Understanding robust and exploratory data analysis


Author: David Caster Hoaglin,Frederick Mosteller,John Wilder Tukey
Publisher: Wiley-Interscience
ISBN: N.A
Category: Business & Economics
Page: 447
View: 3641

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The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensiveeditions, Wiley hopes to extend the life of these important works by making themavailable to future generations of mathematicians and scientists. Currently available in the Series: T.W. Anderson The Statistical Analysis of Time Series T.S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences Robert G. Bartle The Elements of Integration and Lebesgue Measure George E. P. Box & Norman R. Draper Evolutionary Operation: A Statistical Method for Process Improvement George E. P. Box & George C. Tiao Bayesian Inference in Statistical Analysis R. W. Carter Finite Groups of Lie Type: Conjugacy Classes and Complex Characters R. W. Carter Simple Groups of Lie Type William G. Cochran & Gertrude M. Cox Experimental Designs, Second Edition Richard Courant Differential and Integral Calculus, Volume I Richard Courant Differential and Integral Calculus, Volume II Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume I Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume II D. R. Cox Planning of Experiments Harold S. M. Coxeter Introduction to Geometry, Second Edition Charles W. Curtis & Irving Reiner Representation Theory of Finite Groups and Associative Algebras Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume I Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume II Cuthbert Daniel Fitting Equations to Data: Computer Analysis of Multifactor Data, Second Edition Bruno de Finetti Theory of Probability, Volume I Bruno de Finetti Theory of Probability, Volume 2 W. Edwards Deming Sample Design in Business Research Amos de Shalit & Herman Feshbach Theoretical Nuclear Physics, Volume 1— Nuclear Structure Harold F. Dodge & Harry G. Romig Sampling Inspection Tables: Single and Double Sampling J. L. Doob Stochastic Processes Nelson Dunford & Jacob T. Schwartz Linear Operators, Part One, General Theory Nelson Dunford & Jacob T. Schwartz Linear Operators, Part Two, Spectral Theory—Self Adjoint Operators in Hilbert Space Nelson Dunford & Jacob T. Schwartz Linear Operators, Part Three, Spectral Operators Regina C. Elandt-Johnson & Norman L. Johnson Survival Models and Data Analysis Herman Feshbach Theoretical Nuclear Physics: Nuclear Reactions Joseph L. Fleiss Design and Analysis of Clinical Experiments Bernard Friedman Lectures on Applications-Oriented Mathematics Phillip Griffiths & Joseph Harris Principles of Algebraic Geometry Gerald J. Hahn & Samuel S. Shapiro Statistical Models in Engineering Marshall Hall, Jr. Combinatorial Theory, Second Edition Morris H. Hansen, William N. Hurwitz & William G. Madow Sample Survey Methods and Theory, Volume I—Methods and Applications Morris H. Hansen, William N. Hurwitz & William G. Madow Sample Survey Methods and Theory, Volume II—Theory Peter Henrici Applied and Computational Complex Analysis, Volume 1—Power Series—Integration—Conformal Mapping—Location of Zeros Peter Henrici Applied and Computational Complex Analysis, Volume 2—Special Functions—Integral Transforms—Asymptotics—Continued Fractions Peter Henrici Applied and Computational Complex Analysis, Volume 3—Discrete Fourier Analysis—Cauchy Integrals—Construction of Conformal Maps—Univalent Functions Peter Hilton & Yel-Chiang Wu A Course in Modern Algebra David C. Hoaglin, Frederick Mosteller & John W. Tukey Understanding Robust and Exploratory Data Analysis Harry Hochstadt Integral Equations Leslie Kish Survey Sampling Shoshichi Kobayashi & Katsumi Nomizu Foundations of Differential Geometry, Volume I Shoshichi Kobayashi & Katsumi Nomizu Foundations of Differential Geometry, Volume 2 Erwin O. Kreyszig Introductory Functional Analysis with Applications William H. Louisell Quantum Statistical Properties of Radiation Rupert G. Miller Jr. Survival Analysis Ali Hasan Nayfeh Introduction to Perturbation Techniques Ali Hasan Nayfeh & Dean T. Mook Nonlinear Oscillations Emanuel Parzen Modern Probability Theory & Its Applications P. M. Prenter Splines and Variational Methods Howard Raiffa & Robert Schlaifer Applied Statistical Decision Theory Walter Rudin Fourier Analysis on Groups Lawrence S. Schulman Techniques and Applications of Path Integration Shayle R. Searle Linear Models I. H. Segel Enzyme Kinetics: Behavior and Analysis of Rapid Equilibrium and Steady-State Enzyme Systems C. L. Siegel Topics in Complex Function Theory, Volume I—Elliptic Functions and Uniformization Theory C. L. Siegel Topics in Complex Function Theory, Volume II—Automorphic and Abelian Integrals C. L. Siegel Topics in Complex Function Theory, Volume III—Abelian Functions and Modular Functions of Several Variables L. Spitzer Physical Processes in the Interstellar Medium J. J. Stoker Differential Geometry J. J. Stoker Water Waves: The Mathematical Theory with Applications J. J. Stoker Nonlinear Vibrations in Mechanical and ElectricalSystems Richard Zallen The Physics of Amorphous Solids Arnold Zellner Introduction to Bayesian Inference in Econometrics

Graphisch gestützte Datenanalyse


Author: Rainer Schnell
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3486787322
Category: Business & Economics
Page: 385
View: 1223

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Der "Schnell" behandelt Techniken zur graphischen Darstellung von Daten oder statistischer Größe im Rahmen von Datenanalysen. Diese "Datenanalysegraphik" ist ein nützliches Instrument für Datenanalytiker, hier wiederum bevorzugt solche in den Sozialwissenschaften.

Fundamentals of Exploratory Analysis of Variance


Author: David C. Hoaglin,Frederick Mosteller,John W. Tukey
Publisher: John Wiley & Sons
ISBN: 9780471527350
Category: Mathematics
Page: 448
View: 8146

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The analysis of variance is presented as an exploratory component of data analysis, while retaining the customary least squares fitting methods. Balanced data layouts are used to reveal key ideas and techniques for exploration. The approach emphasizes both the individual observations and the separate parts that the analysis produces. Most chapters include exercises and the appendices give selected percentage points of the Gaussian, t, F chi-squared and studentized range distributions.

Forschungsmethoden und Evaluation in den Sozial- und Humanwissenschaften


Author: Nicola Döring,Jürgen Bortz
Publisher: Springer-Verlag
ISBN: 3642410898
Category: Psychology
Page: 1051
View: 397

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Der Klassiker zu den Forschungsmethoden – rundum erneuert, didaktisch verbessert und aktueller denn je! Dieses Buch ist ein fundierter und verlässlicher Begleiter für Studierende, Forschende und Berufstätige – da ist alles drin: Grundlagen: Wissenschaftstheorie, Qualitätskriterien sowie ethische Aspekte. Anwendung: Alle Phasen des Forschungsprozesses von der Festlegung des Forschungsthemas, des Untersuchungsdesigns und der Operationalisierung über Stichprobenziehung, Datenerhebungs- und Datenanalysemethoden bis zur Ergebnispräsentation. Vertiefung: Effektgrößen, Metaanalysen, Strukturgleichungsmodelle, Evaluationsforschung. Die 5. Auflage wurde grundlegend überarbeitet: Klarheit: Verbesserte Gliederung der Kapitel sowie des gesamten Buches. Aktualität: Beiträge zu Online-Methoden, Mixed-Methods-Designs und anderen neueren Entwicklungen. Lernfreundlichkeit: Viele Abbildungen, Tabellen, Definitionsboxen, Cartoons, Übungsaufgaben und Lernquiz mit Lösungen. Praxisbezug: Reale Studienbeispiele aus verschiedenen sozial- und humanwissenschaftlichen Fächern (z.B. Psychologie, Kommunikationswissenschaft, Erziehungswissenschaft, Medizin, Soziologie). Eine Begleit-Website bietet Lern-Tools für Studierende und Materialien für Lehrende.

Exploring Data Tables, Trends, and Shapes


Author: David C. Hoaglin,Frederick Mosteller,John W. Tukey
Publisher: John Wiley & Sons
ISBN: 1118150694
Category: Mathematics
Page: 527
View: 4792

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WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists ofselected books that have been made more accessible to consumers inan effort to increase global appeal and general circulation. Withthese new unabridged softcover volumes, Wiley hopes to extend thelives of these works by making them available to future generationsof statisticians, mathematicians, and scientists. "Exploring Data Tables, Trends, and Shapes (EDTTS) waswritten as a companion volume to the same editors' book,Understanding Robust and Exploratory Data Analysis (UREDA). WhereasUREDA is a collection of exploratory and resistant methods ofestimation and display, EDTTS goes a step further, describingmultivariate and more complicated techniques . . . I feel that theauthors have made a very significant contribution in the area ofmultivariate nonparametric methods. This book [is] a valuablesource of reference to researchers in the area." —Technometrics "This edited volume . . . provides an important theoretical andphilosophical extension to the currently popular statistical areaof Exploratory Data Analysis, which seeks to reveal structure, orsimple descriptions, in data . . . It is . . . an importantreference volume which any statistical library should considerseriously." —The Statistician This newly available and affordably priced paperback version ofExploring Data Tables, Trends, and Shapes presents majoradvances in exploratory data analysis and robust regression methodsand explains the techniques, relating them to classical methods.The book addresses the role of exploratory and robust techniques inthe overall data-analytic enterprise, and it also presents newmethods such as fitting by organized comparisons using the squarecombining table and identifying extreme cells in a sizablecontingency table with probabilistic and exploratory approaches.The book features a chapter on using robust regression in lesstechnical language than available elsewhere. Conceptual support foreach technique is also provided.

The Analysis of Covariance and Alternatives

Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies
Author: Bradley Huitema
Publisher: John Wiley & Sons
ISBN: 9781118067468
Category: Mathematics
Page: 480
View: 1467

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A complete guide to cutting-edge techniques and best practices for applying covariance analysis methods The Second Edition of Analysis of Covariance and Alternatives sheds new light on its topic, offering in-depth discussions of underlying assumptions, comprehensive interpretations of results, and comparisons of distinct approaches. The book has been extensively revised and updated to feature an in-depth review of prerequisites and the latest developments in the field. The author begins with a discussion of essential topics relating to experimental design and analysis, including analysis of variance, multiple regression, effect size measures and newly developed methods of communicating statistical results. Subsequent chapters feature newly added methods for the analysis of experiments with ordered treatments, including two parametric and nonparametric monotone analyses as well as approaches based on the robust general linear model and reversed ordinal logistic regression. Four groundbreaking chapters on single-case designs introduce powerful new analyses for simple and complex single-case experiments. This Second Edition also features coverage of advanced methods including: Simple and multiple analysis of covariance using both the Fisher approach and the general linear model approach Methods to manage assumption departures, including heterogeneous slopes, nonlinear functions, dichotomous dependent variables, and covariates affected by treatments Power analysis and the application of covariance analysis to randomized-block designs, two-factor designs, pre- and post-test designs, and multiple dependent variable designs Measurement error correction and propensity score methods developed for quasi-experiments, observational studies, and uncontrolled clinical trials Thoroughly updated to reflect the growing nature of the field, Analysis of Covariance and Alternatives is a suitable book for behavioral and medical scineces courses on design of experiments and regression and the upper-undergraduate and graduate levels. It also serves as an authoritative reference work for researchers and academics in the fields of medicine, clinical trials, epidemiology, public health, sociology, and engineering.

Multivariate Time Series Analysis

With R and Financial Applications
Author: Ruey S. Tsay
Publisher: John Wiley & Sons
ISBN: 1118617754
Category: Mathematics
Page: 520
View: 7464

