Living Without Mathematical Statistics
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Author | : Herbert Ruefer |
Publisher | : Springer |
Total Pages | : 507 |
Release | : 2018-09-28 |
Genre | : Technology & Engineering |
ISBN | : 3319996320 |
The underlying principles invented and developed by Dr. Genichi Taguchi (1924 - 2012), for the design of experiments or simulation calculations in multi-parameter systems, are today known as Taguchi Method. Due to the great success, it was extended to many other areas. The book explains the basics of this method in as much detail as necessary and as simply and graphically as possible. The author shows how broad the current application spectrum is and for which different tasks it can be used. The application examples range from optimizing a fermentation process in biotechnology to minimizing costs in mechanical production and maintaining and improving competitiveness in industrial production. The processes described are ideally suited to finding reliable and precise solutions for a wide variety of problems relatively quickly. A real competitive advantage not only in research but also for companies that want to remain competitive in international business competition. Contents Part 1: Analysis of Variables Part 2: Pattern Recognition and Diagnosis Part 3: Prognosis Target groups Students, scientists, engineers or those responsible for development and products learn to use the Taguchi Method with this book - even without any previous mathematical-statistical knowledge. The author Herbert Ruefer studied physics and obtained his doctorate at the Technical University Karlsruhe, Germany. After a research stay at IBM, San Jose, California, he taught at the San Marcos National University in Lima, Peru. He then took on research, development, and training tasks in the chemical industry in Germany. During this time, the first personal contacts with Dr. Genichi Taguchi and Dr. Yuin Wu took place. After his active professional life, he dedicated himself to special optical methods for astronomical observations. He also lectures at the Universidad Nacional Mayor de San Marcos which awarded him an honorary doctorate in 2017.
Author | : Herbert Ruefer |
Publisher | : |
Total Pages | : 507 |
Release | : 2019 |
Genre | : Engineering mathematics |
ISBN | : 9783319996332 |
The book provides structured access to gaining accurate results of limited data applicable to science, technology, and manufacturing. The Taguchi Method is presented in every detail and also put into practice. The basic principle was developed in the 1950's. Dr. Genichi Taguchi (1924 to 2012) kept perfecting his method until 2006, and it has been brought up-to-date until now. The main purpose of this book is to make the above knowledge available to a wide range of people of different backgrounds, regardless of their fields of expertise.
Author | : William E. Magnusson |
Publisher | : Sinauer Associates Incorporated |
Total Pages | : 136 |
Release | : 2004 |
Genre | : Science |
ISBN | : 9780878935062 |
Statistics without Math is not your typical statistics book; nor is it designed to serve as a substitute for conventional statistical texts. Experience with ecology students and researchers has shown that too much mathematical detail diverts attention away from basic logical concepts, resulting in errors in sampling design, data analysis, and comprehension of the ecological literature. Hence, this book starts with real-world observations and explains how statistics may be used as a practical tool to answer questions about them, and to clearly communicate these results. The book targets intermediate-level statistics (given short shrift in most books and courses), and teaches concepts with a minimum of mathematical detail, instead using simple graphs and, where necessary, analogy. This approach, class-tested for many years by the authors, has revolutionized students' ability to understand statistics.
Author | : Jordan Ellenberg |
Publisher | : Penguin Press |
Total Pages | : 480 |
Release | : 2014-05-29 |
Genre | : Mathematics |
ISBN | : 1594205221 |
A brilliant tour of mathematical thought and a guide to becoming a better thinker, How Not to Be Wrong shows that math is not just a long list of rules to be learned and carried out by rote. Math touches everything we do; It's what makes the world make sense. Using the mathematician's methods and hard-won insights-minus the jargon-professor and popular columnist Jordan Ellenberg guides general readers through his ideas with rigor and lively irreverence, infusing everything from election results to baseball to the existence of God and the psychology of slime molds with a heightened sense of clarity and wonder. Armed with the tools of mathematics, we can see the hidden structures beneath the messy and chaotic surface of our daily lives. How Not to Be Wrong shows us how--Publisher's description.
Author | : Victor M. Panaretos |
Publisher | : Birkhäuser |
Total Pages | : 190 |
Release | : 2016-06-01 |
Genre | : Mathematics |
ISBN | : 3319283413 |
This textbook provides a coherent introduction to the main concepts and methods of one-parameter statistical inference. Intended for students of Mathematics taking their first course in Statistics, the focus is on Statistics for Mathematicians rather than on Mathematical Statistics. The goal is not to focus on the mathematical/theoretical aspects of the subject, but rather to provide an introduction to the subject tailored to the mindset and tastes of Mathematics students, who are sometimes turned off by the informal nature of Statistics courses. This book can be used as the basis for an elementary semester-long first course on Statistics with a firm sense of direction that does not sacrifice rigor. The deeper goal of the text is to attract the attention of promising Mathematics students.
Author | : Larry Wasserman |
Publisher | : Springer Science & Business Media |
Total Pages | : 446 |
Release | : 2013-12-11 |
Genre | : Mathematics |
ISBN | : 0387217363 |
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Author | : Kit Yates |
Publisher | : Simon and Schuster |
Total Pages | : 288 |
Release | : 2021-04-27 |
Genre | : MATHEMATICS |
ISBN | : 1982111887 |
"Few of us really appreciate the full power of math--the extent to which its influence is not only in every office and every home, but also in every courtroom and hospital ward. In this ... book, Kit Yates explores the true stories of life-changing events in which the application--or misapplication--of mathematics has played a critical role: patients crippled by faulty genes and entrepreneurs bankrupted by faulty algorithms; innocent victims of miscarriages of justice; and the unwitting victims of software glitches"--Publisher marketing.
Author | : Brian Albright |
Publisher | : Jones & Bartlett Publishers |
Total Pages | : 607 |
Release | : 2014 |
Genre | : Mathematics |
ISBN | : 144968534X |
This text combines the topics generally found in main-stream elementary statistics books with the essentials of the underlying theory. The book begins with an axiomatic treatment of probability followed by chapters on discrete and continuous random variables and their associated distributions. It then introduces basic statistical concepts including summarizing data and interval parameter estimation, stressing the connection between probability and statistics. Final chapters introduce hypothesis testing, regression, and non-parametric techniques. All chapters provide a balance between conceptual understanding and theoretical understanding of the topics at hand.
Author | : David J. Bartholomew |
Publisher | : SAGE |
Total Pages | : 193 |
Release | : 2015-10-19 |
Genre | : Social Science |
ISBN | : 1473934338 |
This is a book about the ideas that drive statistics. It is an ideal primer for students who need an introduction to the concepts of statistics without the added confusion of technical jargon and mathematical language. It introduces the intuitive thinking behind standard procedures, explores the process of informal reasoning, and uses conceptual frameworks to provide a foundation for students new to statistics. It showcases the expertise we have all developed from living in a data saturated society, increases our statistical literacy and gives us the tools needed to approach statistical mathematics with confidence. Key topics include: Variability Standard Distributions Correlation Relationship Sampling Inference An engaging, informal introduction this book sets out the conceptual tools required by anyone undertaking statistical procedures for the first time or for anyone needing a fresh perspective whilst studying the work of others.
Author | : Rebecca M. Warner |
Publisher | : SAGE Publications |
Total Pages | : 649 |
Release | : 2020-01-14 |
Genre | : Psychology |
ISBN | : 1506352790 |
Applied Statistics I: Basic Bivariate Techniques has been created from the first half of Rebecca M. Warner's popular Applied Statistics: From Bivariate Through Multivariate Techniques. The author's contemporary approach differs from some of the well-worn texts in the market, and reflects current thinking in the field. It spends less time on statistical significance testing, and moves in the direction of the "new statistics" by focusing more on confidence intervals and effect size. Instructors of upper undergraduate or beginning graduate level courses will find that the greater focus on basic concepts such as partition of variance and effect size is more useful to students, particularly as preparation for more advanced courses. Spending less time on statistical significance testing allows for more time to be devoted to more interesting and useful statistics that students will see in journal articles (such as correlation and regression). This introductory statistics text includes examples in SPSS, together with datasets on an accompanying website. A companion study guide reproducing the exercises and examples in R will also be available.