Statistical Methods For Data Analysis

Author : Luca Lista
Publisher : Springer
Page : 257 pages
File Size : 53,5 Mb
Release : 2017-10-13
Category : Science
ISBN : 9783319628400

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Statistical Methods for Data Analysis in Particle Physics by Luca Lista Pdf

This concise set of course-based notes provides the reader with the main concepts and tools needed to perform statistical analyses of experimental data, in particular in the field of high-energy physics (HEP). First, the book provides an introduction to probability theory and basic statistics, mainly intended as a refresher from readers’ advanced undergraduate studies, but also to help them clearly distinguish between the Frequentist and Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on both discoveries and upper limits, as many applications in HEP concern hypothesis testing, where the main goal is often to provide better and better limits so as to eventually be able to distinguish between competing hypotheses, or to rule out some of them altogether. Many worked-out examples will help newcomers to the field and graduate students alike understand the pitfalls involved in applying theoretical concepts to actual data. This new second edition significantly expands on the original material, with more background content (e.g. the Markov Chain Monte Carlo method, best linear unbiased estimator), applications (unfolding and regularization procedures, control regions and simultaneous fits, machine learning concepts) and examples (e.g. look-elsewhere effect calculation).

Author : John K. Taylor,Cheryl Cihon
Publisher : CRC Press
Page : 296 pages
File Size : 40,6 Mb
Release : 2004-01-14
Category : Mathematics
ISBN : 9781135439545

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Statistical Techniques for Data Analysis by John K. Taylor,Cheryl Cihon Pdf

Since the first edition of this book appeared, computers have come to the aid of modern experimenters and data analysts, bringing with them data analysis techniques that were once beyond the calculational reach of even professional statisticians. Today, scientists in every field have access to the techniques and technology they need to analyze stat

Author : Samaradasa Weerahandi
Publisher : Springer Science & Business Media
Page : 343 pages
File Size : 48,9 Mb
Release : 2013-12-01
Category : Mathematics
ISBN : 9781461208259

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Exact Statistical Methods for Data Analysis by Samaradasa Weerahandi Pdf

Now available in paperback, this book covers some recent developments in statistical inference. It provides methods applicable in problems involving nuisance parameters such as those encountered in comparing two exponential distributions or in ANOVA without the assumption of equal error variances. The generalized procedures are shown to be more powerful in detecting significant experimental results and in avoiding misleading conclusions.

Author : R. Lyman Ott,Micheal Longnecker
Publisher : Cengage Learning
Page : 0 pages
File Size : 53,8 Mb
Release : 2010-02-16
Category : Probabilities
ISBN : 0495109150

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An Introduction to Statistical Methods and Data Analysis by R. Lyman Ott,Micheal Longnecker Pdf

Provides worked-out solutions to odd-numbered exercises.

Author : Rudolf J. Freund,William J. Wilson
Publisher : Elsevier
Page : 694 pages
File Size : 41,9 Mb
Release : 2003-01-07
Category : Mathematics
ISBN : 9780080498225

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Statistical Methods by Rudolf J. Freund,William J. Wilson Pdf

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

Author : Daniel Powers,Yu Xie
Publisher : Emerald Group Publishing
Page : 296 pages
File Size : 43,5 Mb
Release : 2008-11-13
Category : Psychology
ISBN : 1781906599

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Statistical Methods for Categorical Data Analysis by Daniel Powers,Yu Xie Pdf

This book provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social science research. Companion website also available, at https://webspace.utexas.edu/dpowers/www/

Author : D.R. Helsel,R.M. Hirsch
Publisher : Elsevier
Page : 546 pages
File Size : 47,6 Mb
Release : 1993-03-03
Category : Mathematics
ISBN : 0080875084

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Statistical Methods in Water Resources by D.R. Helsel,R.M. Hirsch Pdf

Data on water quality and other environmental issues are being collected at an ever-increasing rate. In the past, however, the techniques used by scientists to interpret this data have not progressed as quickly. This is a book of modern statistical methods for analysis of practical problems in water quality and water resources. The last fifteen years have seen major advances in the fields of exploratory data analysis (EDA) and robust statistical methods. The 'real-life' characteristics of environmental data tend to drive analysis towards the use of these methods. These advances are presented in a practical and relevant format. Alternate methods are compared, highlighting the strengths and weaknesses of each as applied to environmental data. Techniques for trend analysis and dealing with water below the detection limit are topics covered, which are of great interest to consultants in water-quality and hydrology, scientists in state, provincial and federal water resources, and geological survey agencies. The practising water resources scientist will find the worked examples using actual field data from case studies of environmental problems, of real value. Exercises at the end of each chapter enable the mechanics of the methodological process to be fully understood, with data sets included on diskette for easy use. The result is a book that is both up-to-date and immediately relevant to ongoing work in the environmental and water sciences.

Author : Ding-Geng Chen,Jiahua Chen,Xuewen Lu,Grace Y. Yi,Hao Yu
Publisher : Springer
Page : 222 pages
File Size : 49,8 Mb
Release : 2016-11-30
Category : Mathematics
ISBN : 9789811025945

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Advanced Statistical Methods in Data Science by Ding-Geng Chen,Jiahua Chen,Xuewen Lu,Grace Y. Yi,Hao Yu Pdf

This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world. It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invited the presenters to prepare a full chapter for this book in order to disseminate the findings and promote further research collaborations in this area. This timely book offers new methods that impact advanced statistical model development in big-data sciences.

Author : Oliver Schabenberger,Carol A. Gotway
Publisher : CRC Press
Page : 512 pages
File Size : 49,8 Mb
Release : 2017-01-27
Category : Mathematics
ISBN : 9781482258134

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Statistical Methods for Spatial Data Analysis by Oliver Schabenberger,Carol A. Gotway Pdf

Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses on the unique characteristics of spatial data and the development of specialized analytical tools designed explicitly for spatial data analysis. Statistical Methods for Spatial Data Analysis answers the demand for a text that incorporates all of these factors by presenting a balanced exposition that explores both the theoretical foundations of the field of spatial statistics as well as practical methods for the analysis of spatial data. This book is a comprehensive and illustrative treatment of basic statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain. It introduces essential tools and approaches including: measures of autocorrelation and their role in data analysis; the background and theoretical framework supporting random fields; the analysis of mapped spatial point patterns; estimation and modeling of the covariance function and semivariogram; a comprehensive treatment of spatial analysis in the spectral domain; and spatial prediction and kriging. The volume also delivers a thorough analysis of spatial regression, providing a detailed development of linear models with uncorrelated errors, linear models with spatially-correlated errors and generalized linear mixed models for spatial data. It succinctly discusses Bayesian hierarchical models and concludes with reviews on simulating random fields, non-stationary covariance, and spatio-temporal processes. Additional material on the CRC Press website supplements the content of this book. The site provides data sets used as examples in the text, software code that can be used to implement many of the principal methods described and illustrated, and updates to the text itself.

Author : Elisa T. Lee,John Wenyu Wang
Publisher : John Wiley & Sons
Page : 389 pages
File Size : 48,7 Mb
Release : 2013-09-23
Category : Mathematics
ISBN : 9781118593059

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Statistical Methods for Survival Data Analysis by Elisa T. Lee,John Wenyu Wang Pdf

Praise for the Third Edition “. . . an easy-to read introduction to survival analysis which covers the major concepts and techniques of the subject.” —Statistics in Medical Research Updated and expanded to reflect the latest developments, Statistical Methods for Survival Data Analysis, Fourth Edition continues to deliver a comprehensive introduction to the most commonly-used methods for analyzing survival data. Authored by a uniquely well-qualified author team, the Fourth Edition is a critically acclaimed guide to statistical methods with applications in clinical trials, epidemiology, areas of business, and the social sciences. The book features many real-world examples to illustrate applications within these various fields, although special consideration is given to the study of survival data in biomedical sciences. Emphasizing the latest research and providing the most up-to-date information regarding software applications in the field, Statistical Methods for Survival Data Analysis, Fourth Edition also includes: Marginal and random effect models for analyzing correlated censored or uncensored data Multiple types of two-sample and K-sample comparison analysis Updated treatment of parametric methods for regression model fitting with a new focus on accelerated failure time models Expanded coverage of the Cox proportional hazards model Exercises at the end of each chapter to deepen knowledge of the presented material Statistical Methods for Survival Data Analysis is an ideal text for upper-undergraduate and graduate-level courses on survival data analysis. The book is also an excellent resource for biomedical investigators, statisticians, and epidemiologists, as well as researchers in every field in which the analysis of survival data plays a role.