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An accessible guide to the multivariate time series toolsused in numerous real-world applications Multivariate Time Series Analysis: With R and FinancialApplications is the much anticipated sequel coming from one ofthe most influential and prominent experts on the topic of timeseries. Through a fundamental balance of theory and methodology,the book supplies readers with a comprehensible approach tofinancial econometric models and their applications to real-worldempirical research. Differing from the traditional approach to multivariate timeseries, the book focuses on reader comprehension by emphasizingstructural specification, which results in simplified parsimoniousVAR MA modeling. Multivariate Time Series Analysis: With R andFinancial Applications utilizes the freely available Rsoftware package to explore complex data and illustrate relatedcomputation and analyses. Featuring the techniques and methodologyof multivariate linear time series, stationary VAR models, VAR MAtime series and models, unitroot process, factor models, andfactor-augmented VAR models, the book includes: • Over 300 examples and exercises to reinforce thepresented content • User-friendly R subroutines and research presentedthroughout to demonstrate modern applications • Numerous datasets and subroutines to provide readerswith a deeper understanding of the material Multivariate Time Series Analysis is an ideal textbookfor graduate-level courses on time series and quantitative financeand upper-undergraduate level statistics courses in time series.The book is also an indispensable reference for researchers andpractitioners in business, finance, and econometrics.

Nonparametric Statistical Methods


Author: Myles Hollander,Douglas A. Wolfe,Eric Chicken
Publisher: John Wiley & Sons
ISBN: 1118553292
Category: Mathematics
Page: 848
View: 6778

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Praise for the Second Edition “This book should be an essential part of the personallibrary of every practicingstatistician.”—Technometrics Thoroughly revised and updated, the new edition of NonparametricStatistical Methods includes additional modern topics andprocedures, more practical data sets, and new problems fromreal-life situations. The book continues to emphasize theimportance of nonparametric methods as a significant branch ofmodern statistics and equips readers with the conceptual andtechnical skills necessary to select and apply the appropriateprocedures for any given situation. Written by leading statisticians, Nonparametric StatisticalMethods, Third Edition provides readers with crucialnonparametric techniques in a variety of settings, emphasizing theassumptions underlying the methods. The book provides an extensivearray of examples that clearly illustrate how to use nonparametricapproaches for handling one- or two-sample location and dispersionproblems, dichotomous data, and one-way and two-way layoutproblems. In addition, the Third Edition features: The use of the freely available R software to aid incomputation and simulation, including many new R programs writtenexplicitly for this new edition New chapters that address density estimation, wavelets,smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science,astronomy, biology, criminology, education, engineering,environmental science, geology, home economics, medicine,oceanography, physics, psychology, sociology, and spacescience Nonparametric Statistical Methods, Third Edition is anexcellent reference for applied statisticians and practitioners whoseek a review of nonparametric methods and their relevantapplications. The book is also an ideal textbook forupper-undergraduate and first-year graduate courses in appliednonparametric statistics.

Statistics

Statistics, Statistics
Author: CTI Reviews
Publisher: Cram101 Textbook Reviews
ISBN: 1478442905
Category: Education
Page: 67
View: 6939

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Facts101 is your complete guide to Statistics. In this book, you will learn topics such as as those in your book plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.

Statistical Analysis of Designed Experiments

Theory and Applications
Author: Ajit C. Tamhane
Publisher: John Wiley & Sons
ISBN: 1118491432
Category: Science
Page: 720
View: 8279

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A indispensable guide to understanding and designing modern experiments The tools and techniques of Design of Experiments (DOE) allow researchers to successfully collect, analyze, and interpret data across a wide array of disciplines. Statistical Analysis of Designed Experiments provides a modern and balanced treatment of DOE methodology with thorough coverage of the underlying theory and standard designs of experiments, guiding the reader through applications to research in various fields such as engineering, medicine, business, and the social sciences. The book supplies a foundation for the subject, beginning with basic concepts of DOE and a review of elementary normal theory statistical methods. Subsequent chapters present a uniform, model-based approach to DOE. Each design is presented in a comprehensive format and is accompanied by a motivating example, discussion of the applicability of the design, and a model for its analysis using statistical methods such as graphical plots, analysis of variance (ANOVA), confidence intervals, and hypothesis tests. Numerous theoretical and applied exercises are provided in each chapter, and answers to selected exercises are included at the end of the book. An appendix features three case studies that illustrate the challenges often encountered in real-world experiments, such as randomization, unbalanced data, and outliers. Minitab® software is used to perform analyses throughout the book, and an accompanying FTP site houses additional exercises and data sets. With its breadth of real-world examples and accessible treatment of both theory and applications, Statistical Analysis of Designed Experiments is a valuable book for experimental design courses at the upper-undergraduate and graduate levels. It is also an indispensable reference for practicing statisticians, engineers, and scientists who would like to further their knowledge of DOE.

