2nd Edition. — Springer Gabler Wiesbaden, 2023. — 607 p. — eBook ISBN: 978-3-658-32589-3. Offers an easy-to-understand introduction to the most relevant methods of multivariate data analysis. Illustrates each method via a case study solved with SPSS. Interactive flashcards are available to the reader for reviewing selected focal points. Data can be extremely valuable if we are...
Springer, 2021. — 667 p. — ISBN 978-3-030-74360-4. This book takes a unique approach to explaining permutation statistics by integrating permutation statistical methods with a wide range of classical statistical methods and associated R programs. It opens by comparing and contrasting two models of statistical inference: the classical population model espoused by J. Neyman and...
2nd edition. — O’Reilly Media, 2012. — 1248 p. — ISBN 9781449316921. Need to learn statistics for your job? Want help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference for anyone new to the subject. Thoroughly revised and expanded, this edition helps you gain a solid understanding of statistics without the numbing complexity...
Philadelphia: SAGE Publications, 1996. — 88 p. What techniques can social scientists use when an outcome variable for a sample is not representative of the population for whom they would like to generalize the results? This book provides an introduction to regression models for such data including censored, sample-selected and truncated data.
SAGE Publications, 2021. — 616 р. — ISBN 978-1544333861. Designed to introduce students to quantitative methods in a way that can be applied to all kinds of data in all kinds of situations, Statistics and Data Visualization Using R: The Art and Practice of Data Analysis by David S. Brown teaches students statistics through charts, graphs, and displays of data that help students...
Wiley, 2020. — 245 p. — ISBN 9781119549802. Evidence-Based Statistics: An Introduction to the Evidential Approach – from Likelihood Principle to Statistical Practice provides readers with a comprehensive and thorough guide to the evidential approach in statistics. The approach uses likelihood ratios, rather than the probabilities used by other statistical inference approaches....
Rowman & Littlefield Publishers, 2023. — 135 p. Упрощение статистики для аспирантов: сделать использование данных простым и удобным для пользователя One of the greatest barriers to completing a graduate thesis or a doctoral dissertation is statistics. Oftentimes, the journey through graduate school is gratifying when the content courses in the chosen field of study are...
New York: Apress, 2017. — 329 p. Examine and solve the common misconceptions and fallacies that non-statisticians bring to their interpretation of statistical results. Explore the many pitfalls that non-statisticians—and also statisticians who present statistical reports to non-statisticians—must avoid if statistical results are to be correctly used for evidence-based business...
Springer Nature Singapore Pte Ltd., 2018. — 357 p. — (Signals and Communication Technology) — ISBN: 9811075921. This book offers a detailed description of the histogram probabilistic multi-hypothesis tracker (H-PMHT), providing an accessible and intuitive introduction to the mathematical mechanics of H-PMHT as well as a definitive reference source for the existing literature on...
5th edition. — Pearson, 2020. — 1024 p. — ISBN13: 978-0135163825. For courses in Introductory Statistics. Encourages statistical thinking using technology, innovative methods, and a sense of humor. Inspired by the 2016 GAISE Report revision, Stats: Data and Models, 5th Edition by De Veaux/Velleman/Bock uses innovative strategies to help students think critically about data —...
Wiley, 2023. — 240 p. — ISBN-13: 978-1119891796. M-STATISTICS A comprehensive resource providing new statistical methodologies and demonstrating how new approaches work for applications M-statistics introduces a new approach to statistical inference, redesigning the fundamentals of statistics, and improving on the classical methods we already use. This book targets exact...
New York: Morgan & Claypool, 2020. — 181 p. Many people find statistics confusing, and perhaps even more confusing given recent publicity about problems with traditional p-values and alternative statistical techniques including confidence intervals and Bayesian statistics. This book aims to help readers navigate this morass: to understand the debates, to be able to read and...
Springer, Singapore, 2022. — 190 p. — ISBN 978-981-19-0972-6. This book provides methods and applications of latent class analysis, and the following topics are taken up in the focus of discussion: basic latent structure models in a framework of generalized linear models, exploratory latent class analysis, latent class analysis with ordered latent classes, a latent class model...
