Download or read book Statistical Papers in Honor of George W Snedecor written by George Waddel Snedecor and published by Wiley-Blackwell. This book was released on 1972 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statisticians of the Centuries written by C.C. Heyde and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by leading statisticians and probabilists, this volume consists of 104 biographical articles on eminent contributors to statistical and probabilistic ideas born prior to the 20th Century. Among the statisticians covered are Fermat, Pascal, Huygens, Neumann, Bernoulli, Bayes, Laplace, Legendre, Gauss, Poisson, Pareto, Markov, Bachelier, Borel, and many more.
Download or read book Selected Statistical Papers of Sir David Cox Volume 2 Foundations of Statistical Inference Theoretical Statistics Time Series and Stochastic Processes written by David Roxbee Cox and published by Cambridge University Press. This book was released on 2005 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sir David Cox's most important papers, each the subject of a new commentary by Professor Cox.
Download or read book Statistical Methods for Geography written by Peter A Rogerson and published by SAGE Publications. This book was released on 2010-02-11 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Third Edition of this bestselling student favorite has again been revised and updated to provide an expert introduction to the principal methods and techniques needed to understand a statistics module. Features new to this edition include: further introductory material; updated exercises and illustrative examples; updated downloadable datasets Statistical Methods is required reading for undergraduate modules in statistical analysis, statistical methods, and quantitative geography.
Download or read book A Modern Course on Statistical Distributions in Scientific Work written by Ganapati P. Patil and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: These three volumes constitute the edited Proceedings of the NATO Advanced Study Institute on Statistical Distributions in Scientific Work held at the University of Calgary from July 29 to August 10, 1974. The general title of the volumes is "Statistical Distributions in Scientific Work". The individual volumes are: Volume 1 - Models and Structures; Volume 2 - Model Building and Model Selection; and Volume 3 - Characterizations and Applications. These correspond to the three advanced seminars of the Institute devoted to the respective subject areas. The planned activities of the Institute consisted of main lectures and expositions, seminar lectures and study group dis cussions, tutorials and individual study. The activities included meetings of editorial committees to discuss editorial matters for these proceedings which consist of contributions that have gone through the usual refereeing process. A special session was organized to consider the potential of introducing a course on statistical distributions in scientific modeling in the curriculum of statistics and quantitative studies. This session is reported in Volume 2. The overall perspective for the Institute is provided by the Institute Director, Professor G. P. Patil, in his inaugural address which appears in Volume 1. The Linnik Memorial Inaugural Lecture given by Professor C. R. Rao for the Characterizations Seminar is included in Volume 3.
Download or read book Design and Analysis of Experiments Introduction to Experimental Design written by Klaus Hinkelmann and published by John Wiley & Sons. This book was released on 1994-03-22 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design and analysis of experiments/Hinkelmann.-v.1.
Download or read book SAGE Handbook of Mixed Methods in Social Behavioral Research written by Abbas Tashakkori and published by SAGE Publications. This book was released on 2021-06-17 with total page 913 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surveying the differing viewpoints and disciplinary approaches to using mixed methods, this volume helps readers explore the answers to a wide range of key questions in the field, including "Can using mixed methods offset the disadvantages that certain methods have by themselves?" "What criteria can a researcher use to select the best mixed methods design for his or her project?" and "What are the points of agreement and controversy regarding design issues in mixed methods research?" This breakthrough Second Edition, containing all new chapters, examines all aspects of mixed methods research across a variety of disciplines. Key Features • Covers all aspects of inquiry from conceptualizing research to selecting methods, analyzing and interpreting data, and reporting findings • Draws on the work of a mix of internationally recognized researchers as well as new and emerging researchers to provide a diversity of perspectives • Gives specific examples from a wide range of disciplines to help readers understand the issues and controversies in this evolving area • Presents rich material for discussion and new ideas for implementing mixed methods research to provide readers with a cutting-edge resource • Provides pedagogical tools such as learning objectives, discussion questions and exercises, and extensive cross referencing
Download or read book Graphics for Statistics and Data Analysis with R written by Kevin J. Keen and published by CRC Press. This book was released on 2010-04-26 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graphics for Statistics and Data Analysis with R presents the basic principles of sound graphical design and applies these principles to engaging examples using the graphical functions available in R. It offers a wide array of graphical displays for the presentation of data, including modern tools for data visualization and representation. The book considers graphical displays of a single discrete variable, a single continuous variable, and then two or more of each of these. It includes displays and the R code for producing the displays for the dot chart, bar chart, pictographs, stemplot, boxplot, and variations on the quantile-quantile plot. The author discusses nonparametric and parametric density estimation, diagnostic plots for the simple linear regression model, polynomial regression, and locally weighted polynomial regression for producing a smooth curve through data on a scatterplot. The last chapter illustrates visualizing multivariate data with examples using Trellis graphics. Showing how to use graphics to display or summarize data, this text provides best practice guidelines for producing and choosing among graphical displays. It also covers the most effective graphing functions in R. R code is available for download on the book’s website.
