Computer-Intensive Methods for Testing Hypotheses PDF Download
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Author: Eric W. Noreen
Publisher: Wiley-Interscience
ISBN:
Category : Mathematics
Languages : en
Pages : 246
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Book Description
How to use computer-intensive methods to assess the significance of a statistic in an hypothesis test--for both statisticians and nonstatisticians alike. The significance of almost any test can be assessed using one of the methods presented here, for the techniques given are very general (e.g. virtually every nonparametric statistical test is a special case of one of the methods covered). Programs presented are brief, easy to read, require minimal programming, and can be run on most PC's. They also serve as templates adaptable to a wide range of applications. Includes numerous illustrations of how to apply computer-intensive methods.
Author: Eric W. Noreen
Publisher: Wiley-Interscience
ISBN:
Category : Mathematics
Languages : en
Pages : 246
Get Book Here
Book Description
How to use computer-intensive methods to assess the significance of a statistic in an hypothesis test--for both statisticians and nonstatisticians alike. The significance of almost any test can be assessed using one of the methods presented here, for the techniques given are very general (e.g. virtually every nonparametric statistical test is a special case of one of the methods covered). Programs presented are brief, easy to read, require minimal programming, and can be run on most PC's. They also serve as templates adaptable to a wide range of applications. Includes numerous illustrations of how to apply computer-intensive methods.
Author: Cmt Association
Publisher: John Wiley & Sons
ISBN: 1394184794
Category :
Languages : en
Pages : 899
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Book Description
Get Your Copy of the Official 2023 CMT(R) Level III Curriculum Building upon the concepts covered in Levels I and II, the Official CMT(R) Level III Curriculum is the authoritative resource for all candidates preparing for their final CMT exam in June or December of 2023. This text explores asset relationships, portfolio management, behavioral finance, volatility analysis, and more. Published in partnership with the CMT Association, CMT Curriculum Level III 2023: The Integration of Technical Analysis covers all concepts featured on the Level III CMT(R) exam, and is designed to improve candidates' understanding of key topics in the theory and analysis of markets and securities.
Author: CMT Association
Publisher: John Wiley & Sons
ISBN: 1119871735
Category : Business & Economics
Languages : en
Pages : 903
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Book Description
Get Your Copy of the Official 2022 CMT® Level III Curriculum Building upon the concepts covered in Levels I and II, the Official CMT® Level III Curriculum is the authoritative resource for all candidates preparing for their final CMT exam in June or December of 2022. This text explores asset relationships, portfolio management, behavioral finance, volatility analysis, and more. Published in partnership with the CMT Association, CMT Curriculum Level III 2022: The Integration of Technical Analysis covers all concepts featured on the Level III CMT® exam, and is designed to improve candidates’ understanding of key topics in the theory and analysis of markets and securities.
Author: Bryan F.J. Manly
Publisher: CRC Press
ISBN: 1482296411
Category : Mathematics
Languages : en
Pages : 468
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Book Description
Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. This new edition of the bestselling Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates the value of a number of these methods with an emphasis on biological applications. This textbook focuses on three related areas in computational statistics: randomization, bootstrapping, and Monte Carlo methods of inference. The author emphasizes the sampling approach within randomization testing and confidence intervals. Similar to randomization, the book shows how bootstrapping, or resampling, can be used for confidence intervals and tests of significance. It also explores how to use Monte Carlo methods to test hypotheses and construct confidence intervals. New to the Third Edition Updated information on regression and time series analysis, multivariate methods, survival and growth data as well as software for computational statistics References that reflect recent developments in methodology and computing techniques Additional references on new applications of computer-intensive methods in biology Providing comprehensive coverage of computer-intensive applications while also offering data sets online, Randomization, Bootstrap and Monte Carlo Methods in Biology, Third Edition supplies a solid foundation for the ever-expanding field of statistics and quantitative analysis in biology.
Author: Wiley
Publisher: John Wiley & Sons
ISBN: 1119674565
Category : Business & Economics
Languages : en
Pages : 944
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Book Description
Everything you need to pass Level III of the CMT Program CMT Level III 2020: The Integration of Technical Analysis fully prepares you to demonstrate competency integrating basic concepts in Level I with practical applications in Level II, by using critical analysis to arrive at well-supported, ethical investing and trading recommendations. Covered topics include: asset relationships, portfolio management, behavioral finance, volatility, and analysis. The Level III exam emphasizes risk management concepts as well as classical methods of technical analysis. This cornerstone guidebook of the Chartered Market Technician® Program will provide every advantage to passing Level III CMT Exam.
Author: David Aronson
Publisher: John Wiley & Sons
ISBN: 1118160584
Category : Business & Economics
Languages : en
Pages : 572
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Book Description
Evidence-Based Technical Analysis examines how you can apply the scientific method, and recently developed statistical tests, to determine the true effectiveness of technical trading signals. Throughout the book, expert David Aronson provides you with comprehensive coverage of this new methodology, which is specifically designed for evaluating the performance of rules/signals that are discovered by data mining.
