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Comprehensive Statistical Methods

Comprehensive Statistical Methods PDF Author: PN Arora
Publisher: S. Chand Publishing
ISBN: 8121927765
Category : Technology & Engineering
Languages : en
Pages : 45

Book Description
• For M.Com., MBA, MFC, MBE, M.A(Eco.),MCA, B.Com(H), B.Com(P),B.A.(H)Eco,BBA,BBS,BBE, B.A., etc. of all Indian Universities. Also for CA., ICWA, IAS, and other Equivalent Competitive Examinations. • Presents a clear, simple, systematic and comprehensive exposition of the methods, principles and techniques of statistics in various disciplines with special reference of commerce, management, economics and business. • A large number of solved (about 1500) problems and unsolved (nearly 3000) problems have been included to enable the user of statistical techniques and methods in commerce, economics, management and other related areas.

Comprehensive Statistical Methods

Comprehensive Statistical Methods PDF Author: PN Arora
Publisher: S. Chand Publishing
ISBN: 8121927765
Category : Technology & Engineering
Languages : en
Pages : 45

Book Description
• For M.Com., MBA, MFC, MBE, M.A(Eco.),MCA, B.Com(H), B.Com(P),B.A.(H)Eco,BBA,BBS,BBE, B.A., etc. of all Indian Universities. Also for CA., ICWA, IAS, and other Equivalent Competitive Examinations. • Presents a clear, simple, systematic and comprehensive exposition of the methods, principles and techniques of statistics in various disciplines with special reference of commerce, management, economics and business. • A large number of solved (about 1500) problems and unsolved (nearly 3000) problems have been included to enable the user of statistical techniques and methods in commerce, economics, management and other related areas.

Statistical Methods

Statistical Methods PDF Author: Rudolf J. Freund
Publisher: Elsevier
ISBN: 0080498221
Category : Mathematics
Languages : en
Pages : 694

Book Description
This broad text provides a complete overview of most standard statistical methods, including multiple regression, analysis of variance, experimental design, and sampling techniques. Assuming a background of only two years of high school algebra, this book teaches intelligent data analysis and covers the principles of good data collection. * Provides a complete discussion of analysis of data including estimation, diagnostics, and remedial actions * Examples contain graphical illustration for ease of interpretation * Intended for use with almost any statistical software * Examples are worked to a logical conclusion, including interpretation of results * A complete Instructor's Manual is available to adopters

Statistics

Statistics PDF Author: Thomas Hill
Publisher: StatSoft, Inc.
ISBN: 9781884233593
Category : Mathematics
Languages : en
Pages : 854

Book Description
This - one of a kind - book offers a comprehensive, almost encyclopedic presentation of statistical methods and analytic approaches used in science, industry, business, and data mining, written from the perspective of the real-life practitioner ("consumer") of these methods.

Statistical Methods for Business and Economics

Statistical Methods for Business and Economics PDF Author: Gert Nieuwenhuis
Publisher: McGraw-Hill Education
ISBN: 9780077109875
Category : Commercial statistics
Languages : en
Pages : 863

Book Description
This brand new book in statistics aims to provide an introduction to the key methods and techniques essential to a typical statistics syllabus, whilst also helping students to develop the skills needed to analyse, interpret and prepare data for use in business, economics and related disciplines. Covering the essential methods required at undergraduate level, the book is structured into four parts that deal with descriptive statistics, probability, sample theory and inferential statistics, taking students from the basics through to more advanced topics such as multiple linear regression. Every chapter contains clear descriptions of each technique, illustrated with numerous worked examples to aid students in understanding how to practice statistical methods. The real data used in the examples is drawn from European sources. The text also contains longer case examples set in a European business context, to show how statistics is used everyday in the business environment. Finally, each chapter concludes with a variety of exercises to test students’ ability to apply the theory and attain a high level of competence in using statistics. This comprehensive book is ideal for student of statistics at undergraduate level taking an introductory module in the topic.

Statistical Methods in Diagnostic Medicine

Statistical Methods in Diagnostic Medicine PDF Author: Xiao-Hua Zhou
Publisher: John Wiley & Sons
ISBN: 1118626044
Category : Medical
Languages : en
Pages : 597

Book Description
Praise for the First Edition " . . . the book is a valuable addition to the literature in the field, serving as a much-needed guide for both clinicians and advanced students."—Zentralblatt MATH A new edition of the cutting-edge guide to diagnostic tests in medical research In recent years, a considerable amount of research has focused on evolving methods for designing and analyzing diagnostic accuracy studies. Statistical Methods in Diagnostic Medicine, Second Edition continues to provide a comprehensive approach to the topic, guiding readers through the necessary practices for understanding these studies and generalizing the results to patient populations. Following a basic introduction to measuring test accuracy and study design, the authors successfully define various measures of diagnostic accuracy, describe strategies for designing diagnostic accuracy studies, and present key statistical methods for estimating and comparing test accuracy. Topics new to the Second Edition include: Methods for tests designed to detect and locate lesions Recommendations for covariate-adjustment Methods for estimating and comparing predictive values and sample size calculations Correcting techniques for verification and imperfect standard biases Sample size calculation for multiple reader studies when pilot data are available Updated meta-analysis methods, now incorporating random effects Three case studies thoroughly showcase some of the questions and statistical issues that arise in diagnostic medicine, with all associated data provided in detailed appendices. A related web site features Fortran, SAS®, and R software packages so that readers can conduct their own analyses. Statistical Methods in Diagnostic Medicine, Second Edition is an excellent supplement for biostatistics courses at the graduate level. It also serves as a valuable reference for clinicians and researchers working in the fields of medicine, epidemiology, and biostatistics.

Statistical Methods for Quality Improvement

Statistical Methods for Quality Improvement PDF Author: Thomas P. Ryan
Publisher: John Wiley & Sons
ISBN: 1118058100
Category : Technology & Engineering
Languages : en
Pages : 578

Book Description
Praise for the Second Edition "As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available." —Technometrics This new edition continues to provide the most current, proven statistical methods for quality control and quality improvement The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods. In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include: Updated coverage of control charts, with newly added tools The latest research on the monitoring of linear profiles and other types of profiles Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of CUSUM and EWMA procedures New discussions on design of experiments that include conditional effects and fraction of design space plots New material on Lean Six Sigma and Six Sigma programs and training Incorporating the latest software applications, the author has added coverage on how to use Minitab software to obtain probability limits for attribute charts. new exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic. Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. the book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement.

Using Statistical Methods in Social Science Research

Using Statistical Methods in Social Science Research PDF Author: Soleman H. Abu-Bader
Publisher: Oxford University Press
ISBN: 0190685352
Category : Social Science
Languages : en
Pages : 395

Book Description
In Using Statistical Methods, Soleman Abu-Bader detects and addresses the gaps between the research and data analysis of the classroom environment and the practitioner's office. This book not only guides social scientists through different tests, but also provides students and researchers alike with information that will help them in their own practice. With focus on the purpose, rationale, and assumptions made by each statistical test, and a plethora of research examples that clearly display their applicability and function in real-world practice, Professor Abu-Bader creates a step-by-step description of the process needed to clearly organize, choose a test or statistical technique, analyze, interpret, and report research findings.

Understanding Advanced Statistical Methods

Understanding Advanced Statistical Methods PDF Author: Peter Westfall
Publisher: CRC Press
ISBN: 1466512105
Category : Mathematics
Languages : en
Pages : 572

Book Description
Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum likelihood, bootstrapping, nonparametrics, and Bayesian methods. The book teaches students how to properly model, think critically, and design their own studies to avoid common errors. It leads them to think differently not only about math and statistics but also about general research and the scientific method. With a focus on statistical models as producers of data, the book enables students to more easily understand the machinery of advanced statistics. It also downplays the "population" interpretation of statistical models and presents Bayesian methods before frequentist ones. Requiring no prior calculus experience, the text employs a "just-in-time" approach that introduces mathematical topics, including calculus, where needed. Formulas throughout the text are used to explain why calculus and probability are essential in statistical modeling. The authors also intuitively explain the theory and logic behind real data analysis, incorporating a range of application examples from the social, economic, biological, medical, physical, and engineering sciences. Enabling your students to answer the why behind statistical methods, this text teaches them how to successfully draw conclusions when the premises are flawed. It empowers them to use advanced statistical methods with confidence and develop their own statistical recipes. Ancillary materials are available on the book’s website.

Statistical Methods in Bioinformatics

Statistical Methods in Bioinformatics PDF Author: Warren J. Ewens
Publisher: Springer Science & Business Media
ISBN: 0387400826
Category : Science
Languages : en
Pages : 616

Book Description
Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community. This book provides an introduction to some of these new methods. The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes. The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods. The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized. The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspects of the theory outlined in the main text. Warren J. Ewens holds the Christopher H. Brown Distinguished Professorship at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics. He is a senior editor of Annals of Human Genetics and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceedings of the Royal Society B and SIAM Journal in Mathematical Biology. He is a fellow of the Royal Society and the Australian Academy of Science. Gregory R. Grant is a senior bioinformatics researcher in the University of Pennsylvania Computational Biology and Informatics Laboratory. He obtained his Ph.D. in number theory from the University of Maryland in 1995 and his Masters in Computer Science from the University of Pennsylvania in 1999. Comments on the first edition: "This book would be an ideal text for a postgraduate course...[and] is equally well suited to individual study.... I would recommend the book highly." (Biometrics) "Ewens and Grant have given us a very welcome introduction to what is behind those pretty [graphical user] interfaces." (Naturwissenschaften) "The authors do an excellent job of presenting the essence of the material without getting bogged down in mathematical details." (Journal American Statistical Association) "The authors have restructured classical material to a great extent and the new organization of the different topics is one of the outstanding services of the book." (Metrika)

Longitudinal Data Analysis

Longitudinal Data Analysis PDF Author: Garrett Fitzmaurice
Publisher: CRC Press
ISBN: 142001157X
Category : Mathematics
Languages : en
Pages : 633

Book Description
Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory