Statistical methods for categorical data analysis, Powers, Daniel Xie, Yu

Автор: Leonard
Название: A Course in Categorical Data Analysis
ISBN: 1584881801 ISBN-13(EAN): 9781584881803
Издательство: Taylor&Francis
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Цена: 117390.00 T
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Описание: Categorical data requires a different methodology and techniques typically not encountered in introductory statistics courses. This title presents various ways of extracting real-life conclusions from contingency tables. It uses a Fisherian approach to categorical data analysis and incorporates numerous examples and real data sets.

Автор: Leonard, Thomas
Название: A Course in Categorical Data Analysis
ISBN: 1138469610 ISBN-13(EAN): 9781138469617
Издательство: Taylor&Francis
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Цена: 183750.00 T
Наличие на складе: Невозможна поставка.
Описание: Categorical data requires a different methodology and techniques typically not encountered in introductory statistics courses. This title presents various ways of extracting real-life conclusions from contingency tables. It uses a Fisherian approach to categorical data analysis and incorporates numerous examples and real data sets.

Автор: Erling B. Andersen
Название: The Statistical Analysis of Categorical Data
ISBN: 364278819X ISBN-13(EAN): 9783642788192
Издательство: Springer
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Цена: 102480.00 T
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Описание: The aim of this book is to give an up to date account of the most commonly uses statisti- cal models for categorical data. In many cases, the data sets are those data sets, which were not included in the examples of the book, although they at one point in time were regarded as potential can- didates for an example.

Автор: Tang, Wan (tulane University, New Orleans, La) He, Hua (tulane University) Tu, Xin M. (university Of California-san Diego)
Название: Applied categorical and count data analysis
ISBN: 0367568276 ISBN-13(EAN): 9780367568276
Издательство: Taylor&Francis
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Цена: 81650.00 T
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Описание: This second edition explains how to perform the statistical analysis of discrete data, including categorical and count outcomes. It covers classic concepts and popular topics, such as logistic regression models, along with modern areas including models for zero-modified count outcomes.

Автор: Nussbaum E Michael
Название: Categorical and Nonparametric Data Analysis
ISBN: 1138787825 ISBN-13(EAN): 9781138787827
Издательство: Taylor&Francis
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Цена: 81650.00 T
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Описание: Featuring in-depth coverage of categorical and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain their assumptions and how tests work in future publications. Numerous examples from psychology, education, and other social sciences demonstrate varied applications of the material. Basic statistics and probability are reviewed for those who need a refresher. Mathematical derivations are placed in optional appendices for those interested in this detailed coverage. Highlights include the following: Unique coverage of categorical and nonparametric statistics better prepares readers to select the best technique for their particular research project; however, some chapters can be omitted entirely if preferred. Step-by-step examples of each test help readers see how the material is applied in a variety of disciplines.  Although the book can be used with any program, examples of how to use the tests in SPSS and Excel foster conceptual understanding. Exploring the Concept boxes integrated throughout prompt students to review key material and draw links between the concepts to deepen understanding.  Problems in each chapter help readers test their understanding of the material.  Emphasis on selecting tests that maximize power helps readers avoid "marginally" significant results.  Website (www.routledge.com/9781138787827) features datasets for the book's examples and problems, and for the instructor, PowerPoint slides, sample syllabi, answers to the even-numbered problems, and Excel data sets for lecture purposes. Intended for individual or combined graduate or advanced undergraduate courses in categorical and nonparametric data analysis, cross-classified data analysis, advanced statistics and/or quantitative techniques taught in psychology, education, human development, sociology, political science, and other social and life sciences, the book also appeals to researchers in these disciplines. The nonparametric chapters can be deleted if preferred. Prerequisites include knowledge of t tests and ANOVA.

Автор: Nussbaum E. Michael
Название: Categorical and Nonparametric Data Analysis: Choosing the Best Statistical Technique
ISBN: 1848726031 ISBN-13(EAN): 9781848726031
Издательство: Taylor&Francis
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Цена: 183750.00 T
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Описание:

Featuring in-depth coverage of categorical and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain their assumptions and how tests work in future publications. Numerous examples from psychology, education, and other social sciences demonstrate varied applications of the material. Basic statistics and probability are reviewed for those who need a refresher. Mathematical derivations are placed in optional appendices for those interested in this detailed coverage.

Автор: J.D. Jobson
Название: Applied Multivariate Data Analysis
ISBN: 1461269474 ISBN-13(EAN): 9781461269472
Издательство: Springer
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Цена: 93160.00 T
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Описание: A Second Course in Statistics The past decade has seen a tremendous increase in the use of statistical data analysis and in the availability of both computers and statistical software.

Автор: Guogen Shan
Название: Exact Statistical Inference for Categorical Data
ISBN: 0081006810 ISBN-13(EAN): 9780081006818
Издательство: Elsevier Science
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Цена: 58380.00 T
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Описание:

Exact Statistical Inference for Categorical Data discusses the way asymptotic approaches have been often used in practice to make statistical inference. This book introduces both conditional and unconditional exact approaches for the data in 2 by 2, or 2 by k contingency tables, and is an ideal reference for users who are interested in having the convenience of applying asymptotic approaches, with less computational time. In addition to the existing conditional exact inference, some efficient, unconditional exact approaches could be used in data analysis to improve the performance of the testing procedure.

Автор: Brajendra C. Sutradhar
Название: Longitudinal Categorical Data Analysis
ISBN: 1493953206 ISBN-13(EAN): 9781493953202
Издательство: Springer
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Цена: 88500.00 T
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Описание: This is the first book in longitudinal categorical data analysis with parametric correlation models developed based on dynamic relationships among repeated categorical responses.

Автор: James K. Lindsey
Название: The Analysis of Categorical Data Using GLIM
ISBN: 0387970290 ISBN-13(EAN): 9780387970295
Издательство: Springer
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Цена: 107130.00 T
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Описание: Besides their previous statistics courses, these students have had an introductory course in computer programming (FORTRAN, Pascal, or C) and courses in calculus and linear algebra, so that they may not be typical students of sociology.

Автор: Y. Sakamoto
Название: Categorical Data Analysis by AIC
ISBN: 0792314298 ISBN-13(EAN): 9780792314295
Издательство: Springer
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Цена: 88500.00 T
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Описание: Presents a practical approach to categorical data analysis based on the Akaike Information Criterion (AIC) and the Akaike Bayesian Information Criterion (ABIC). Topics covered include variable selection for categorical data, Bayesian binary regression and nonparametric density estimator.

Автор: Kunihiro Suzuki
Название: Statistics. Volume 3: Categorical and Time Dependent Data Analysis
ISBN: 1536151246 ISBN-13(EAN): 9781536151244
Издательство: Nova Science
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Цена: 252370.00 T
Наличие на складе: Невозможна поставка.
Описание: We utilize statistics when we evaluate TV program ratings, predict voting outcomes, prepare stock, predict the amount of sales, and evaluate the effectiveness of medical treatment. We want to predict the results not on the basis of personal experience or images, but on the basis of corresponding data. The accuracy of the prediction depends on the data and related theories. It is easy to show input and output data associated with a model without understanding it. However, the models themselves are not perfect, because they contain assumptions and approximations in general. Therefore, the application of the model to the data should be careful. We should know what model we should apply to the data, what parameters are assumed in the model, and what we can state based on the results of the models.Let us consider a coin toss, for example. When we perform a coin toss, we obtain a head or a tail. If we try the toss a coin three times, we may obtain the results of two heads and one tail. Therefore, the probability that we obtain for heads is , and the one that we obtain for tails is . This is a fact and we need not to discuss this any further. It is important to notice that the probability ( ) of getting a head is limited to this trial. Therefore, we can never say that the probability that we obtain for heads with this coin is , in which we state general characteristics of the coin. If we perform the coin toss trial 400 times and obtain heads 300 times, we may be able to state that the probability of obtaining a head is as the characteristics of the coin. What we can state based on the obtained data depends on the sample number. Statistics gives us a clear guideline under which we can state something is based on the data with corresponding error ranges.Mathematics used in statistics is not so easy. It may be tough work to acquire the related techniques. Fortunately, software development makes it easy to obtain results. Therefore, many members who are not specialists in mathematics can perform statistical analysis with these types of software. However, it is important to understand the meaning of the model, that is, why some certain variables are introduced and what they express, and what we can state based on the results. Therefore, understanding mathematics related to the models is invoked to appreciate the results.In this book, the authors treat models from fundamental ones to advanced ones without skipping their derivation processes. It is then possible to clearly understand the assumptions and approximations used in the models, and hence understand the limitation of the models.The authors also cover almost all the subjects in statistics since they are all related to each other, and the mathematical treatments used in a model are frequently used in the other ones.Additionally, many good practical and theoretical books on statistics are presented [1]-[10]. However, these books are oriented to special cases: Fundamental, mathematical, or special subjects. The author also aims to connect theories to practical subjects. He hopes that this book will aid readers in furthering their knowledge of special cases in statistics.