Author: James E. Gentle
Publisher: Springer Science & Business Media
ISBN: 0387216111
Category : Computers
Languages : en
Pages : 427
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Book Description
Will provide a more elementary introduction to these topics than other books available; Gentle is the author of two other Springer books
Author: Bruce Ratner
Publisher: CRC Press
ISBN: 1351652389
Category : Computers
Languages : en
Pages : 849
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Book Description
Interest in predictive analytics of big data has grown exponentially in the four years since the publication of Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition. In the third edition of this bestseller, the author has completely revised, reorganized, and repositioned the original chapters and produced 13 new chapters of creative and useful machine-learning data mining techniques. In sum, the 43 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. What is new in the Third Edition: The current chapters have been completely rewritten. The core content has been extended with strategies and methods for problems drawn from the top predictive analytics conference and statistical modeling workshops. Adds thirteen new chapters including coverage of data science and its rise, market share estimation, share of wallet modeling without survey data, latent market segmentation, statistical regression modeling that deals with incomplete data, decile analysis assessment in terms of the predictive power of the data, and a user-friendly version of text mining, not requiring an advanced background in natural language processing (NLP). Includes SAS subroutines which can be easily converted to other languages. As in the previous edition, this book offers detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. The author addresses each methodology and assigns its application to a specific type of problem. To better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. While this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.
Author: Micah Altman
Publisher: John Wiley & Sons
ISBN: 0471475742
Category : Mathematics
Languages : en
Pages : 349
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Book Description
At last—a social scientist's guide through the pitfalls of modern statistical computing Addressing the current deficiency in the literature on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social Scientist seeks to provide readers with a unique practical guidebook to the numerical methods underlying computerized statistical calculations specific to these fields. The authors demonstrate that knowledge of these numerical methods and how they are used in statistical packages is essential for making accurate inferences. With the aid of key contributors from both the social and behavioral sciences, the authors have assembled a rich set of interrelated chapters designed to guide empirical social scientists through the potential minefield of modern statistical computing. Uniquely accessible and abounding in modern-day tools, tricks, and advice, the text successfully bridges the gap between the current level of social science methodology and the more sophisticated technical coverage usually associated with the statistical field. Highlights include: A focus on problems occurring in maximum likelihood estimation Integrated examples of statistical computing (using software packages such as the SAS, Gauss, Splus, R, Stata, LIMDEP, SPSS, WinBUGS, and MATLAB®) A guide to choosing accurate statistical packages Discussions of a multitude of computationally intensive statistical approaches such as ecological inference, Markov chain Monte Carlo, and spatial regression analysis Emphasis on specific numerical problems, statistical procedures, and their applications in the field Replications and re-analysis of published social science research, using innovative numerical methods Key numerical estimation issues along with the means of avoiding common pitfalls A related Web site includes test data for use in demonstrating numerical problems, code for applying the original methods described in the book, and an online bibliography of Web resources for the statistical computation Designed as an independent research tool, a professional reference, or a classroom supplement, the book presents a well-thought-out treatment of a complex and multifaceted field.
Author: Barbara M. Byrne
Publisher: Routledge
ISBN: 131763313X
Category : Psychology
Languages : en
Pages : 460
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Book Description
This bestselling text provides a practical guide to structural equation modeling (SEM) using the Amos Graphical approach. Using clear, everyday language, the text is ideal for those with little to no exposure to either SEM or Amos. The author reviews SEM applications based on actual data taken from her own research. Each chapter "walks" readers through the steps involved (specification, estimation, evaluation, and post hoc modification) in testing a variety of SEM models. Accompanying each application is: an explanation of the issues addressed and a schematic presentation of hypothesized model structure; Amos input and output with interpretations; use of the Amos toolbar icons and pull-down menus; and data upon which the model application was based, together with updated references pertinent to the SEM model tested. Thoroughly updated throughout, the new edition features: All new screen shots featuring Amos Version 23. Descriptions and illustrations of Amos’ new Tables View format which enables the specification of a structural model in spreadsheet form. Key concepts and/or techniques that introduce each chapter. Alternative approaches to model analyses when enabled by Amos thereby allowing users to determine the method best suited to their data. Provides analysis of the same model based on continuous and categorical data (Ch. 5) thereby enabling readers to observe two ways of specifying and testing the same model as well as compare results. All applications based on the Amos graphical mode interface accompanied by more "how to" coverage of graphical techniques unique to Amos. More explanation of key procedures and analyses that address questions posed by readers All application data files are available at www.routledge.com/9781138797031. The two introductory chapters in Section 1 review the fundamental concepts of SEM methodology and a general overview of the Amos program. Section 2 provides single-group analyses applications including two first-order confirmatory factor analytic (CFA) models, one second-order CFA model, and one full latent variable model. Section 3 presents multiple-group analyses applications with two rooted in the analysis of covariance structures and one in the analysis of mean and covariance structures. Two models that are increasingly popular with SEM practitioners, construct validity and testing change over time using the latent growth curve, are presented in Section 4. The book concludes with a review of the use of bootstrapping to address non-normal data and a review of missing (or incomplete) data in Section 5. An ideal supplement for graduate level courses in psychology, education, business, and social and health sciences that cover the fundamentals of SEM with a focus on Amos, this practical text continues to be a favorite of both researchers and practitioners. A prerequisite of basic statistics through regression analysis is recommended but no exposure to either SEM or Amos is required.