Springer, 2021. — 410 p. — ISBN 978-3-030-71174-0. This book presents modern methods and real-world applications of compositional data analysis. It covers a wide variety of topics, ranging from an updated presentation of basic concepts and ideas in compositional data analysis to recent advances in the context of complex data structures. Further, it illustrates real-world...
Independently published, 2015. — 58 p. — ASIN B013HNBQSG. Many introductory books about principal component (PC) analysis using R have been published. These books describe how to use the princomp() function of R. The unique feature of this book is that it explains step-by-step the background theory of the princomp() function and helps readers identify PCs using examples ranging...
Springer, 2018. — 284 p. — ISBN: 3662573784. This comprehensive and richly illustrated volume provides up-to-date material on Singular Spectrum Analysis (SSA). SSA is a well-known methodology for the analysis and forecasting of time series. Since quite recently, SSA is also being used to analyze digital images and other objects that are not necessarily of planar or rectangular...
4 ed. — John Wiley & Sons, 2012. — 336 p. — ISBN: 978-1-118-29439-0. Common Errors in Statistics (and How to Avoid Them), Fourth Edition provides a mathematically rigorous, yet readily accessible foundation in statistics for experienced readers as well as students learning to design and complete experiments, surveys, and clinical trials. Providing a consistent level of...
3rd Ed. — Chapman and Hall/CRC, 2016. — 403 p. — (Chapman & Hall/CRC Interdisciplinary Statistics). — ISBN10: 1498731775. — ISBN13: 978-1498731775. Drawing on the author’s 45 years of experience in multivariate analysis, Correspondence Analysis in Practice, Third Edition, shows how the versatile method of correspondence analysis (CA) can be used for data visualization in a wide...
CRC Press, 2022. — 529 p. — (Time Series for Data Science). — ISBN 978-0-367-54389-1. Временные ряды для науки о данных: анализ и прогнозирование Data Science students and practitioners want to find a forecast that “works” and don’t want to be constrained to a single forecasting strategy, Time Series for Data Science: Analysis and Forecasting discusses techniques of ensemble...
Springer, 2021. — 350 p. — ISBN 978-3-030-74651-3. This book provides a comprehensive and concrete illustration of time series analysis focusing on the state-space model, which has recently attracted increasing attention in a broad range of fields. The major feature of the book lies in its consistent Bayesian treatment regarding whole combinations of batch and sequential...
amazon.com, 2017. — 213 p. If you are looking for a short beginners guide packed with visual examples, this book is for you. Linear Regression is a way of simplifying a group of data into a single equation. For instance, we all know Moore’s law: that the number of transistors on a computer chip doubles every two years. This law was derived by using regression analysis to...
2nd edition. — Springer Nature Switzerland AG, 2022. — 336 p. — (Statistics and Computing). — eBook ISBN 978-3-030-97371-1. Now in its second edition, this textbook provides an introduction to Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from...
Springer, 2022. — 338 p. — (ICSA Book Series in Statistics). — ISBN 978-3-031-08328-0. This book covers a variety of topics, including methodology development in Data Science, such as methodology in the analysis of high dimensional data, feature screening in ultra-high dimensional data and natural language ranking; statistical analysis challenges in sampling, multivariate...
Springer, 2022. — 94 p. — (Synthesis Lectures on Mathematics & Statistics). — ISBN 978-3-031-04201-0. Статистическая проверка гипотез с помощью Microsoft Office Excel This book provides a comprehensive treatment of the logic behind hypothesis testing. Readers will learn to understand statistical hypothesis testing and how to interpret P-values under a variety of conditions...
Springer, 2023. — 310 p. — (Springer Series in Reliability Engineering). — ISBN 978-3-031-21231-4. This book discusses practical applications of reliability and statistical methods and techniques in various disciplines, using Machine Learning, Artificial Intelligence, optimization, and other computation methods. Bringing together research from international experts, each...
Birmingham, UK: Packt Publishing, 2019. — 448 p. — (Mathematical & Statistical Software). — ISBN 978-1-78980-256-6. Solve real-world statistical problems using the most popular R packages and techniques. This book will be a useful guide to solving common and not-so-common challenges in statistics. With this book, you'll be equipped to confidently perform essential statistical...
Springer, 2011. — 118 p. — (Springer Briefs in statistics) — ISBN: 978-3-642-23502-3. The text gives a concise introduction into fundamental concepts in statistics. Chapter 1: Short exposition of probability theory, using generic examples. Chapter 2: Estimation in theory and practice, using biologically motivated examples. Maximum-likelihood estimation in covered, including...
Springer, 2021. — 307 p. — ISBN 978-981-16-0621-2. This book discusses all major topics on survey sampling and estimation. It covers traditional as well as advanced sampling methods related to the spatial populations. The book presents real-world applications of major sampling methods and illustrates them with the R software. As a large sample size is not cost-efficient, this...
Independently published, 2021. — 134 p. — ASIN B091K3XT8G. This text will provide guidance for anyone who has difficulty in doing their research work particularly research that involved the use of statistical methods. Introduction and Purpose T-Test Statistic Analysis of Variance (ANOVA) Correlation Analysis Linear and Multiple Regression Analysis Chi-Square Statistic...
3rd Edition. — Pearson Education, Inc., 2015. — 384 p. — ISBN 0-13-338266-4-13, 978-0-13-338266-2. In today’s world, understanding statistics and analytics is more important than ever. Even You Can Learn Statistics and Analytics: A Guide for Everyone Who Has Ever Been Afraid of Statistics and Analytics can teach you the basic concepts that provide you with the knowledge to...
Cambridge: Cambridge University Press, 2018. — 474 p. Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of...
Springer, 2023. — 415 р. — (Springer Series in Statistics). — ISBN 978-3-031-14275-8. The first half of the book is aimed at quantitative research workers in biology, medicine, ecology and genetics. The book as a whole is aimed at graduate students in statistics, biostatistics, and other quantitative disciplines. Ten detailed examples show how the author approaches real-world...
Independently published, 2022. — 315 р. The Most Basic Approach To Learn, Create And Analyze Data, Charts, Tables With Helpful Tricks For Both Beginners And Pros. The world of Excel is a large one especially filled with all of the special functions for your special duty. Now if you are an Excel enthusiast, you are going to agree with me that Excel gets deep and extensive. The...
2nd ed. — CRC, 2019. — 811 p. — ISBN: 9781439895474. Engineers are expected to design structures and machines that can operate in challenging and volatile environments, while allowing for variation in materials and noise in measurements and signals. Statistics in Engineering, Second Edition: With Examples in MatLAB and R covers the fundamentals of probability and statistics and...
New York: Dover Publications, 2013. — 608 p. This introduction to the world of statistics draws examples from a broad range of applications, including business, government, medicine, social sciences, biology, and everyday life. The first four chapters present a brief course in exploratory data analysis. The authors place special emphasis on methods for collecting data and offer an...
5th edition. — McGraw-Hill Education, 2020. — 2023 p. — ISBN 978-1-260-54788-7. Statistics for Engineers and Scientists stands out for its crystal clear presentation of applied statistics and probability. The book takes a practical approach to methods of statistical modeling and data analysis that are often used in scientific work. An engaging writing style coupled with real...
6th edition. — McGraw-Hill Education, 204. — 961 p. — ISBN 9781265877972. Statistics for Engineers and Scientists stands out for its clear presentation of applied statistics. The book takes a practical approach to methods of statistical modeling and data analysis that are most often used in scientific work. This edition features a unique approach highlighted by an engaging...
2nd Edition. — Springer, 2023. — 1175 p. — ISBN 978-1-4471-7503-2. In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them to gain sensible...
John Wiley & Sons, 2020. — 503 p. — ISBN: 978-1119551546 (EPUB). Instructs readers on how to use methods of statistics and experimental design with R software Applied statistics covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce, and research. It proceeds from a strong...
2nd edition. — CRC Press, 2022. — 501 p. — ISBN 9781032119496. Thoroughly updated throughout, this second edition will continue to be about the practicable methods of statistical applications for engineers, and as well for scientists and those in business. It remains a what-I-wish-I-had-known-when-starting-my-career compilation of techniques. Contrasting a mathematical and...
4th Edition. — Caren M. Rotello, Jerome L. Myers, Arnold D. Well and Robert F. Lorch, Jr. — Routledge, 2025. — 814 p. — ISBN: 978-1-003-45355-0. This fully updated fourth edition of Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data. The guiding philosophy is to provide...
2nd Edition. — For Dummies, 2016. — 416 p. — ISBN: 978-1-119-29352-1. The fun and easy way to get down to business with statistics Stymied by statistics? No fear? this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life. Statistics For...
Springer, 2021. — 233 p. — ISBN 978-981-16-5935-5. The book covers computational statistics, its methodologies and applications for IoT device. It includes the details in the areas of computational arithmetic and its influence on computational statistics, numerical algorithms in statistical application software, basics of computer systems, statistical techniques, linear algebra...
CRC Press, 2022. — 275 p. — ISBN 978-0-367-71512-0. With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for Machine Learning. It offers applications that can be used in various domains and...
Springer, 2021. — 144 p. — ISBN 978-3-658-32396-7. This book describes how statistical methods can be effectively applied in the work of an engineer in terms that can be readily understood. Application of these methods enables the effort involved in experiments to be reduced, the results of these experiments to be fully evaluated, and statistically sound statements to be made...
Springer, 2021. — 475 p. — ISBN 978-3-030-46379-3. Design Research uses scientific methods to evaluate designs and build design theories. This book starts with recognizable questions in Design Research, such as A/B testing, how users learn to operate a device and why computer-generated faces are eerie. Using a broad range of examples, efficient research designs are presented...
Wiley, 2020. — 175 p. — ISBN 978-1-119-67585-3. This book offers a one academic term text that prepares the student to broaden their skills in statistics, probability and inference, prior to selecting their follow-on courses in their chosen fields, whether it be engineering, computer science, programming, data sciences, business or economics. The book places focus early on...
Harvard University Press, 2016. — 240 p. What gives statistics its unity as a science? Stephen Stigler sets forth the seven foundational ideas of statistics—a scientific discipline related to but distinct from mathematics and computer science and one which often seems counterintuitive. His original account will fascinate the interested layperson and engage the professional...
CRC Press, 2022. — 249 p. — (Texts in Statistical Science Series). — ISBN 978-0-367-63937-2. Прикладная линейная регрессия для продольных данных: с акцентом на отсутствующие наблюдения This book introduces best practices in longitudinal data analysis at intermediate level, with a minimum number of formulas without sacrificing depths. It meets the need to understand statistical...
2nd edition. — CRC Press/Chapman & Hall, 2023. — 395 p. — (Texts in Statistical Science). — ISBN 978-0-367-56827-6. Developed from the authors' graduate-level biostatistics course, Applied Categorical and Count Data Analysis, Second Edition explains how to perform the statistical analysis of discrete data, including categorical and count outcomes. The authors have been teaching...
Academic Press, 2022. — 460 p. — ISBN 978-0-12-815861-6. Statistical Modeling using Local Gaussian Approximation extends powerful characteristics of the Gaussian distribution, perhaps, the most well-known and most used distribution in statistics, to a large class of non-Gaussian and nonlinear situations through local approximation. This extension enables the reader to follow...
National Academy of Sciences, 2017. — 101 p. The concept of utilizing big data to enable scientific discovery has generated tremendous excitement and investment from both private and public sectors over the past decade, and expectations continue to grow (FTC, 2016; NITRD/NCO, 2016). Big data is considered herein as data sets whose heterogeneity, complexity, and size—typically...
CRC Press, 2025. — 267 p. — (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences Series). — ISBN 978-1-032-90495-5. Generalized Kernel Equating is a comprehensive guide for statisticians, psychometricians, and educational researchers aiming to master test score equating. This book introduces the Generalized Kernel Equating (GKE) framework, providing the...
Wiley, 2021. — 435 p. — ISBN 9781119523079. Covers the latest developments in direction dependence research Direction Dependence in Statistical Modeling: Methods of Analysis incorporates the latest research for the statistical analysis of hypotheses that are compatible with the causal direction of dependence of variable relations. Having particular application in the fields of...
Springer, 2023. — 611 p. — (Springer Actuarial). — ISBN 978-3-031-12408-2. This book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and...
М.: Физматлит, 2006.— 816 с. В книге рассматриваются способы анализа наблюдений методами математической статистики. Последовательно на языке, доступном специалисту - не математику, излагаются современные методы анализа распределений вероятностей, оценки параметров распределений, проверки статистических гипотез, оценки связей между случайными величинами, планирования...
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