Multivariate Density Estimation

Theory, Practice, and Visualization
Author: David W. Scott
Publisher: John Wiley & Sons
ISBN: 1118575539
Category: Mathematics
Page: 384
View: 1933

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Clarifies modern data analysis through nonparametric density estimation for a complete working knowledge of the theory and methods Featuring a thoroughly revised presentation, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition maintains an intuitive approach to the underlying methodology and supporting theory of density estimation. Including new material and updated research in each chapter, the Second Edition presents additional clarification of theoretical opportunities, new algorithms, and up-to-date coverage of the unique challenges presented in the field of data analysis. The new edition focuses on the various density estimation techniques and methods that can be used in the field of big data. Defining optimal nonparametric estimators, the Second Edition demonstrates the density estimation tools to use when dealing with various multivariate structures in univariate, bivariate, trivariate, and quadrivariate data analysis. Continuing to illustrate the major concepts in the context of the classical histogram, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition also features: Over 150 updated figures to clarify theoretical results and to show analyses of real data sets An updated presentation of graphic visualization using computer software such as R A clear discussion of selections of important research during the past decade, including mixture estimation, robust parametric modeling algorithms, and clustering More than 130 problems to help readers reinforce the main concepts and ideas presented Boxed theorems and results allowing easy identification of crucial ideas Figures in color in the digital versions of the book A website with related data sets Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition is an ideal reference for theoretical and applied statisticians, practicing engineers, as well as readers interested in the theoretical aspects of nonparametric estimation and the application of these methods to multivariate data. The Second Edition is also useful as a textbook for introductory courses in kernel statistics, smoothing, advanced computational statistics, and general forms of statistical distributions.

Stochastic Dynamic Programming and the Control of Queueing Systems


Author: Linn I. Sennott
Publisher: John Wiley & Sons
ISBN: 0470317876
Category: Mathematics
Page: 354
View: 2551

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A path-breaking account of Markov decision processes-theory and computation This book's clear presentation of theory, numerous chapter-end problems, and development of a unified method for the computation of optimal policies in both discrete and continuous time make it an excellent course text for graduate students and advanced undergraduates. Its comprehensive coverage of important recent advances in stochastic dynamic programming makes it a valuable working resource for operations research professionals, management scientists, engineers, and others. Stochastic Dynamic Programming and the Control of Queueing Systems presents the theory of optimization under the finite horizon, infinite horizon discounted, and average cost criteria. It then shows how optimal rules of operation (policies) for each criterion may be numerically determined. A great wealth of examples from the application area of the control of queueing systems is presented. Nine numerical programs for the computation of optimal policies are fully explicated. The Pascal source code for the programs is available for viewing and downloading on the Wiley Web site at www.wiley.com/products/subject/mathematics. The site contains a link to the author's own Web site and is also a place where readers may discuss developments on the programs or other aspects of the material. The source files are also available via ftp at ftp://ftp.wiley.com/public/sci_tech_med/stochastic Stochastic Dynamic Programming and the Control of Queueing Systems features: * Path-breaking advances in Markov decision process techniques, brought together for the first time in book form * A theorem/proof format (proofs may be omitted without loss of continuity) * Development of a unified method for the computation of optimal rules of system operation * Numerous examples drawn mainly from the control of queueing systems * Detailed discussions of nine numerical programs * Helpful chapter-end problems * Appendices with complete treatment of background material

Time Series

Applications to Finance
Author: Ngai Hang Chan
Publisher: John Wiley & Sons
ISBN: 0471461644
Category: Mathematics
Page: 224
View: 7643

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Elements of Financial Time Series fills a gap in the market in thearea of financial time series analysis by giving both conceptualand practical illustrations. Examples and discussions in the laterchapters of the book make recent developments in time series moreaccessible. Examples from finance are maximized as much as possiblethroughout the book. * Full set of exercises is displayed at the end of eachchapter. * First seven chapters cover standard topics in time series at ahigh-intensity level. * Recent and timely developments in nonstandard time seriestechniques are illustrated with real finance examples indetail. * Examples are systemically illustrated with S-plus with codes anddata available on an associated Web site.

