Download Full eBooks in PDF
Studies In The History Of Statistical Method Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Studies In The History Of Statistical Method book. This book definitely worth reading, it is an incredibly well-written.
Author : Helen Mary Walker
Publisher : New York : Arno Press
Page : 272 pages
File Size : 53,9 Mb
Release : 1975
Category : Mathematics
ISBN : WISC:89057156341
Bibliografi s. 193-215
Author : Helen Mary Walker
Publisher : Unknown
Page : 229 pages
File Size : 53,6 Mb
Release : 1987
Category : Statistics
ISBN : LCCN:29013991
Author : Helen M. Walker
Publisher : Unknown
Page : 0 pages
File Size : 42,6 Mb
Release : 1931
Category : Electronic
ISBN : OCLC:476487568
Author : Helen Mary Walker
Publisher : Unknown
Page : 262 pages
File Size : 41,9 Mb
Release : 1929
Category : Electronic
ISBN : 059880692X
Author : August Meitzen
Publisher : Unknown
Page : 264 pages
File Size : 49,5 Mb
Release : 1891
Category : Statistics
ISBN : UCAL:$B553568
Author : Konrad H. Jarausch,Kenneth A. Hardy
Publisher : UNC Press Books
Page : 266 pages
File Size : 51,5 Mb
Release : 2016-08-01
Category : History
ISBN : 9781469621470
The pioneering texts in quantitative history were written over two decades ago, but as a command of methodological context, computer experience, and statistical literacy have become increasingly important to the study of history, the need for an introductory text addressing these matters has increased. Quantitative Methods for Historians is a theoretical and practical guide for the application of quantitative analysis in historical research. It is designed for students of history and related disciplines who are curious about the possibilities of quantification and want to learn more about its recent development. Integrating the use of the statistical packages SAS and SPSS with the quantitative method, the authors discuss techniques for defining a problem, proceed to the building of a data set and the use of statistical methods, and conclude with the interpretation of results. The data set section concentrates on the basics of formalized research, discussing the coding process and the more complicated problems of data transformation and linkage. The statistical parts systematically build upon traditional fundamentals and introduce new analytical techniques for qualitative variables. Intended as a working introduction to quantitative methods, this guide also provides additional information on advanced statistical techniques and discusses questions of historical computing, reflecting critically on the proper role of quantitative methods.
Author : Stephen M. Stigler
Publisher : Harvard University Press
Page : 436 pages
File Size : 42,5 Mb
Release : 1990-03-01
Category : History
ISBN : 9780674256859
This magnificent book is the first comprehensive history of statistics from its beginnings around 1700 to its emergence as a distinct and mature discipline around 1900. Stephen M. Stigler shows how statistics arose from the interplay of mathematical concepts and the needs of several applied sciences including astronomy, geodesy, experimental psychology, genetics, and sociology. He addresses many intriguing questions: How did scientists learn to combine measurements made under different conditions? And how were they led to use probability theory to measure the accuracy of the result? Why were statistical methods used successfully in astronomy long before they began to play a significant role in the social sciences? How could the introduction of least squares predate the discovery of regression by more than eighty years? On what grounds can the major works of men such as Bernoulli, De Moivre, Bayes, Quetelet, and Lexis be considered partial failures, while those of Laplace, Galton, Edgeworth, Pearson, and Yule are counted as successes? How did Galton’s probability machine (the quincunx) provide him with the key to the major advance of the last half of the nineteenth century? Stigler’s emphasis is upon how, when, and where the methods of probability theory were developed for measuring uncertainty in experimental and observational science, for reducing uncertainty, and as a conceptual framework for quantitative studies in the social sciences. He describes with care the scientific context in which the different methods evolved and identifies the problems (conceptual or mathematical) that retarded the growth of mathematical statistics and the conceptual developments that permitted major breakthroughs. Statisticians, historians of science, and social and behavioral scientists will gain from this book a deeper understanding of the use of statistical methods and a better grasp of the promise and limitations of such techniques. The product of ten years of research, The History of Statistics will appeal to all who are interested in the humanistic study of science.
