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Practical Statistics For Non Mathematical People
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Book Synopsis Practical Statistics for Non-mathematical People by : Russell Langley
Download or read book Practical Statistics for Non-mathematical People written by Russell Langley and published by . This book was released on 1971 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Practical Statistics by : Russell Langley
Download or read book Practical Statistics written by Russell Langley and published by . This book was released on 1968 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Practical Statistics for Data Scientists by : Peter Bruce
Download or read book Practical Statistics for Data Scientists written by Peter Bruce and published by "O'Reilly Media, Inc.". This book was released on 2017-05-10 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data
Book Synopsis Practical Statistics Simply Explained by : Dr. Russell A. Langley
Download or read book Practical Statistics Simply Explained written by Dr. Russell A. Langley and published by Courier Corporation. This book was released on 2013-04-26 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: Primer on how to draw valid conclusions from numerical data using logic and the philosophy of statistics rather than complex formulae. Discusses averages and scatter, investigation design, more. Problems, solutions.
Book Synopsis Practical Statistics by : Robert E. Levasseur
Download or read book Practical Statistics written by Robert E. Levasseur and published by Mindfire Press. This book was released on 2006-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Statistics is for anyone who wants to learn basic statistics for work, school, research, or the sheer enjoyment of gaining new knowledge. If you are practical, decision-oriented person, then Practical Statistics is what you need to facilitate your introduction to the fascinating and powerful tools of statistical analysis.
Book Synopsis Statistics for Non-Statisticians by : Birger Madsen
Download or read book Statistics for Non-Statisticians written by Birger Madsen and published by Springer Science & Business Media. This book was released on 2011-04-13 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book was written for those who need to know how to collect, analyze and present data. It is meant to be a first course for practitioners, a book for private study or brush-up on statistics, and supplementary reading for general statistics classes. The book is untraditional, both with respect to the choice of topics and the presentation. The topics were determined by what is most useful for practical statistical work: even experienced statisticians will find new topics or new approaches to traditional topics. The presentation is as non-mathematical as possible. Mathematical formulae are presented only if they are necessary for calculations and/or add to readers’ understanding. A sample survey is developed as a realistic example throughout the book, and many further examples are presented, which also use data spreadsheets from a supplementary website.
Book Synopsis How Not to Be Wrong by : Jordan Ellenberg
Download or read book How Not to Be Wrong written by Jordan Ellenberg and published by Penguin. This book was released on 2015-05-26 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: “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.
Book Synopsis Statistics for the Health Sciences by : Christine Dancey
Download or read book Statistics for the Health Sciences written by Christine Dancey and published by SAGE. This book was released on 2012-03-19 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Practical Statistics for Medical Research by : Douglas G. Altman
Download or read book Practical Statistics for Medical Research written by Douglas G. Altman and published by CRC Press. This book was released on 1990-11-22 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background. The author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research. Using real data and including dozens of interesting data sets, this bestselling text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.
Book Synopsis Foundations of Data Science by : Avrim Blum
Download or read book Foundations of Data Science written by Avrim Blum and published by Cambridge University Press. This book was released on 2020-01-23 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
Book Synopsis Chance, Luck, and Statistics by : Horace C. Levinson
Download or read book Chance, Luck, and Statistics written by Horace C. Levinson and published by Courier Corporation. This book was released on 2001-01-01 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: In simple, non-technical language, this volume explores the fundamentals governing chance and applies them to sports, government, and business. Topics includenbsp;the theory of probability in relation to superstitions, betting odds, warfare,nbsp;social problems, stocks, and other areas. "Clear and lively ...nbsp;remarkably accurate." —Scientific Monthly.
Author :MacDonald Pairman Jackson Publisher :Oxford University Press, USA ISBN 13 :9780199260508 Total Pages :276 pages Book Rating :4.2/5 (65 download)
Book Synopsis Defining Shakespeare by : MacDonald Pairman Jackson
Download or read book Defining Shakespeare written by MacDonald Pairman Jackson and published by Oxford University Press, USA. This book was released on 2003 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'That very great play, Pericles', as T. S. Eliot called it, poses formidable problems of text and authorship. The first of the Late Romances, it was ascribed to Shakespeare when printed in a quarto of 1609, but was not included in the First Folio (1623) collection of his plays. This bookexamines rival theories about the quarto's origins and offers compelling evidence that Pericles is the product of collaboration between Shakespeare and the minor dramatist George Wilkins, who was responsible for the first two acts and for portions of the 'brothel scenes' in Act 4. Pericles serves asa test case for methodologies that seek to define the limits of the Shakespeare canon and to rdentify co-authors. A wide range of metrical, lexical, and other data is analysed. Computerized 'stylometric' texts are explained and their findings assessed. A concluding chapter introduces a new techniquethat has the potential to answer many of the remaining questions of attribution associated with Shakespeare and his contemporaries.
