Statistical Graphics for Univariate and Bivariate Data

Statistical Graphics for Univariate and Bivariate Data PDF Author: William G. Jacoby
Publisher: SAGE
ISBN: 9780761900832
Category : Medical
Languages : en
Pages : 116

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Book Description
Author William G. Jacoby focuses on graphical displays that researchers can employ as an integral part of the data analysis process. Such visual depictions are frequently more revealing than traditional, numerical summary statistics. Accessibly written, this book contains chapters on univariate and bivariate methods. The former covers histograms, smoothed histograms, univariate scatterplots, quantile plots, box plots, and dot plots. The latter covers scatterplot construction guidelines, jittering for overplotted points, marginal box plots, scatterplot slicing, the Loess procedure for nonparametric scatterplot smoothing, and banking to 45 degrees for enhanced visual perception. This book provides strategies for examining data more effectively. The resultant insights help researchers avoid the problem of forcing an inaccurate model onto uncooperative data and guide analysts to model specifications that provide accurate representations of empirical information. Learn more about "The Little Green Book" - QASS Series! Click Here

Statistical Graphics for Univariate and Bivariate Data

Statistical Graphics for Univariate and Bivariate Data PDF Author: William G. Jacoby
Publisher: SAGE
ISBN: 0761900837
Category : Medical
Languages : en
Pages : 107

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Book Description
Author William G. Jacoby focuses on graphical displays that researchers can employ as an integral part of the data analysis process. Such visual depictions are frequently more revealing than traditional, numerical summary statistics. Accessibly written, this book contains chapters on univariate and bivariate methods. The former covers histograms, smoothed histograms, univariate scatterplots, quantile plots, box plots, and dot plots. The latter covers scatterplot construction guidelines, jittering for overplotted points, marginal box plots, scatterplot slicing, the Loess procedure for nonparametric scatterplot smoothing, and banking to 45 degrees for enhanced visual perception. This book provides strategies for examining data more effectively. The resultant insights help researchers avoid the problem of forcing an inaccurate model onto uncooperative data and guide analysts to model specifications that provide accurate representations of empirical information. Learn more about "The Little Green Book" - QASS Series! Click Here

Statistical Graphics for Visualizing Multivariate Data

Statistical Graphics for Visualizing Multivariate Data PDF Author: William G. Jacoby
Publisher: SAGE
ISBN: 9780761908999
Category : Medical
Languages : en
Pages : 116

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Book Description
Jacoby explores a variety of graphical displays that are useful for visualising multivariate data, and introduces the concept of a 'data space'. Several methods for coding information directly into the plotting symbols are explained.

Graphics for Statistics and Data Analysis with R

Graphics for Statistics and Data Analysis with R PDF Author: Kevin J Keen
Publisher: CRC Press
ISBN: 1584880872
Category : Mathematics
Languages : en
Pages : 486

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Book Description
Graphics for Statistics and Data Analysis with R presents the basic principles of sound graphical design and applies these principles to engaging examples using the graphical functions available in R. It offers a wide array of graphical displays for the presentation of data, including modern tools for data visualization and representation. The book considers graphical displays of a single discrete variable, a single continuous variable, and then two or more of each of these. It includes displays and the R code for producing the displays for the dot chart, bar chart, pictographs, stemplot, boxplot, and variations on the quantile-quantile plot. The author discusses nonparametric and parametric density estimation, diagnostic plots for the simple linear regression model, polynomial regression, and locally weighted polynomial regression for producing a smooth curve through data on a scatterplot. The last chapter illustrates visualizing multivariate data with examples using Trellis graphics. Showing how to use graphics to display or summarize data, this text provides best practice guidelines for producing and choosing among graphical displays. It also covers the most effective graphing functions in R. R code is available for download on the book’s website.

Census Bureau Statistical Graphics

Census Bureau Statistical Graphics PDF Author: Lawrence H. Cox
Publisher:
ISBN:
Category : Computer graphics
Languages : en
Pages : 7

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Book Description
For some time, the U.S. Bureau of the Census has published statistical data in graphical as well as tabular formats. These graphical displays include barcharts, pie charts, line graphs, time series plots and univariate and bivariate statistical maps. Such publication graphics are provided both monochromatically and in color. Recently, the Census Bureau has initiated a research program to investigate the application of computer graphics to statistical data analysis. Examples of such analytical graphics are regression and time series plots, scatterplots used in outlier analysis, line graphs depicting rate of change overlayed on barcharts depicting level or value of one or more variables, and color statistical maps. This paper describes the computer graphics hardware and software capabilities of the Census Bureau, our experience in computerized statistical graphics, and research directions for employing computer graphics as an analytical tool in statistical data analysis.

Univariate, Bivariate, and Multivariate Statistics Using R

Univariate, Bivariate, and Multivariate Statistics Using R PDF Author: Daniel J. Denis
Publisher: John Wiley & Sons
ISBN: 1119549930
Category : Mathematics
Languages : en
Pages : 384

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Book Description
A practical source for performing essential statistical analyses and data management tasks in R Univariate, Bivariate, and Multivariate Statistics Using R offers a practical and very user-friendly introduction to the use of R software that covers a range of statistical methods featured in data analysis and data science. The author— a noted expert in quantitative teaching —has written a quick go-to reference for performing essential statistical analyses and data management tasks in R. Requiring only minimal prior knowledge, the book introduces concepts needed for an immediate yet clear understanding of statistical concepts essential to interpreting software output. The author explores univariate, bivariate, and multivariate statistical methods, as well as select nonparametric tests. Altogether a hands-on manual on the applied statistics and essential R computing capabilities needed to write theses, dissertations, as well as research publications. The book is comprehensive in its coverage of univariate through to multivariate procedures, while serving as a friendly and gentle introduction to R software for the newcomer. This important resource: Offers an introductory, concise guide to the computational tools that are useful for making sense out of data using R statistical software Provides a resource for students and professionals in the social, behavioral, and natural sciences Puts the emphasis on the computational tools used in the discovery of empirical patterns Features a variety of popular statistical analyses and data management tasks that can be immediately and quickly applied as needed to research projects Shows how to apply statistical analysis using R to data sets in order to get started quickly performing essential tasks in data analysis and data science Written for students, professionals, and researchers primarily in the social, behavioral, and natural sciences, Univariate, Bivariate, and Multivariate Statistics Using R offers an easy-to-use guide for performing data analysis fast, with an emphasis on drawing conclusions from empirical observations. The book can also serve as a primary or secondary textbook for courses in data analysis or data science, or others in which quantitative methods are featured.

Computing and Graphics in Statistics

Computing and Graphics in Statistics PDF Author: ANDREAS BUJA
Publisher: Springer
ISBN:
Category : Computers
Languages : en
Pages : 312

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Book Description
This IMA Volume in Mathematics and its Applications COMPUTING AND GRAPHICS IN STATISTICS is based on the proceedings of the last two weeks of the six week IMA 1989 summer program "Robustness, Diagnostics, Computing and Graphics in Statistics". An important objective of the organizers was to draw a broad set of statisticians working in statistical computation into collaboration on the challenging problems in this rapidly developing area. We thank the organizers of the robustness and diagnostics program Werner Stuetzle, Luke Tierney, Edward Wegman, Allan R. Wilks, and especially Andreas Buja and Paul A. Tukey who edited the proceedings. We also take this opportunity to thank those agencies whose financial support made the summer program possible: the Air Force Office of Scientific Research, the Army Research Office, the National Science Foundation, the National Security Agency and the Office of Naval Research. A vner Friedman Willard Miller, Jr. PREFACE This volume covers the computational part of IMA activities in statistics during the summer of 1989. The areas of statistical computing and graphics encompass a broad range of research, much of it represented here. The vigor of this research is probably best demonstrated by the fact that as of this writing two new journals are being launched, both entirely dedicated to these areas.

Using and Interpreting Statistics in the Social, Behavioral, and Health Sciences

Using and Interpreting Statistics in the Social, Behavioral, and Health Sciences PDF Author: William E. Wagner, III
Publisher: SAGE Publications
ISBN: 1544321090
Category : Social Science
Languages : en
Pages : 142

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Book Description
Using and Interpreting Statistics in the Social, Behavioral, and Health Sciences is designed to be paired with any undergraduate introduction to research methods text used by students in a variety of disciplines. It introduces students to statistics at the conceptual level—examining the meaning of statistics, and why researchers use a particular statistical technique, rather than computational skills. Focusing on descriptive statistics, and some more advanced topics such as tests of significance, measures of association, and regression analysis, this brief, inexpensive text is the perfect companion to help students who have not yet taken an introductory statistics course or are confused by the statistics used in the articles they are reading.

Visual Statistics

Visual Statistics PDF Author: Forrest W. Young
Publisher: John Wiley & Sons
ISBN: 1118165411
Category : Mathematics
Languages : en
Pages : 396

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Book Description
A visually intuitive approach to statistical data analysis Visual Statistics brings the most complex and advanced statistical methods within reach of those with little statistical training by using animated graphics of the data. Using ViSta: The Visual Statistics System-developed by Forrest Young and Pedro Valero-Mora and available free of charge on the Internet-students can easily create fully interactive visualizations from relevant mathematical statistics, promoting perceptual and cognitive understanding of the data's story. An emphasis is placed on a paradigm for understanding data that is visual, intuitive, geometric, and active, rather than one that relies on convoluted logic, heavy mathematics, systems of algebraic equations, or passive acceptance of results. A companion Web site complements the book by further demonstrating the concept of creating interactive and dynamic graphics. The book provides users with the opportunity to view the graphics in a dynamic way by illustrating how to analyze statistical data and explore the concepts of visual statistics. Visual Statistics addresses and features the following topics: * Why use dynamic graphics? * A history of statistical graphics * Visual statistics and the graphical user interface * Visual statistics and the scientific method * Character-based statistical interface objects * Graphics-based statistical interfaces * Visualization for exploring univariate data This is an excellent textbook for undergraduate courses in data analysis and regression, for students majoring or minoring in statistics, mathematics, science, engineering, and computer science, as well as for graduate-level courses in mathematics. The book is also ideal as a reference/self-study guide for engineers, scientists, and mathematicians. With contributions by highly regarded professionals in the field, Visual Statistics not only improves a student's understanding of statistics, but also builds confidence to overcome problems that may have previously been intimidating.

Graphics for Statistics and Data Analysis with R

Graphics for Statistics and Data Analysis with R PDF Author: Kevin J. Keen
Publisher: CRC Press
ISBN: 0429632215
Category : Mathematics
Languages : en
Pages : 508

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Book Description
Praise for the First Edition "The main strength of this book is that it provides a unified framework of graphical tools for data analysis, especially for univariate and low-dimensional multivariate data. In addition, it is clearly written in plain language and the inclusion of R code is particularly useful to assist readers’ understanding of the graphical techniques discussed in the book. ... It not only summarises graphical techniques, but it also serves as a practical reference for researchers and graduate students with an interest in data display." -Han Lin Shang, Journal of Applied Statistics Graphics for Statistics and Data Analysis with R, Second Edition, presents the basic principles of graphical design and applies these principles to engaging examples using the graphics and lattice packages in R. It offers a wide array of modern graphical displays for data visualization and representation. Added in the second edition are coverage of the ggplot2 graphics package, material on human visualization and color rendering in R, on screen, and in print. Features Emphasizes the fundamentals of statistical graphics and best practice guidelines for producing and choosing among graphical displays in R Presents technical details on topics such as: the estimation of quantiles, nonparametric and parametric density estimation; diagnostic plots for the simple linear regression model; polynomial regression, splines, and locally weighted polynomial regression for producing a smooth curve; Trellis graphics for multivariate data Provides downloadable R code and data for figures at www.graphicsforstatistics.com Kevin J. Keen is a Professor of Mathematics and Statistics at the University of Northern British Columbia (Prince George, Canada) and an Accredited Professional StatisticianTM by the Statistical Society of Canada and the American Statistical Association.