R.A. Fisher: An Appreciation

R.A. Fisher: An Appreciation
Author: Stephen E. Fienberg
Publisher: Springer Science & Business Media
Total Pages: 219
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461260795

From the reviews: "This collection of essays surveys the most important of Fisher's papers in various areas of statistics. ... ... the monograph will be a useful source of reference to most of Fisher's major papers; it will certainly provide background material for much vigorous discussion." #Australian Journal of Statistics#1

R. A. Fisher, the Life of a Scientist

R. A. Fisher, the Life of a Scientist
Author: Joan Fisher Box
Publisher: John Wiley & Sons
Total Pages: 560
Release: 1978
Genre: Biography & Autobiography
ISBN:

Nature and nurture; In the wilderness; Mathematical statistics; Rothamsted Experimental Station; Tests of significance; The design of experiments; The genetical theory of natural selection; The evolution of dominance; The role of a statistician; Galton Professor of Eugenics; Evolutionary ideas; In the United States and India; Blood groups in man; Losses of war; Arthur Balfour Professor of genetics; The biometrical movement; Scientific inference; Retirement.

Experimental Design and Analysis

Experimental Design and Analysis
Author: Steven R. Brown
Publisher: SAGE
Total Pages: 102
Release: 1990
Genre: Social Science
ISBN: 9780803938540

Experimental design is one of the most fundamental topics in social science statistics. This book introduces the reader to the elements of experimental design and analysis through careful explanations of the procedures as well as through illustrations using actual examples.

The Lady Tasting Tea

The Lady Tasting Tea
Author: David Salsburg
Publisher: Henry Holt and Company
Total Pages: 356
Release: 2002-05-01
Genre: Mathematics
ISBN: 1466801786

An insightful, revealing history of the magical mathematics that transformed our world. The Lady Tasting Tea is not a book of dry facts and figures, but the history of great individuals who dared to look at the world in a new way. At a summer tea party in Cambridge, England, a guest states that tea poured into milk tastes different from milk poured into tea. Her notion is shouted down by the scientific minds of the group. But one man, Ronald Fisher, proposes to scientifically test the hypothesis. There is no better person to conduct such an experiment, for Fisher is a pioneer in the field of statistics. The Lady Tasting Tea spotlights not only Fisher's theories but also the revolutionary ideas of dozens of men and women which affect our modern everyday lives. Writing with verve and wit, David Salsburg traces breakthroughs ranging from the rise and fall of Karl Pearson's theories to the methods of quality control that rebuilt postwar Japan's economy, including a pivotal early study on the capacity of a small beer cask at the Guinness brewing factory. Brimming with intriguing tidbits and colorful characters, The Lady Tasting Tea salutes the spirit of those who dared to look at the world in a new way.

Fisher, Neyman, and the Creation of Classical Statistics

Fisher, Neyman, and the Creation of Classical Statistics
Author: Erich L. Lehmann
Publisher: Springer Science & Business Media
Total Pages: 123
Release: 2011-07-25
Genre: Mathematics
ISBN: 1441995005

Classical statistical theory—hypothesis testing, estimation, and the design of experiments and sample surveys—is mainly the creation of two men: Ronald A. Fisher (1890-1962) and Jerzy Neyman (1894-1981). Their contributions sometimes complemented each other, sometimes occurred in parallel, and, particularly at later stages, often were in strong opposition. The two men would not be pleased to see their names linked in this way, since throughout most of their working lives they detested each other. Nevertheless, they worked on the same problems, and through their combined efforts created a new discipline. This new book by E.L. Lehmann, himself a student of Neyman’s, explores the relationship between Neyman and Fisher, as well as their interactions with other influential statisticians, and the statistical history they helped create together. Lehmann uses direct correspondence and original papers to recreate an historical account of the creation of the Neyman-Pearson Theory as well as Fisher’s dissent, and other important statistical theories.

Information and Exponential Families

Information and Exponential Families
Author: O. Barndorff-Nielsen
Publisher: John Wiley & Sons
Total Pages: 248
Release: 2014-05-07
Genre: Mathematics
ISBN: 1118857372

First published by Wiley in 1978, this book is being re-issued with a new Preface by the author. The roots of the book lie in the writings of RA Fisher both as concerns results and the general stance to statistical science, and this stance was the determining factor in the author's selection of topics. His treatise brings together results on aspects of statistical information, notably concerning likelihood functions, plausibility functions, ancillarity, and sufficiency, and on exponential families of probability distributions.

The Book of R

The Book of R
Author: Tilman M. Davies
Publisher: No Starch Press
Total Pages: 833
Release: 2016-07-16
Genre: Computers
ISBN: 1593276516

The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.

Statistics Done Wrong

Statistics Done Wrong
Author: Alex Reinhart
Publisher: No Starch Press
Total Pages: 177
Release: 2015-03-01
Genre: Mathematics
ISBN: 1593276206

Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: –Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan –How to think about p values, significance, insignificance, confidence intervals, and regression –Choosing the right sample size and avoiding false positives –Reporting your analysis and publishing your data and source code –Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong.