Data science, Timbers, Tiffany-anne (university Of British Colum
Автор: Little Название: Statistical Analysis with Missing Data, Third Edit ion ISBN: 0470526793 ISBN-13(EAN): 9780470526798 Издательство: Wiley Рейтинг: Цена: 12664.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Reflecting new application topics, Statistical Analysis with Missing Data offers a thoroughly up-to-date, reorganized survey of current methodology for handling missing data problems. The third edition reviews historical approaches to the subject and describe rigorous yet simple methods for multivariate analysis with missing values.
Автор: Michael C. Whitlock, Dolph Schluter Название: The Analysis of Biological Data ISBN: 1319325343 ISBN-13(EAN): 9781319325343 Издательство: Macmillan Learning Рейтинг: Цена: 13858.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The evolution of a classicThe new 12th edition of Introduction to Genetic Analysis takes this cornerstone textbook to the next level.
Автор: Baltagi Badi H. Название: Econometric Analysis of Panel Data ISBN: 3030539520 ISBN-13(EAN): 9783030539528 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction.- The One-Way Error Component Regression Model.- The Two-Way Error Component Regression Model.- Test of Hypotheses with Panel Data.- Heteroskedasticity and Serial Correlation in the Error Component Model.- Seemingly Unrelated Regressions with Error Components.- Simultaneous Equations with Error Components.- Dynamic Panel Data Models.- Unbalanced Panel Data Models.- Special Topics.- Limited Dependent Variables and Panel Data.- Nonstationary Panels.- Spatial Panel Data Models.
Автор: Wheelan Charles Название: Naked Statistics: Stripping the Dread from the Data ISBN: 039334777X ISBN-13(EAN): 9780393347777 Издательство: Wiley Рейтинг: Цена: 2216.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A New York Times bestseller "Brilliant, funny...the best math teacher you never had." -San Francisco Chronicle
Incorporating the latest R packages as well as new case studies and applications, Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition covers the aspects of R most often used by statistical analysts. New users of R will find the book's simple approach easy to understand while more sophisticated users will appreciate the invaluable source of task-oriented information.
New to the Second Edition
The use of RStudio, which increases the productivity of R users and helps users avoid error-prone cut-and-paste workflows
New chapter of case studies illustrating examples of useful data management tasks, reading complex files, making and annotating maps, "scraping" data from the web, mining text files, and generating dynamic graphics
New chapter on special topics that describes key features, such as processing by group, and explores important areas of statistics, including Bayesian methods, propensity scores, and bootstrapping
New chapter on simulation that includes examples of data generated from complex models and distributions
A detailed discussion of the philosophy and use of the knitr and markdown packages for R
New packages that extend the functionality of R and facilitate sophisticated analyses
Reorganized and enhanced chapters on data input and output, data management, statistical and mathematical functions, programming, high-level graphics plots, and the customization of plots
Easily Find Your Desired Task
Conveniently organized by short, clear descriptive entries, this edition continues to show users how to easily perform an analytical task in R. Users can quickly find and implement the material they need through the extensive indexing, cross-referencing, and worked examples in the text. Datasets and code are available for download on a supplementary website.
Автор: MacInnes John Название: An Introduction to Secondary Data Analysis with IBM SPSS Statis ISBN: 1446285774 ISBN-13(EAN): 9781446285770 Издательство: Sage Publications Рейтинг: Цена: 6968.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: John MacInnes takes the fear out of statistics for students, and helps to raise the standards of their quantitative methods skills, by clearly and accessibly introducing all that`s needed to know about using secondary data and working with IBM SPSS Statistics.
Описание: Learning how to manage, share and preserve data is essential for active researchers. A comprehensive guide for scientific researchers providing everything they need to know about data management and how to organize, document, use and reuse their data.
Introduces the latest developments in forecasting in advanced quantitative data analysis
This book presents advanced univariate multiple regressions, which can directly be used to forecast their dependent variables, evaluate their in-sample forecast values, and compute forecast values beyond the sample period. Various alternative multiple regressions models are presented based on a single time series, bivariate, and triple time-series, which are developed by taking into account specific growth patterns of each dependent variables, starting with the simplest model up to the most advanced model. Graphs of the observed scores and the forecast evaluation of each of the models are offered to show the worst and the best forecast models among each set of the models of a specific independent variable.
Advanced Time Series Data Analysis: Forecasting Using EViews provides readers with a number of modern, advanced forecast models not featured in any other book. They include various interaction models, models with alternative trends (including the models with heterogeneous trends), and complete heterogeneous models for monthly time series, quarterly time series, and annually time series. Each of the models can be applied by all quantitative researchers.
Presents models that are all classroom tested
Contains real-life data samples
Contains over 350 equation specifications of various time series models
Contains over 200 illustrative examples with special notes and comments
Applicable for time series data of all quantitative studies
Advanced Time Series Data Analysis: Forecasting Using EViews will appeal to researchers and practitioners in forecasting models, as well as those studying quantitative data analysis. It is suitable for those wishing to obtain a better knowledge and understanding on forecasting, specifically the uncertainty of forecast values.
Автор: Moulin Pierre Название: Statistical Inference for Engineers and Data Scientists ISBN: 1107185920 ISBN-13(EAN): 9781107185920 Издательство: Cambridge Academ Рейтинг: Цена: 10138.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An up-to-date and mathematically accessible introduction to the tools needed to address modern inference problems in engineering and data science. Richly illustrated with examples and exercises connecting the theory with practice, it is the `go to` guide for students studying the topic, and an excellent reference for researchers and practitioners.
Описание: Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies.
Автор: Hernando Ombao, Martin Lindquist, Wesley Thompson, John Aston Название: Handbook of Neuroimaging Data Analysis ISBN: 0367330695 ISBN-13(EAN): 9780367330699 Издательство: Taylor&Francis Рейтинг: Цена: 11023.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development of novel statistical approaches to model brain data.
Автор: Thomas Cleff Название: Applied Statistics and Multivariate Data Analysis ISBN: 3030177661 ISBN-13(EAN): 9783030177669 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Поставка под заказ.
Описание: This textbook will familiarize students in economics and business, as well as practitioners, with the basic principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis.
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