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Statistical Prediction By Discriminant Analysis
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Book Synopsis Statistical Prediction by Discriminant Analysis by : Robert Miller
Download or read book Statistical Prediction by Discriminant Analysis written by Robert Miller and published by Springer. This book was released on 2016-06-27 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objects of the American Meteorological Society are "the development and dissemination of knowledge of meteorology in all its phases and applications, and the advancement of its professional ideals." The organization of the Society took place in affiliation with the American Association for the Advancement of Science at Saint Louis, Missouri, December 29, 1919, and its incorporation, at Washington, D. C., January 21, 1920. The work of the Society is carried on by the Bulletin, the Journal, and Meteorological Monographs, by papers and discussions at meetings of the Society, through the offices of the Secretary and the Executive Secretary, and by correspondence. All of the Americas are represented in the membership of the Society as well as many foreign countries.
Book Synopsis Statistical Prediction by Discriminant Analysis by : Robert G. Miller
Download or read book Statistical Prediction by Discriminant Analysis written by Robert G. Miller and published by . This book was released on 1962 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applied MANOVA and Discriminant Analysis by : Carl J. Huberty
Download or read book Applied MANOVA and Discriminant Analysis written by Carl J. Huberty and published by John Wiley & Sons. This book was released on 2006-05-12 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete introduction to discriminant analysis--extensively revised, expanded, and updated This Second Edition of the classic book, Applied Discriminant Analysis, reflects and references current usage with its new title, Applied MANOVA and Discriminant Analysis. Thoroughly updated and revised, this book continues to be essential for any researcher or student needing to learn to speak, read, and write about discriminant analysis as well as develop a philosophy of empirical research and data analysis. Its thorough introduction to the application of discriminant analysis is unparalleled. Offering the most up-to-date computer applications, references, terms, and real-life research examples, the Second Edition also includes new discussions of MANOVA, descriptive discriminant analysis, and predictive discriminant analysis. Newer SAS macros are included, and graphical software with data sets and programs are provided on the book's related Web site. The book features: Detailed discussions of multivariate analysis of variance and covariance An increased number of chapter exercises along with selected answers Analyses of data obtained via a repeated measures design A new chapter on analyses related to predictive discriminant analysis Basic SPSS(r) and SAS(r) computer syntax and output integrated throughout the book Applied MANOVA and Discriminant Analysis enables the reader to become aware of various types of research questions using MANOVA and discriminant analysis; to learn the meaning of this field's concepts and terms; and to be able to design a study that uses discriminant analysis through topics such as one-factor MANOVA/DDA, assessing and describing MANOVA effects, and deleting and ordering variables.
Book Synopsis Statistical Prediction by Discriminant Analysis by : Robert G. Miller
Download or read book Statistical Prediction by Discriminant Analysis written by Robert G. Miller and published by . This book was released on 1962 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applied Discriminant Analysis by : Carl J. Huberty
Download or read book Applied Discriminant Analysis written by Carl J. Huberty and published by Wiley-Interscience. This book was released on 1994-08-11 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most books on discriminant analysis focus on statistical theory. But properly applied, discriminant analysis methods can be enormously useful in the interpretation of data. This book is the first ever to offer a complete introduction to discriminant analysis that focuses on applications. It provides numerous examples, explained in great detail, using current statistical discriminant analysis algorithms. It also develops several themes that will be useful to researchers and students regardless of the analytical methods they employ. They are the careful examination of data prior to final analysis; the application of critical judgment and common sense to all analyses and interpretations; and conducting multiple analyses as a matter of routine. To encourage and enable readers to conduct multiple analyses of their data, the accompanying diskette contains the four complete data sets and five special computer programs that are referred to repeatedly in the text and are the subjects of numerous exercise problems. This enables the reader to carry out package analyses on the data sets using a variety of procedural options both within and across computer packages. The term "discriminant analysis" means different things to different people. For statisticians and researchers in the physical sciences, it usually denotes the process through which group membership is predicted on the basis of multiple predictor variables. Behavioral scientists, on the other hand, often use discriminant analysis to describe group differences across multiple response variables. Though closely related, predictive discriminant analysis (PDA) and descriptive discriminant analysis (DDA) are used for different purposes and should be approached in different ways. To accentuate these differences and distinguish clearly between the two, Applied Discriminant Analysis presents these topics separately. For graduate students, this book will expand your background in multivariate data analysis methods and facilitate both the reading and the conducting of applied empirical research. It will also be of great use to experienced researchers who wish to enhance or update their quantitative background, and to methodologists who want to learn more about the details of applied discriminant data analysis, and some still unresolved problems, as well.
Book Synopsis TRADITIONAL AND DATA-DRIVEN PREDICTIVE STATISTICAL MODELS by : Dr. Neeta Kishor Dhane
Download or read book TRADITIONAL AND DATA-DRIVEN PREDICTIVE STATISTICAL MODELS written by Dr. Neeta Kishor Dhane and published by Laxmi Book Publication. This book was released on 2021-07-23 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: The desire to know the unknown has always been one of the human characteristics that distinguish humans from other living things on the earth. The past is known but cannot be changed, and hence is if no interest. The present is happening and everyone is witnessing it and therefore it is not exciting. But the future is both unknown and perhaps therefore uncertain, and is therefore both interesting and exciting. Using past experience for predicting the unknown future was initially treated as an art because it require careful choice of parts of the past that will make prediction both easy and accurate, and there were times when it was felt that it is impossible to formulate a method for this. Prediction was then not considered to be scientific empirical sciences that learn from scientist and professionals realized the scientific nature of the ability to predict. What then began as the preparation for developing a prediction formula involved finding common patterns in past data and their consequences so that the consequence can be predicted as soon as the relevant pattern is observed. At the same time the discipline of statistics developed the concept and methodology for building statistical models. With experience in the development and applications of different models, scientists and researchers identify models as belonging to four different classes namely, the class of descriptive models, the class of diagnostic models, the class of predictive models, and the class of prescriptive or prognostic models. The scientific or theoretical activity of building models and analyzing data accordingly is known as analytics. It has therefore been recognized that there are four classes of analytics, namely descriptive analytics, diagnostic analytics, prescriptive analytics and predictive analytics. These four classes are defined briefly for convenience of the reader.
Book Synopsis Statistical Techniques for Bankruptcy Prediction by : Volodymyr Perederiy
Download or read book Statistical Techniques for Bankruptcy Prediction written by Volodymyr Perederiy and published by GRIN Verlag. This book was released on 2015-05-22 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master's Thesis from the year 2005 in the subject Business economics - Accounting and Taxes, grade: 1,0, European University Viadrina Frankfurt (Oder), course: International Business Administration, language: English, abstract: Bankruptcy prediction has become during the past 3 decades a matter of ever rising academic interest and intensive research. This is due to the academic appeal of the problem, combined with its importance in practical applications. The practical importance of bankruptcy prediction models grew recently even more, with “Basle-II” regulations, which were elaborated by Basle Committee on Banking Supervision to enhance the stability of international financial system. These regulations oblige financial institutions and banks to estimate the probability of default of their obligors. There exist some fundamental economic theory to base bankruptcy prediction models on, but this typically relies on stock market prices of companies under consideration. These prices are, however, only available for large public listed companies. Models for private firms are therefore empirical in their nature and have to rely on rigorous statistical analysis of all available information for such firms. In 95% of cases, this information is limited to accounting information from the financial statements. Large databases of financial statements (e.g. Compustat in the USA) are maintained and often available for research purposes. Accounting information is particularly important for bankruptcy prediction models in emerging markets. This is because the capital markets in these countries are often underdeveloped and illiquid and don’t deliver sufficient stock market data, even for public/listed companies, for structural models to be applied. The accounting information is normally summarized in so-called financial ratios. Such ratios (e.g. leverage ratio, calculated as Debt to Total Assets of a company) have a long tradition in accounting analysis. Many of these ratios are believed to reflect the financial health of a company and to be related to the bankruptcy. However, these beliefs are often very vague (e.g. leverages above 70% might provoke a bankruptcy) and subjective. Quantitative bankruptcy prediction models objectify these beliefs in that they apply statistical techniques to the accounting data. [...]
Author :R. Karl Hanson Publisher :American Psychological Association (APA) ISBN 13 :9781433836411 Total Pages :440 pages Book Rating :4.8/5 (364 download)
Book Synopsis Prediction Statistics for Psychological Assessment by : R. Karl Hanson
Download or read book Prediction Statistics for Psychological Assessment written by R. Karl Hanson and published by American Psychological Association (APA). This book was released on 2021-11-16 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: "As statistical prediction becomes ubiquitous in many areas of psychology, a comprehensive guide to navigating these tools is needed, one that covers topics pertinent to those in psychology and the social sciences. Prediction Statistics for Psychological Assessment, by R. Karl Hanson, is the first book to teach students and practitioners the nuts and bolts of prediction statistics, while illustrating the utility of prediction and prediction tools in applied psychological practice. This valuable resource uses real-world examples, helpful explanations and practice exercises to support the use of prediction tools in psychological assessment. Actuarial risk assessment evaluators need to know how prediction tools work, how to evaluate them, and how to interpret their results in applied assessments. Written in a clear and accessible manner, this user-friendly book helps readers understand how to evaluate and interpret different kinds of prediction tools, appreciate the numeric information used in risk communication, and utilize prediction tools to inform evidence-based decision-making"--
Book Synopsis Modern Statistics with R by : Måns Thulin
Download or read book Modern Statistics with R written by Måns Thulin and published by BoD - Books on Demand. This book was released on 2021-07-28 with total page 598 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. The aim of Modern Statistics with R is to introduce you to key parts of the modern statistical toolkit. It teaches you: - Data wrangling - importing, formatting, reshaping, merging, and filtering data in R. - Exploratory data analysis - using visualisation and multivariate techniques to explore datasets. - Statistical inference - modern methods for testing hypotheses and computing confidence intervals. - Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting. - Simulation - using simulation techniques for sample size computations and evaluations of statistical methods. - Ethics in statistics - ethical issues and good statistical practice. - R programming - writing code that is fast, readable, and free from bugs. Starting from the very basics, Modern Statistics with R helps you learn R by working with R. Topics covered range from plotting data and writing simple R code to using cross-validation for evaluating complex predictive models and using simulation for sample size determination. The book includes more than 200 exercises with fully worked solutions. Some familiarity with basic statistical concepts, such as linear regression, is assumed. No previous programming experience is needed.