Book Synopsis Linear Algebra Problem Book by : Paul R. Halmos
Download or read book Linear Algebra Problem Book written by Paul R. Halmos and published by American Mathematical Soc.. This book was released on 1995-12-31 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear Algebra Problem Book can be either the main course or the dessert for someone who needs linear algebraand today that means every user of mathematics. It can be used as the basis of either an official course or a program of private study. If used as a course, the book can stand by itself, or if so desired, it can be stirred in with a standard linear algebra course as the seasoning that provides the interest, the challenge, and the motivation that is needed by experienced scholars as much as by beginning students. The best way to learn is to do, and the purpose of this book is to get the reader to DO linear algebra. The approach is Socratic: first ask a question, then give a hint (if necessary), then, finally, for security and completeness, provide the detailed answer.
Book Synopsis Essential Statistics for Non-STEM Data Analysts by : Rongpeng Li
Download or read book Essential Statistics for Non-STEM Data Analysts written by Rongpeng Li and published by Packt Publishing Ltd. This book was released on 2020-11-12 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforce your understanding of data science and data analysis from a statistical perspective to extract meaningful insights from your data using Python programming Key FeaturesWork your way through the entire data analysis pipeline with statistics concerns in mind to make reasonable decisionsUnderstand how various data science algorithms functionBuild a solid foundation in statistics for data science and machine learning using Python-based examplesBook Description Statistics remain the backbone of modern analysis tasks, helping you to interpret the results produced by data science pipelines. This book is a detailed guide covering the math and various statistical methods required for undertaking data science tasks. The book starts by showing you how to preprocess data and inspect distributions and correlations from a statistical perspective. You’ll then get to grips with the fundamentals of statistical analysis and apply its concepts to real-world datasets. As you advance, you’ll find out how statistical concepts emerge from different stages of data science pipelines, understand the summary of datasets in the language of statistics, and use it to build a solid foundation for robust data products such as explanatory models and predictive models. Once you’ve uncovered the working mechanism of data science algorithms, you’ll cover essential concepts for efficient data collection, cleaning, mining, visualization, and analysis. Finally, you’ll implement statistical methods in key machine learning tasks such as classification, regression, tree-based methods, and ensemble learning. By the end of this Essential Statistics for Non-STEM Data Analysts book, you’ll have learned how to build and present a self-contained, statistics-backed data product to meet your business goals. What you will learnFind out how to grab and load data into an analysis environmentPerform descriptive analysis to extract meaningful summaries from dataDiscover probability, parameter estimation, hypothesis tests, and experiment design best practicesGet to grips with resampling and bootstrapping in PythonDelve into statistical tests with variance analysis, time series analysis, and A/B test examplesUnderstand the statistics behind popular machine learning algorithmsAnswer questions on statistics for data scientist interviewsWho this book is for This book is an entry-level guide for data science enthusiasts, data analysts, and anyone starting out in the field of data science and looking to learn the essential statistical concepts with the help of simple explanations and examples. If you’re a developer or student with a non-mathematical background, you’ll find this book useful. Working knowledge of the Python programming language is required.
Book Synopsis Examples and Problems in Mathematical Statistics by : Shelemyahu Zacks
Download or read book Examples and Problems in Mathematical Statistics written by Shelemyahu Zacks and published by John Wiley & Sons. This book was released on 2013-12-17 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides the necessary skills to solve problems in mathematical statistics through theory, concrete examples, and exercises With a clear and detailed approach to the fundamentals of statistical theory, Examples and Problems in Mathematical Statistics uniquely bridges the gap between theory andapplication and presents numerous problem-solving examples that illustrate the relatednotations and proven results. Written by an established authority in probability and mathematical statistics, each chapter begins with a theoretical presentation to introduce both the topic and the important results in an effort to aid in overall comprehension. Examples are then provided, followed by problems, and finally, solutions to some of the earlier problems. In addition, Examples and Problems in Mathematical Statistics features: Over 160 practical and interesting real-world examples from a variety of fields including engineering, mathematics, and statistics to help readers become proficient in theoretical problem solving More than 430 unique exercises with select solutions Key statistical inference topics, such as probability theory, statistical distributions, sufficient statistics, information in samples, testing statistical hypotheses, statistical estimation, confidence and tolerance intervals, large sample theory, and Bayesian analysis Recommended for graduate-level courses in probability and statistical inference, Examples and Problems in Mathematical Statistics is also an ideal reference for applied statisticians and researchers.
Book Synopsis The Statistical Analysis of Experimental Data by : John Mandel
Download or read book The Statistical Analysis of Experimental Data written by John Mandel and published by Courier Corporation. This book was released on 2012-06-08 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: First half of book presents fundamental mathematical definitions, concepts, and facts while remaining half deals with statistics primarily as an interpretive tool. Well-written text, numerous worked examples with step-by-step presentation. Includes 116 tables.
Book Synopsis Theory of Statistics by : Mark J. Schervish
Download or read book Theory of Statistics written by Mark J. Schervish and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this graduate textbook is to provide a comprehensive advanced course in the theory of statistics covering those topics in estimation, testing, and large sample theory which a graduate student might typically need to learn as preparation for work on a Ph.D. An important strength of this book is that it provides a mathematically rigorous and even-handed account of both Classical and Bayesian inference in order to give readers a broad perspective. For example, the "uniformly most powerful" approach to testing is contrasted with available decision-theoretic approaches.