Author : Stephen M. Stigler
Publisher : Harvard University Press
Page : 514 pages
File Size : 40,8 Mb
Release : 2002-09-30
Category : History
ISBN : 0674009797
This lively collection of essays examines statistical ideas with an ironic eye for their essence and what their history can tell us for current disputes. The topics range from 17th-century medicine and the circulation of blood, to the cause of the Great Depression, to the determinations of the shape of the Earth and the speed of light.
Author : Hans-Peter Blossfeld,Alfred Hamerle,Karl Ulrich Mayer
Publisher : Psychology Press
Page : 298 pages
File Size : 47,8 Mb
Release : 2014-02-24
Category : Psychology
ISBN : 9781317785729
Serving as both a student textbook and a professional reference/handbook, this volume explores the statistical methods of examining time intervals between successive state transitions or events. Examples include: survival rates of patients in medical studies, unemployment periods in economic studies, or the period of time it takes a criminal to break the law after his release in a criminological study. The authors illustrate the entire research path required in the application of event-history analysis, from the initial problems of recording event-oriented data to the specific questions of data organization, to the concrete application of available program packages and the interpretation of the obtained results. Event History Analysis: * makes didactically accessible the inclusion of covariates in semi-parametric and parametric regression models based upon concrete examples * presents the unabbreviated close relationship underlying statistical theory * details parameter-free methods of analysis of event-history data and the possibilities of their graphical presentation * discusses specific problems of multi-state and multi-episode models * introduces time-varying covariates and the question of unobserved population heterogeneity * demonstrates, through examples, how to implement hypotheses tests and how to choose the right model.
Author : Kenneth J. Berry,Janis E. Johnston,Paul W. Mielke Jr.
Publisher : Springer Science & Business Media
Page : 517 pages
File Size : 54,6 Mb
Release : 2014-04-11
Category : Mathematics
ISBN : 9783319027449
The focus of this book is on the birth and historical development of permutation statistical methods from the early 1920s to the near present. Beginning with the seminal contributions of R.A. Fisher, E.J.G. Pitman, and others in the 1920s and 1930s, permutation statistical methods were initially introduced to validate the assumptions of classical statistical methods. Permutation methods have advantages over classical methods in that they are optimal for small data sets and non-random samples, are data-dependent, and are free of distributional assumptions. Permutation probability values may be exact, or estimated via moment- or resampling-approximation procedures. Because permutation methods are inherently computationally-intensive, the evolution of computers and computing technology that made modern permutation methods possible accompanies the historical narrative. Permutation analogs of many well-known statistical tests are presented in a historical context, including multiple correlation and regression, analysis of variance, contingency table analysis, and measures of association and agreement. A non-mathematical approach makes the text accessible to readers of all levels.
Author : Larry V. Hedges,Ingram Olkin
Publisher : Academic Press
Page : 369 pages
File Size : 52,8 Mb
Release : 2014-06-28
Category : Mathematics
ISBN : 9780080570655
The main purpose of this book is to address the statistical issues for integrating independent studies. There exist a number of papers and books that discuss the mechanics of collecting, coding, and preparing data for a meta-analysis , and we do not deal with these. Because this book concerns methodology, the content necessarily is statistical, and at times mathematical. In order to make the material accessible to a wider audience, we have not provided proofs in the text. Where proofs are given, they are placed as commentary at the end of a chapter. These can be omitted at the discretion of the reader. Throughout the book we describe computational procedures whenever required. Many computations can be completed on a hand calculator, whereas some require the use of a standard statistical package such as SAS, SPSS, or BMD. Readers with experience using a statistical package or who conduct analyses such as multiple regression or analysis of variance should be able to carry out the analyses described with the aid of a statistical package.
