Download or read book Introductory Statistics for Engineering Experimentation written by Peter R. Nelson and published by Academic Press. This book was released on 2003-08-14 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise treatment for undergraduate and graduate students who need a guide to statistics that focuses specifically on engineering.
Download or read book Statistics for Technology written by Chris Chatfield and published by Routledge. This book was released on 2018-02-19 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the most popular introductory texts in its field, Statistics for Technology: A Course in Applied Studies presents the range of statistical methods commonly used in science, social science, and engineering.The mathematics are simple and straightforward; statistical concepts are explained carefully; and real-life (rather than contrived) examples are used throughout the chapters.Divided into three parts, the Introduction describes some simple methods of summarizing data. Theory examines the basic concepts and theory of statistics. Applications covers the planning and procedures of experiments, quality control, and life testing.Revised throughout, this Third Edition places a higher priority on the role of computers in analysis, and many new references have been incorporated. A new appendix describes general methods of tackling statistical problems, including guidance on literature searching and report writing.
Download or read book Statistics for Data Scientists written by Maurits Kaptein and published by Springer Nature. This book was released on 2022-02-02 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science students. It uniquely combines a hands-on approach to data analysis – supported by numerous real data examples and reusable [R] code – with a rigorous treatment of probability and statistical principles. Where contemporary undergraduate textbooks in probability theory or statistics often miss applications and an introductory treatment of modern methods (bootstrapping, Bayes, etc.), and where applied data analysis books often miss a rigorous theoretical treatment, this book provides an accessible but thorough introduction into data analysis, using statistical methods combining the two viewpoints. The book further focuses on methods for dealing with large data-sets and streaming-data and hence provides a single-course introduction of statistical methods for data science.
Download or read book Science and Technology in World History written by James Edward McClellan and published by JHU Press. This book was released on 2006 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher description
Download or read book Introduction to Probability and Statistics for Data Scientists with R written by Ronald D. Fricker, Jr. and published by CreateSpace. This book was released on 2014-05-25 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first three chapters of a textbook for data scientists who want to improve how they work with, analyze, and extract information from data. The focus of the textbook is how to appropriately apply statistical methods, both simple and sophisticated, to 21st century data and problems. This book contains the first three chapters: Introduction -- Data Science and Statistics, Descriptive Statistics, and Data Visualization -- as well as the book front matter. Subsequent chapters will be published in 3- to 5-chapter sets as they become available.The textbook is intended for current and future data scientists, and for anyone interested in deriving information from data. It requires some mathematical sophistication on the part of the reader, as well as comfort using computers and statistical software.Data science is a new field that has arisen to exploit the proliferation of data in the modern world. Mathematical statistics dates back to the mid-18th century, where the field began as the systematic collection of population and economic data by nations. The modern practice of statistics – which includes the collection, summarization, and analysis of data – dates to the early 20th century. Today statistical methods are widely used by governments, businesses and other organizations, as well as by all scientific disciplines.It has been said that a data scientist must have a better grasp of statistics than the average computer scientist and a better grasp of programming than the average statistician. This book will give data scientists a firm foundation in statistics.
Download or read book Statistics for Technology written by Christopher Chatfield and published by Chapman & Hall. This book was released on 1978 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the most popular introductory texts in its field, Statistics for Technology: A Course in Applied Studies presents the range of statistical methods commonly used in science, social science, and engineering.The mathematics are simple and straightforward; statistical concepts are explained carefully; and real-life (rather than contrived) examples are used throughout the chapters.Divided into three parts, the Introduction describes some simple methods of summarizing data. Theory examines the basic concepts and theory of statistics. Applications covers the planning and procedures of experiments, quality control, and life testing.Revised throughout, this Third Edition places a higher priority on the role of computers in analysis, and many new references have been incorporated. A new appendix describes general methods of tackling statistical problems, including guidance on literature searching and report writing.
