity and efficiency in health and healthcare.
Download or read book Relative Distribution Methods in the Social Sciences written by Mark S. Handcock and published by Springer Science & Business Media. This book was released on 2006-05-10 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents methods for full comparative distributional analysis based on the relative distribution. This provides a general integrated framework for analysis, a graphical component that simplifies exploratory data analysis and display, a statistically valid basis for the development of hypothesis-driven summary measures, and the potential for decomposition - enabling the examination of complex hypotheses regarding the origins of distributional changes within and between groups. Written for data analysts and those interested in measurement, the text can also serve as a textbook for a course on distributional methods.
Download or read book A Distributional Analysis of Trends in Energy Expenditures by Black Households written by John M. Brazzel and published by . This book was released on 1980 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Analysis of Nonnormal Data written by J. V. Deshpande and published by Taylor & Francis. This book was released on 1995 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Analysis Of Nonnormal Data Has Successfully Made Available In One Place Nonparametric Methods And Methods Of Discrete Data-Analysis. It Has Attempted To Introduce The Reader To Methods Appropriate For Simple, Continuous, Nonnormal Distribution Of Interest In The Newly Emerging Area Of Survival Analysis And Reliability. The Book Also Provides Computer Programmes For Ready Use.It Can Be Used By Anyone Familiar With Standard Statistical Principles And The Tools In The Framework Of Normal Distribution. Computer Programmes Are In Theready To Use Format. Therefore, Familiarity With Operations Of A Personal Computer And A Dos Environment Is The Only Prerequisite.The Book Would Make An Excellent Text For A Second Course In Statistical Methods For Biologists, Social Scientists, Engineers, Etc. Researchers In Various Disciplines Should Be Able To Use The Methods Described In The Book Without The Benefit Of A Formal Course.
Download or read book Introduction to Data Science written by Rafael A. Irizarry and published by CRC Press. This book was released on 2019-11-20 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.
Download or read book Resampling Methods written by Phillip I. Good and published by Springer Science & Business Media. This book was released on 2013-04-18 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: "...the author has packaged an excellent and modern set of topics around the development and use of quantitative models...the author has the capability to work at a more modest level. He does that very effectively in this 2nd Edition... If you need to learn about resampling, this book would be a good place to start." -- Technometrics This work is a practical, table-free introduction to data analysis using the bootstrap, cross-validation, and permutation tests; new to the second edition are several additional examples and a chapter dedicated to regression, data mining techniques, and their limitations. The book’s many exercises, practical data sets, and use of free shareware make it an essential resource for students and teachers, as well as industrial statisticians, consultants, and research professionals.
Download or read book Statistical Analysis of Reliability Data written by Martin J. Crowder and published by Routledge. This book was released on 2017-11-13 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written for those who have taken a first course in statistical methods, this book takes a modern, computer-oriented approach to describe the statistical techniques used for the assessment of reliability.
Download or read book Statistical Analysis written by Conrad Carlberg and published by Que Publishing. This book was released on 2014-04-04 with total page 714 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use Excel 2013’s statistical tools to transform your data into knowledge Conrad Carlberg shows how to use Excel 2013 to perform core statistical tasks every business professional, student, and researcher should master. Using real-world examples, Carlberg helps you choose the right technique for each problem and get the most out of Excel’s statistical features, including recently introduced consistency functions. Along the way, he clarifies confusing statistical terminology and helps you avoid common mistakes. You’ll learn how to use correlation and regression, analyze variance and covariance, and test statistical hypotheses using the normal, binomial, t, and F distributions. To help you make accurate inferences based on samples from a population, this edition adds two more chapters on inferential statistics, covering crucial topics ranging from experimental design to the statistical power of F tests. Becoming an expert with Excel statistics has never been easier! You’ll find crystal-clear instructions, insider insights, and complete step-by-step projects—all complemented by extensive web-based resources. Master Excel’s most useful descriptive and inferential statistical tools Tell the truth with statistics—and recognize when others don’t Accurately summarize sets of values Infer a population’s characteristics from a sample’s frequency distribution Explore correlation and regression to learn how variables move in tandem Use Excel consistency functions such as STDEV.S() and STDEV.P() Test differences between two means using z tests, t tests, and Excel’s Data Analysis Add-in Use ANOVA to test differences between more than two means Explore statistical power by manipulating mean differences, standard errors, directionality, and alpha Take advantage of Recommended PivotTables, Quick Analysis, and other Excel 2013 shortcuts
Download or read book Introductory Business Statistics paperback B w written by Alexander Holmes and published by . This book was released on 2023-06-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Printed in b&w. Introductory Business Statistics is designed to meet the scope and sequence requirements of the one-semester statistics course for business, economics, and related majors. Core statistical concepts and skills have been augmented with practical business examples, scenarios, and exercises. The result is a meaningful understanding of the discipline, which will serve students in their business careers and real-world experiences.