Author : Peter Westfall,Kevin S. S. Henning
Publisher : CRC Press
Page : 572 pages
File Size : 46,6 Mb
Release : 2013-04-09
Category : Mathematics
ISBN : 9781466512108
Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum likelihood, bootstrapping, nonparametrics, and Bayesian methods. The book teaches students how to properly model, think critically, and design their own studies to avoid common errors. It leads them to think differently not only about math and statistics but also about general research and the scientific method. With a focus on statistical models as producers of data, the book enables students to more easily understand the machinery of advanced statistics. It also downplays the "population" interpretation of statistical models and presents Bayesian methods before frequentist ones. Requiring no prior calculus experience, the text employs a "just-in-time" approach that introduces mathematical topics, including calculus, where needed. Formulas throughout the text are used to explain why calculus and probability are essential in statistical modeling. The authors also intuitively explain the theory and logic behind real data analysis, incorporating a range of application examples from the social, economic, biological, medical, physical, and engineering sciences. Enabling your students to answer the why behind statistical methods, this text teaches them how to successfully draw conclusions when the premises are flawed. It empowers them to use advanced statistical methods with confidence and develop their own statistical recipes. Ancillary materials are available on the book’s website.
Author : Chris Dewberry
Publisher : Routledge
Page : 365 pages
File Size : 40,5 Mb
Release : 2004-08-26
Category : Business & Economics
ISBN : 9781134314348
This clearly written textbook clarifies the concepts underpinning descriptive and inferential statistics in organizational research. Acting as much more than a theoretical reference tool, step-by-step it guides readers through the various key stages of successful data analysis. Covering everything from introductory descriptive statistics to advanced inferential techniques such as ANOVA, multiple and logistic regression and factor analysis, this is one of the most comprehensive textbooks available. Using examples directly relevant to organizational research it includes practical advice on such topics as the size of samples required in research studies, using and interpreting SPSS, and writing up results. In helping readers to develop a sound understanding of statistical methods, rather than focusing on complex formulas and computations, this outstanding textbook is as appropriate for those who wish to refresh their knowledge as those new to the subject area.
Author : Anders Hald
Publisher : Springer Science & Business Media
Page : 221 pages
File Size : 52,6 Mb
Release : 2008-08-24
Category : Mathematics
ISBN : 9780387464091
This book offers a detailed history of parametric statistical inference. Covering the period between James Bernoulli and R.A. Fisher, it examines: binomial statistical inference; statistical inference by inverse probability; the central limit theorem and linear minimum variance estimation by Laplace and Gauss; error theory, skew distributions, correlation, sampling distributions; and the Fisherian Revolution. Lively biographical sketches of many of the main characters are featured throughout, including Laplace, Gauss, Edgeworth, Fisher, and Karl Pearson. Also examined are the roles played by DeMoivre, James Bernoulli, and Lagrange.
Author : Kenneth J. Berry,Janis E. Johnston,Paul W. Mielke, Jr.
Publisher : Springer
Page : 476 pages
File Size : 52,5 Mb
Release : 2019-08-02
Category : Mathematics
ISBN : 9783030209339
The primary purpose of this textbook is to introduce the reader to a wide variety of elementary permutation statistical methods. Permutation methods are optimal for small data sets and non-random samples, and are free of distributional assumptions. The book follows the conventional structure of most introductory books on statistical methods, and features chapters on central tendency and variability, one-sample tests, two-sample tests, matched-pairs tests, one-way fully-randomized analysis of variance, one-way randomized-blocks analysis of variance, simple regression and correlation, and the analysis of contingency tables. In addition, it introduces and describes a comparatively new permutation-based, chance-corrected measure of effect size. Because permutation tests and measures are distribution-free, do not assume normality, and do not rely on squared deviations among sample values, they are currently being applied in a wide variety of disciplines. This book presents permutation alternatives to existing classical statistics, and is intended as a textbook for undergraduate statistics courses or graduate courses in the natural, social, and physical sciences, while assuming only an elementary grasp of statistics.