Download or read book Introduction to Probability and Statistics for Engineers and Scientists written by Sheldon M. Ross and published by . This book was released on 1987 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elements of probability; Random variables and expectation; Special; random variables; Sampling; Parameter estimation; Hypothesis testing; Regression; Analysis of variance; Goodness of fit and nonparametric testing; Life testing; Quality control; Simulation.
Download or read book A Hands On Introduction to Data Science written by Chirag Shah and published by Cambridge University Press. This book was released on 2020-04-02 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introductory textbook offering a low barrier entry to data science; the hands-on approach will appeal to students from a range of disciplines.
Download or read book Introductory Statistics written by Openstax and published by . This book was released on 2022-03-23 with total page 914 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introductory Statistics follows scope and sequence requirements of a one-semester introduction to statistics course and is geared toward students majoring in fields other than math or engineering. The text assumes some knowledge of intermediate algebra and focuses on statistics application over theory. Introductory Statistics includes innovative practical applications that make the text relevant and accessible, as well as collaborative exercises, technology integration problems, and statistics labs. Senior Contributing Authors Barbara Illowsky, De Anza College Susan Dean, De Anza College Contributing Authors Daniel Birmajer, Nazareth College Bryan Blount, Kentucky Wesleyan College Sheri Boyd, Rollins College Matthew Einsohn, Prescott College James Helmreich, Marist College Lynette Kenyon, Collin County Community College Sheldon Lee, Viterbo University Jeff Taub, Maine Maritime Academy
Download or read book An Introduction to Statistical Genetic Data Analysis written by Melinda C. Mills and published by MIT Press. This book was released on 2020-02-18 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to modern applied statistical genetic data analysis, accessible to those without a background in molecular biology or genetics. Human genetic research is now relevant beyond biology, epidemiology, and the medical sciences, with applications in such fields as psychology, psychiatry, statistics, demography, sociology, and economics. With advances in computing power, the availability of data, and new techniques, it is now possible to integrate large-scale molecular genetic information into research across a broad range of topics. This book offers the first comprehensive introduction to modern applied statistical genetic data analysis that covers theory, data preparation, and analysis of molecular genetic data, with hands-on computer exercises. It is accessible to students and researchers in any empirically oriented medical, biological, or social science discipline; a background in molecular biology or genetics is not required. The book first provides foundations for statistical genetic data analysis, including a survey of fundamental concepts, primers on statistics and human evolution, and an introduction to polygenic scores. It then covers the practicalities of working with genetic data, discussing such topics as analytical challenges and data management. Finally, the book presents applications and advanced topics, including polygenic score and gene-environment interaction applications, Mendelian Randomization and instrumental variables, and ethical issues. The software and data used in the book are freely available and can be found on the book's website.
Download or read book An Introduction to Science and Technology Studies written by Sergio Sismondo and published by John Wiley & Sons. This book was released on 2011-08-17 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Science and Technology Studies, Second Edition reflects the latest advances in the field while continuing to provide students with a road map to the complex interdisciplinary terrain of science and technology studies. Distinctive in its attention to both the underlying philosophical and sociological aspects of science and technology Explores core topics such as realism and social construction, discourse and rhetoric, objectivity, and the public understanding of science Includes numerous empirical studies and illustrative examples to elucidate the topics discussed Now includes new material on political economies of scientific and technological knowledge, and democratizing technical decisions Other features of the new edition include improved readability, updated references, chapter reorganization, and more material on medicine and technology
Download or read book Big Data and Social Science written by Ian Foster and published by CRC Press. This book was released on 2016-08-10 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.