Sensor Networks and Configuration

Fundamentals, Standards, Platforms, and Applications
Author: Nitaigour P. Mahalik
Publisher: Springer Science & Business Media
ISBN: 3540373667
Category: Technology & Engineering
Page: 509
View: 4371

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This book incorporates a selection of research and development papers. Its scope is on history and background, underlying design methodology, application domains and recent developments. The readers will be able to understand the underlying technology, philosophy, concepts, ideas, and principles, with regard to broader areas of sensor network. Aspects of sensor network and experimental results have been presented in proper order.

Six Sigma and Beyond

The Implementation Process
Author: D.H. Stamatis
Publisher: CRC Press
ISBN: 1420000306
Category: Business & Economics
Page: 672
View: 3242

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The final volume of this series presents a synopsis of the curriculum that a typical Six Sigma program should follow. It differs from the preceding six volumes in that it is an implementation volume, therefore the information is geared towards helping readers formalize their own training. The book establishes the minimum requirements for the Six Sigma methodology and provides the body of knowledge needed for a successful and rewarding implementation of the Six Sigma processes.

Data Science and Big Data Analytics

Discovering, Analyzing, Visualizing and Presenting Data
Author: EMC Education Services
Publisher: John Wiley & Sons
ISBN: 1118876059
Category: Computers
Page: 432
View: 9095

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Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

Datenanalyse mit Python

Auswertung von Daten mit Pandas, NumPy und IPython
Author: Wes McKinney
Publisher: O'Reilly
ISBN: 3960102143
Category: Computers
Page: 542
View: 4775

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Erfahren Sie alles über das Manipulieren, Bereinigen, Verarbeiten und Aufbereiten von Datensätzen mit Python: Aktualisiert auf Python 3.6, zeigt Ihnen dieses konsequent praxisbezogene Buch anhand konkreter Fallbeispiele, wie Sie eine Vielzahl von typischen Datenanalyse-Problemen effektiv lösen. Gleichzeitig lernen Sie die neuesten Versionen von pandas, NumPy, IPython und Jupyter kennen.Geschrieben von Wes McKinney, dem Begründer des pandas-Projekts, bietet Datenanalyse mit Python einen praktischen Einstieg in die Data-Science-Tools von Python. Das Buch eignet sich sowohl für Datenanalysten, für die Python Neuland ist, als auch für Python-Programmierer, die sich in Data Science und Scientific Computing einarbeiten wollen. Daten und zugehöriges Material des Buchs sind auf GitHub verfügbar.Aus dem Inhalt:Nutzen Sie die IPython-Shell und Jupyter Notebook für das explorative ComputingLernen Sie Grundfunktionen und fortgeschrittene Features von NumPy kennenSetzen Sie die Datenanalyse-Tools der pandasBibliothek einVerwenden Sie flexible Werkzeuge zum Laden, Bereinigen, Transformieren, Zusammenführen und Umformen von DatenErstellen Sie interformative Visualisierungen mit matplotlibWenden Sie die GroupBy-Mechanismen von pandas an, um Datensätzen zurechtzuschneiden, umzugestalten und zusammenzufassenAnalysieren und manipulieren Sie verschiedenste Zeitreihen-DatenFür diese aktualisierte 2. Auflage wurde der gesamte Code an Python 3.6 und die neuesten Versionen der pandas-Bibliothek angepasst. Neu in dieser Auflage: Informationen zu fortgeschrittenen pandas-Tools sowie eine kurze Einführung in statsmodels und scikit-learn.

Experimental Design

Procedures for the Behavioral Sciences
Author: Roger E. Kirk
Publisher: SAGE Publications
ISBN: 1483305511
Category: Social Science
Page: 1072
View: 6009

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Experimental Design: Procedures for Behavioral Sciences, Fourth Edition is a classic text with a reputuation for accessibility and readability. It has been revised and updated to make learning design concepts even easier. Roger E. Kirk shows how three simple experimental designs can be combined to form a variety of complex designs. He provides diagrams illustrating how subjects are assigned to treatments and treatment combinations. New terms are emphasized in boldface type, there are summaries of the advantages and disadvantages of each design, and real-life examples show how the designs are used.