Author : Elisa T. Lee
Publisher : Wiley-Interscience
Page : 504 pages
File Size : 52,9 Mb
Release : 1992-05-07
Category : Mathematics
ISBN : STANFORD:36105001600191

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Statistical Methods for Survival Data Analysis by Elisa T. Lee Pdf

Functions of survival time; Examples of survival data analysis; Nonparametric methods of estimating survival functions; Nonparametric methods for comparing survival distributions; Some well-known survival distributions and their applications; Graphical methods for sulvival distribution fitting and goodness-of-fit tests; Analytical estimation procedures for sulvival distributions; Parametric methods for comparing two survival distribution; Identification of prognostic factors related to survival time; Identification of risk factors related to dichotomous data; Planning and design of clinical trials (I); Planning and design of clinicL trials(II).

Author : Lyman Ott
Publisher : Brooks/Cole
Page : 752 pages
File Size : 54,9 Mb
Release : 1977
Category : Mathematics
ISBN : UOM:39015046750926

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An Introduction to Statistical Methods and Data Analysis by Lyman Ott Pdf

Author : Mervyn G. Marasinghe,William J. Kennedy
Publisher : Springer Science & Business Media
Page : 562 pages
File Size : 55,8 Mb
Release : 2008-12-10
Category : Mathematics
ISBN : 9780387773728

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SAS for Data Analysis by Mervyn G. Marasinghe,William J. Kennedy Pdf

This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate majors or advanced undergraduate students from a variety of disciplines. These students typically have taken an introductory-level s- tistical methods course that requires the use a software system such as SAS for performing statistical analysis. Thus students are expected to have an - derstanding of basic concepts of statistical inference such as estimation and hypothesis testing. Understandably, adequate time is not available in a ?rst course in stat- tical methods to cover the use of a software system adequately in the amount of time available for instruction. The aim of this book is to teach how to use the SAS system for data analysis. The SAS language is introduced at a level of sophistication not found in most introductory SAS books. Important features such as SAS data step programming, pointers, and line-hold spe- ?ers are described in detail. The powerful graphics support available in SAS is emphasized throughout, and many worked SAS program examples contain graphic components.

Author : Richard M. Heiberger,Burt Holland
Publisher : Springer Science & Business Media
Page : 739 pages
File Size : 50,7 Mb
Release : 2013-06-29
Category : Mathematics
ISBN : 9781475742848

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Statistical Analysis and Data Display by Richard M. Heiberger,Burt Holland Pdf

This presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying computer listings. They emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how tabular results are used to confirm the visual impressions derived from the graphs. Many of the graphical formats are novel and appear here for the first time in print.

Author : Mervyn G. Marasinghe,Kenneth J. Koehler
Publisher : Springer
Page : 679 pages
File Size : 51,9 Mb
Release : 2018-04-12
Category : Computers
ISBN : 9783319692395

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Statistical Data Analysis Using SAS by Mervyn G. Marasinghe,Kenneth J. Koehler Pdf

The aim of this textbook (previously titled SAS for Data Analytics) is to teach the use of SAS for statistical analysis of data for advanced undergraduate and graduate students in statistics, data science, and disciplines involving analyzing data. The book begins with an introduction beyond the basics of SAS, illustrated with non-trivial, real-world, worked examples. It proceeds to SAS programming and applications, SAS graphics, statistical analysis of regression models, analysis of variance models, analysis of variance with random and mixed effects models, and then takes the discussion beyond regression and analysis of variance to conclude. Pedagogically, the authors introduce theory and methodological basis topic by topic, present a problem as an application, followed by a SAS analysis of the data provided and a discussion of results. The text focuses on applied statistical problems and methods. Key features include: end of chapter exercises, downloadable SAS code and data sets, and advanced material suitable for a second course in applied statistics with every method explained using SAS analysis to illustrate a real-world problem. New to this edition: • Covers SAS v9.2 and incorporates new commands • Uses SAS ODS (output delivery system) for reproduction of tables and graphics output • Presents new commands needed to produce ODS output • All chapters rewritten for clarity • New and updated examples throughout • All SAS outputs are new and updated, including graphics • More exercises and problems • Completely new chapter on analysis of nonlinear and generalized linear models • Completely new appendix Mervyn G. Marasinghe, PhD, is Associate Professor Emeritus of Statistics at Iowa State University, where he has taught courses in statistical methods and statistical computing. Kenneth J. Koehler, PhD, is University Professor of Statistics at Iowa State University, where he teaches courses in statistical methodology at both graduate and undergraduate levels and primarily uses SAS to supplement his teaching.