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Statistical implications of turing's formula
Features a broad introduction to recent research on Turing's formula and presents modern applications in statistics, probability, information theory, and other areas of modern data science Turing's formula is, perhaps, the only known method for estimating the underlying distributional characteristics beyond the range of observed data without.
eBook
Stochastics
This textbook, now in its second revised and extended edition, presents the fundamental ideas and results of both probability theory and statistics.It comprises the material of a one-year course, which is addressed to students of mathematics and to scientists with an interest in the mathematical side of stochastics.
eBook
Introductory Statistics: A Conceptual Approach Using R
This comprehensive and uniquely organized text is aimed at undergraduate and graduate level statistics courses in education, psychology, and other social sciences. A conceptual approach, built around common issues and problems rather than statistical techniques, allows students to understand the conceptual nature of statistical procedures and to focus more on cases and examples of analysis. Wherever possible, presentations contain explanations of the underlying reasons behind a technique. Importantly, this is one of the first statistics texts in the social sciences using R as the principal statistical package. Key features include the following.
Conceptual Focus - The focus throughout is more on conceptual understanding and attainment of statistical literacy and thinking than on learning a set of tools and procedures.
Problems and Cases - Chapters and sections open with examples of situations related to the forthcoming issues, and major sections ends with a case study. For example, after the section on describing relationships between variables, there is a worked case that demonstrates the analyses, presents computer output, and leads the student through an interpretation of that output.
Continuity of Examples - A master data set containing nearly all of the data used in the book's examples is introduced at the beginning of the text. This ensures continuity in the examples used across the text.
Companion Website - A companion website contains instructions on how to use R, SAS, and SPSS to solve the end-of-chapter exercises and offers additional exercises.
Field Tested - The manuscript has been field tested for three years at two leading institutions.
eBook
Probability
Praise for the First Edition
\"This is a well-written and impressively presented introduction to probability and statistics. The text throughout is highly readable, and the author makes liberal use of graphs and diagrams to clarify the theory.\" - The Statistician
Thoroughly updated, Probability: An Introduction with Statistical Applications, Second Edition features a comprehensive exploration of statistical data analysis as an application of probability. The new edition provides an introduction to statistics with accessible coverage of reliability, acceptance sampling, confidence intervals, hypothesis testing, and simple linear regression. Encouraging readers to develop a deeper intuitive understanding of probability, the author presents illustrative geometrical presentations and arguments without the need for rigorous mathematical proofs.
The Second Edition features interesting and practical examples from a variety of engineering and scientific fields, as well as:
* Over 880 problems at varying degrees of difficulty allowing readers to take on more challenging problems as their skill levels increase
* Chapter-by-chapter projects that aid in the visualization of probability distributions
* New coverage of statistical quality control and quality production
* An appendix dedicated to the use of Mathematica® and a companion website containing the referenced data sets
Featuring a practical and real-world approach, this textbook is ideal for a first course in probability for students majoring in statistics, engineering, business, psychology, operations research, and mathematics. Probability: An Introduction with Statistical Applications, Second Edition is also an excellent reference for researchers and professionals in any discipline who need to make decisions based on data as well as readers interested in learning how to accomplish effective decision making from data.
eBook
Univariate, bivariate, and multivariate statistics using R : quantitative tools for data analysis and data science
A practical source for performing essential statistical analyses and data management tasks in R Univariate, Bivariate, and Multivariate Statistics Using R offers a practical and very user-friendly introduction to the use of R software that covers a range of statistical methods featured in data analysis and data science.
eBook
Statistical inference
A concise, easily accessible introduction to descriptive and inferential techniques Statistical Inference: A Short Course offers a concise presentation of the essentials of basic statistics for readers seeking to acquire a working knowledge of statistical concepts, measures, and procedures.
eBook
Endocrine Manifestations of Systemic Autoimmune Diseases
This book is one of the first to evaluate the role of Steroids in autoimmune rheumatic diseases from the basic mechanisms to the clinical involvements and focuses on the importance of steroidal hormones in the pathogenesis and therapeutic management of the autoimmune rheumatic diseases.
eBook
Advanced statistics from an elementary point of view
The highly readable text captures the flavor of a course in mathematical statistics without imposing too much rigor; students can concentrate on the statistical strategies without getting lost in the theory. Students who use this book will be well on their way to thinking like a statistician. Practicing statisticians will find this book useful in that it is replete with statistical test procedures (both parametric and non-parametric) as well as numerous detailed examples. · Comprehensive coverage of descriptive statistics· More detailed treatment of univariate and bivariate probability distributions· Thorough coverage of probability theory with numerous event classifications
eBook