Download or read book Distributional Analysis of Tax Policy written by David F. Bradford and published by American Enterprise Institute. This book was released on 1995 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fifteen authors and five commentators include current and former members of the Office of Tax Analysis, the Joint Committee on Taxation, and the Congressional Budget Office, lending an authority to this discussion of tax distributional tables, their methodology, and consideration for improvement. The analysis outlines the attitudes and problems in the current distributional tax methods, innovations in the JCT distribution, the use of generational accounting, transfer systems, and lifetime taxpayer profiles. Annotation copyright by Book News, Inc., Portland, OR
Download or read book Practical Methods for Reliability Data Analysis written by Jake Ansell and published by Oxford University Press. This book was released on 1994 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical introduction to the analysis of data collected from reliability studies offers clear, detailed explanations of the best and most up-to-date techniques available. Topics include survival analysis with covariates, the assessment of systems performance, reliability growth models, dependency (which encompasses both engineering and statistical approaches), and practical aspects of analysis. A wealth of interesting case studies appear throughout the text, lending "real-world" examples to the more theoretical discussions. Throughout, the authors stress the need for investigators to understand the background and nature of their data if they are to select the most appropriate analysis method. They also provide in-depth treatments of the mathematical and statistical bases underlying each technique. Accessible and comprehensive, the book will be welcomed by students, professionals, and statisticians who are interested in the practical aspects of reliability data analysis.
Download or read book Reliability Analysis with Minitab written by Kishore Kumar Pochampally and published by CRC Press. This book was released on 2016-03-23 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Analysis for the Reliability Engineering ProfessionalEffectively conduct reliability analysis using the world's leading statistical software. Reliability Analysis with Minitab outlines statistical concepts and applications, explains the theory of probability, reliability analysis, and quality improvement, and provides step-by-step instr
Download or read book Statistics for Big Data For Dummies written by Alan Anderson and published by John Wiley & Sons. This book was released on 2015-08-31 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fast and easy way to make sense of statistics for big data Does the subject of data analysis make you dizzy? You've come to the right place! Statistics For Big Data For Dummies breaks this often-overwhelming subject down into easily digestible parts, offering new and aspiring data analysts the foundation they need to be successful in the field. Inside, you'll find an easy-to-follow introduction to exploratory data analysis, the lowdown on collecting, cleaning, and organizing data, everything you need to know about interpreting data using common software and programming languages, plain-English explanations of how to make sense of data in the real world, and much more. Data has never been easier to come by, and the tools students and professionals need to enter the world of big data are based on applied statistics. While the word "statistics" alone can evoke feelings of anxiety in even the most confident student or professional, it doesn't have to. Written in the familiar and friendly tone that has defined the For Dummies brand for more than twenty years, Statistics For Big Data For Dummies takes the intimidation out of the subject, offering clear explanations and tons of step-by-step instruction to help you make sense of data mining—without losing your cool. Helps you to identify valid, useful, and understandable patterns in data Provides guidance on extracting previously unknown information from large databases Shows you how to discover patterns available in big data Gives you access to the latest tools and techniques for working in big data If you're a student enrolled in a related Applied Statistics course or a professional looking to expand your skillset, Statistics For Big Data For Dummies gives you access to everything you need to succeed.
Download or read book Statistics 101 written by David Borman and published by Simon and Schuster. This book was released on 2018-12-18 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to statistics—with information on collecting, measuring, analyzing, and presenting statistical data—continuing the popular 101 series. Data is everywhere. In the age of the internet and social media, we’re responsible for consuming, evaluating, and analyzing data on a daily basis. From understanding the percentage probability that it will rain later today, to evaluating your risk of a health problem, or the fluctuations in the stock market, statistics impact our lives in a variety of ways, and are vital to a variety of careers and fields of practice. Unfortunately, most statistics text books just make us want to take a snooze, but with Statistics 101, you’ll learn the basics of statistics in a way that is both easy-to-understand and apply. From learning the theory of probability and different kinds of distribution concepts, to identifying data patterns and graphing and presenting precise findings, this essential guide can help turn statistical math from scary and complicated, to easy and fun. Whether you are a student looking to supplement your learning, a worker hoping to better understand how statistics works for your job, or a lifelong learner looking to improve your grasp of the world, Statistics 101 has you covered.