Download or read book Counting for Something written by William S. Peters and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Handbook of Meta analysis in Ecology and Evolution written by Julia Koricheva and published by Princeton University Press. This book was released on 2013-04-21 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meta-analysis is a powerful statistical methodology for synthesizing research evidence across independent studies. This is the first comprehensive handbook of meta-analysis written specifically for ecologists and evolutionary biologists, and it provides an invaluable introduction for beginners as well as an up-to-date guide for experienced meta-analysts. The chapters, written by renowned experts, walk readers through every step of meta-analysis, from problem formulation to the presentation of the results. The handbook identifies both the advantages of using meta-analysis for research synthesis and the potential pitfalls and limitations of meta-analysis (including when it should not be used). Different approaches to carrying out a meta-analysis are described, and include moment and least-square, maximum likelihood, and Bayesian approaches, all illustrated using worked examples based on real biological datasets. This one-of-a-kind resource is uniquely tailored to the biological sciences, and will provide an invaluable text for practitioners from graduate students and senior scientists to policymakers in conservation and environmental management. Walks you through every step of carrying out a meta-analysis in ecology and evolutionary biology, from problem formulation to result presentation Brings together experts from a broad range of fields Shows how to avoid, minimize, or resolve pitfalls such as missing data, publication bias, varying data quality, nonindependence of observations, and phylogenetic dependencies among species Helps you choose the right software Draws on numerous examples based on real biological datasets
Download or read book Statistics for Research written by Shirley Dowdy and published by John Wiley & Sons. This book was released on 2011-09-26 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Second Edition "Statistics for Research has other fine qualities besides superior organization. The examples and the statistical methods are laid out with unusual clarity by the simple device of using special formats for each. The book was written with great care and is extremely user-friendly."—The UMAP Journal Although the goals and procedures of statistical research have changed little since the Second Edition of Statistics for Research was published, the almost universal availability of personal computers and statistical computing application packages have made it possible for today's statisticians to do more in less time than ever before. The Third Edition of this bestselling text reflects how the changes in the computing environment have transformed the way statistical analyses are performed today. Based on extensive input from university statistics departments throughout the country, the authors have made several important and timely revisions, including: Additional material on probability appears early in the text New sections on odds ratios, ratio and difference estimations, repeated measure analysis, and logistic regression New examples and exercises, many from the field of the health sciences Printouts of computer analyses on all complex procedures An accompanying Web site illustrating how to use SAS® and JMP® for all procedures The text features the most commonly used statistical techniques for the analysis of research data. As in the earlier editions, emphasis is placed on how to select the proper statistical procedure and how to interpret results. Whenever possible, to avoid using the computer as a "black box" that performs a mysterious process on the data, actual computational procedures are also given. A must for scientists who analyze data, professionals and researchers who need a self-teaching text, and graduate students in statistical methods, Statistics for Research, Third Edition brings the methodology up to date in a very practical and accessible way.
Download or read book BMDP Statistical Software written by Wilfrid Joseph Dixon and published by Univ of California Press. This book was released on 1983-01-01 with total page 748 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modern Applied Regressions written by Jun Xu and published by CRC Press. This book was released on 2022-12-08 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern Applied Regressions creates an intricate and colorful mural with mosaics of categorical and limited response variable (CLRV) models using both Bayesian and Frequentist approaches. Written for graduate students, junior researchers, and quantitative analysts in behavioral, health, and social sciences, this text provides details for doing Bayesian and frequentist data analysis of CLRV models. Each chapter can be read and studied separately with R coding snippets and template interpretation for easy replication. Along with the doing part, the text provides basic and accessible statistical theories behind these models and uses a narrative style to recount their origins and evolution. This book first scaffolds both Bayesian and frequentist paradigms for regression analysis, and then moves onto different types of categorical and limited response variable models, including binary, ordered, multinomial, count, and survival regression. Each of the middle four chapters discusses a major type of CLRV regression that subsumes an array of important variants and extensions. The discussion of all major types usually begins with the history and evolution of the prototypical model, followed by the formulation of basic statistical properties and an elaboration on the doing part of the model and its extension. The doing part typically includes R codes, results, and their interpretation. The last chapter discusses advanced modeling and predictive techniques—multilevel modeling, causal inference and propensity score analysis, and machine learning—that are largely built with the toolkits designed for the CLRV models previously covered. The online resources for this book, including R and Stan codes and supplementary notes, can be accessed at https://sites.google.com/site/socjunxu/home/statistics/modern-applied-regressions.
Download or read book Time Series Techniques for Economists written by Terence C. Mills and published by Cambridge University Press. This book was released on 1990 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of time series techniques in economics has become increasingly important, both for forecasting purposes and in the empirical analysis of time series in general. In this book, Terence Mills not only brings together recent research at the frontiers of the subject, but also analyses the areas of most importance to applied economics. It is an up-to-date text which extends the basic techniques of analysis to cover the development of methods that can be used to analyse a wide range of economic problems. The book analyses three basic areas of time series analysis: univariate models, multivariate models, and non-linear models. In each case the basic theory is outlined and then extended to cover recent developments. Particular emphasis is placed on applications of the theory to important areas of applied economics and on the computer software and programs needed to implement the techniques. This book clearly distinguishes itself from its competitors by emphasising the techniques of time series modelling rather than technical aspects such as estimation, and by the breadth of the models considered. It features many detailed real-world examples using a wide range of actual time series. It will be useful to econometricians and specialists in forecasting and finance and accessible to most practitioners in economics and the allied professions.