Book Synopsis Discriminant Analysis and Applications by : T. Cacoullos
Download or read book Discriminant Analysis and Applications written by T. Cacoullos and published by Academic Press. This book was released on 2014-05-10 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discriminant Analysis and Applications comprises the proceedings of the NATO Advanced Study Institute on Discriminant Analysis and Applications held in Kifissia, Athens, Greece in June 1972. The book presents the theory and applications of Discriminant analysis, one of the most important areas of multivariate statistical analysis. This volume contains chapters that cover the historical development of discriminant analysis methods; logistic and quasi-linear discrimination; and distance functions. Medical and biological applications, and computer graphical analysis and graphical techniques for multidimensional data are likewise discussed. Statisticians, mathematicians, and biomathematicians will find the book very interesting.
Book Synopsis Research Methods for Political Science by : David E. McNabb
Download or read book Research Methods for Political Science written by David E. McNabb and published by Routledge. This book was released on 2015-07-17 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thoroughly updated, more concise than the previous edition, and available for the first time in paperback, "Research Methods for Political Science" is designed to help students learn what to research, why to research, and how to research. The text integrates both quantitative and qualitative approaches to research in one volume, and includes the most comprehensive coverage of qualitative methods currently available. It covers such important topics as research design, specifying research problems, designing questionnaries and writing questions, designing and carrying out qualitative research, and analyzing both quantitative and qualitative research data. Heavily illustrated, classroom tested, and exceptionally readable and engaging, the text also provides specific instructions on the use of available statistical software programs such as Excel and SPSS.
Book Synopsis Fundamentals of Clinical Data Science by : Pieter Kubben
Download or read book Fundamentals of Clinical Data Science written by Pieter Kubben and published by Springer. This book was released on 2018-12-21 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.
Book Synopsis A Historical Survey of Statistical Weather Prediction by : United States. Navy. Weather Research Facility
Download or read book A Historical Survey of Statistical Weather Prediction written by United States. Navy. Weather Research Facility and published by . This book was released on 1963 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work presents the history of the use of statistics in weather forecasting and describes the evolution of the more important statistical methods in this field: graphical techniques, periodicity, empirical orthogonal functions, and multiple discriminant analysis. A bibliography consisting of 141 references, divided by topics, and an appendix listing these references chronologically are included. (Author).
Book Synopsis An Introduction to Statistical Learning by : Gareth James
Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Book Synopsis Discriminant Analysis and Statistical Pattern Recognition by : Geoffrey J. McLachlan
Download or read book Discriminant Analysis and Statistical Pattern Recognition written by Geoffrey J. McLachlan and published by John Wiley & Sons. This book was released on 2005-02-25 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "For both applied and theoretical statisticians as well as investigators working in the many areas in which relevant use can be made of discriminant techniques, this monograph provides a modern, comprehensive, and systematic account of discriminant analysis, with the focus on the more recent advances in the field." –SciTech Book News ". . . a very useful source of information for any researcher working in discriminant analysis and pattern recognition." –Computational Statistics Discriminant Analysis and Statistical Pattern Recognition provides a systematic account of the subject. While the focus is on practical considerations, both theoretical and practical issues are explored. Among the advances covered are regularized discriminant analysis and bootstrap-based assessment of the performance of a sample-based discriminant rule, and extensions of discriminant analysis motivated by problems in statistical image analysis. The accompanying bibliography contains over 1,200 references.
Book Synopsis Cloud Cover Predictions Diagnosed from Global Numerical Weather Prediction Model Forecasts by : Donald C. Norquist
Download or read book Cloud Cover Predictions Diagnosed from Global Numerical Weather Prediction Model Forecasts written by Donald C. Norquist and published by . This book was released on 1997 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Illustrating Statistical Procedures: Finding Meaning in Quantitative Data by : Ray W. Cooksey
Download or read book Illustrating Statistical Procedures: Finding Meaning in Quantitative Data written by Ray W. Cooksey and published by Springer Nature. This book was released on 2020-05-14 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets learners who would benefit from learning more conceptually and less computationally about statistical procedures and the software packages that can be used to implement them. This book provides a comprehensive overview of this important research skill domain with an emphasis on visual support for learning and better understanding. The primary focus is on fundamental concepts, procedures and interpretations of statistical analyses within a single broad illustrative research context. The book covers a wide range of descriptive, correlational and inferential statistical procedures as well as more advanced procedures not typically covered in introductory and intermediate statistical texts. It is an ideal reference for postgraduate students as well as for researchers seeking to broaden their conceptual exposure to what is possible in statistical analysis.