Download or read book Introduction to Glass Science and Technology written by James E Shelby and published by Royal Society of Chemistry. This book was released on 2015-11-06 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a concise and inexpensive introduction for an undergraduate course in glass science and technology. The level of the book has deliberately been maintained at the introductory level to avoid confusion of the student by inclusion of more advanced material, and is unique in that its text is limited to the amount suitable for a one term course for students in materials science, ceramics or inorganic chemistry. The contents cover the fundamental topics of importance in glass science and technology, including glass formation, crystallization, phase separation and structure of glasses. Additional chapters discuss the most important properties of glasses, including discussion of physical, optical, electrical, chemical and mechanical properties. A final chapter provides an introduction to a number of methods used to form technical glasses, including glass sheet, bottles, insulation fibre, optical fibres and other common commercial products. In addition, the book contains discussion of the effects of phase separation and crystallization on the properties of glasses, which is neglected in other texts. Although intended primarily as a textbook, Introduction to Glass Science and Technology will also be invaluable to the engineer or scientist who desires more knowledge regarding the formation, properties and production of glass.
Download or read book Human Centered Data Science written by Cecilia Aragon and published by MIT Press. This book was released on 2022-03-01 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets. Human-centered data science is a new interdisciplinary field that draws from human-computer interaction, social science, statistics, and computational techniques. This book, written by founders of the field, introduces best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of very large datasets. It offers a brief and accessible overview of many common statistical and algorithmic data science techniques, explains human-centered approaches to data science problems, and presents practical guidelines and real-world case studies to help readers apply these methods. The authors explain how data scientists’ choices are involved at every stage of the data science workflow—and show how a human-centered approach can enhance each one, by making the process more transparent, asking questions, and considering the social context of the data. They describe how tools from social science might be incorporated into data science practices, discuss different types of collaboration, and consider data storytelling through visualization. The book shows that data science practitioners can build rigorous and ethical algorithms and design projects that use cutting-edge computational tools and address social concerns.
Download or read book Introductory Statistics for the Behavioral Sciences written by Joan Welkowitz and published by Academic Press. This book was released on 1976 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: * New chapters on multiple comparisons and repeated-measures ANOVA
Download or read book An Introduction to Data Science written by Jeffrey S. Saltz and published by SAGE Publications. This book was released on 2017-08-25 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Data Science by Jeffrey S. Saltz and Jeffrey M. Stanton is an easy-to-read, gentle introduction for people with a wide range of backgrounds into the world of data science. Needing no prior coding experience or a deep understanding of statistics, this book uses the R programming language and RStudio® platform to make data science welcoming and accessible for all learners. After introducing the basics of data science, the book builds on each previous concept to explain R programming from the ground up. Readers will learn essential skills in data science through demonstrations of how to use data to construct models, predict outcomes, and visualize data.
Download or read book Probability with Applications in Engineering Science and Technology written by Matthew A. Carlton and published by Springer. This book was released on 2014-09-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a contemporary and lively postcalculus introduction to the subject of probability. The exposition reflects a desirable balance between fundamental theory and many applications involving a broad range of real problem scenarios. It is intended to appeal to a wide audience, including mathematics and statistics majors, prospective engineers and scientists, and those business and social science majors interested in the quantitative aspects of their disciplines. A one-term course would cover material in the core chapters (1-4), hopefully supplemented by selections from one or more of the remaining chapters on statistical inference (Ch. 5), Markov chains (Ch. 6), stochastic processes (Ch. 7), and signal processing (Ch. 8). The last chapter is specifically designed for electrical and computer engineers, making the book suitable for a one-term class on random signals and noise. Alternatively, there is certainly enough material for those lucky enough to be teaching or taking a year-long course. Most of the core will be accessible to those who have taken a year of univariate differential and integral calculus; matrix algebra, multivariate calculus, and engineering mathematics are needed for the later, more advanced chapters. One unique feature of this book is the inclusion of sections that illustrate the importance of software for carrying out simulations when answers to questions cannot be obtained analytically; R and Matlab code are provided so that students can create their own simulations. Another feature that sets this book apart is the Introduction, which addresses the question “Why study probability?” by surveying selected examples from recent journal articles and discussing some classic problems whose solutions run counter to intuition. The book contains about 1100 exercises, ranging from straightforward to reasonably challenging; roughly 700 of these appear in the first four chapters. The book’s preface provides more information about our purpose, content, mathematical level, and suggestions for what can be covered in courses of varying duration.