Download or read book Financial Data Analytics with Machine Learning Optimization and Statistics written by Sam Chen and published by John Wiley & Sons. This book was released on 2024-10-18 with total page 823 pages. Available in PDF, EPUB and Kindle. Book excerpt: An essential introduction to data analytics and Machine Learning techniques in the business sector In Financial Data Analytics with Machine Learning, Optimization and Statistics, a team consisting of a distinguished applied mathematician and statistician, experienced actuarial professionals and working data analysts delivers an expertly balanced combination of traditional financial statistics, effective machine learning tools, and mathematics. The book focuses on contemporary techniques used for data analytics in the financial sector and the insurance industry with an emphasis on mathematical understanding and statistical principles and connects them with common and practical financial problems. Each chapter is equipped with derivations and proofs—especially of key results—and includes several realistic examples which stem from common financial contexts. The computer algorithms in the book are implemented using Python and R, two of the most widely used programming languages for applied science and in academia and industry, so that readers can implement the relevant models and use the programs themselves. The book begins with a brief introduction to basic sampling theory and the fundamentals of simulation techniques, followed by a comparison between R and Python. It then discusses statistical diagnosis for financial security data and introduces some common tools in financial forensics such as Benford's Law, Zipf's Law, and anomaly detection. The statistical estimation and Expectation-Maximization (EM) & Majorization-Minimization (MM) algorithms are also covered. The book next focuses on univariate and multivariate dynamic volatility and correlation forecasting, and emphasis is placed on the celebrated Kelly's formula, followed by a brief introduction to quantitative risk management and dependence modelling for extremal events. A practical topic on numerical finance for traditional option pricing and Greek computations immediately follows as well as other important topics in financial data-driven aspects, such as Principal Component Analysis (PCA) and recommender systems with their applications, as well as advanced regression learners such as kernel regression and logistic regression, with discussions on model assessment methods such as simple Receiver Operating Characteristic (ROC) curves and Area Under Curve (AUC) for typical classification problems. The book then moves on to other commonly used machine learning tools like linear classifiers such as perceptrons and their generalization, the multilayered counterpart (MLP), Support Vector Machines (SVM), as well as Classification and Regression Trees (CART) and Random Forests. Subsequent chapters focus on linear Bayesian learning, including well-received credibility theory in actuarial science and functional kernel regression, and non-linear Bayesian learning, such as the Naïve Bayes classifier and the Comonotone-Independence Bayesian Classifier (CIBer) recently independently developed by the authors and used successfully in InsurTech. After an in-depth discussion on cluster analyses such as K-means clustering and its inversion, the K-nearest neighbor (KNN) method, the book concludes by introducing some useful deep neural networks for FinTech, like the potential use of the Long-Short Term Memory model (LSTM) for stock price prediction. This book can help readers become well-equipped with the following skills: To evaluate financial and insurance data quality, and use the distilled knowledge obtained from the data after applying data analytic tools to make timely financial decisions To apply effective data dimension reduction tools to enhance supervised learning To describe and select suitable data analytic tools as introduced above for a given dataset depending upon classification or regression prediction purpose The book covers the competencies tested by several professional examinations, such as the Predictive Analytics Exam offered by the Society of Actuaries, and the Institute and Faculty of Actuaries' Actuarial Statistics Exam. Besides being an indispensable resource for senior undergraduate and graduate students taking courses in financial engineering, statistics, quantitative finance, risk management, actuarial science, data science, and mathematics for AI, Financial Data Analytics with Machine Learning, Optimization and Statistics also belongs in the libraries of aspiring and practicing quantitative analysts working in commercial and investment banking.
Download or read book Annotated Readings in the History of Statistics written by H.A. David and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a selection of pioneering papers or extracts ranging from Pascal (1654) to R.A. Fisher (1930). The editors'annotations put the articles in perspective for the modern reader. A special feature of the book is the large number of translations, nearly all made by the authors. There are several reasons for studying the history of statistics: intrinsic interest in how the field of statistics developed, learning from often brilliant ideas and not reinventing the wheel, and livening up general courses in statistics by reference to important contributors.
Download or read book BMDP Statistical Software Manual written by Wilfrid Joseph Dixon and published by Univ of California Press. This book was released on 1992-01-01 with total page 846 pages. Available in PDF, EPUB and Kindle. Book excerpt: The BMDP package is an extensive collection of computer programs that aids students, instructors and research professionals the world over in analyzing data. Running on most mainframes, minicomputers and PCs, the BMDP software has capabilities ranging from plots and simple data description to more sophisticated techniques such as repeated measures analysis. Practitioners in diverse fields, from psychology, sociology and economics to biology, medicine and public health, should find the BDMP programs of use.
