David R. Sessions's Books

R Visualizations

Derive Meaning from Data

By: David Gerbing

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R Visualizations

Derive Meaning from Data

By: David Gerbing

R Visualizations: Derive Meaning from Data focuses on one of the two major topics of data analytics: data visualization, a.k.a., computer graphics. In the book, major R systems for visualization are discussed, organized by topic and not by system. Anyone doing data analysis will be shown how to use R to generate any of the basic visualizations with the R visualization systems. Further, this book introduces the author’s lessR system, which always can accomplish a visualization with less coding than the use of other systems, sometimes dramatically so, and also provides accompanying statistical analyses. Key Features Presents thorough coverage of the leading R visualization system, ggplot2. Gives specific guidance on using base R graphics to attain visualizations of the same quality as those provided by ggplot2. Shows how to create a wide range of data visualizations: distributions of categorical and continuous variables, many types of scatterplots including with a third variable, time series, and maps. Inclusion of the various approaches to R graphics organized by topic instead of by system. Presents the recent work on interactive visualization in R. David W. Gerbing received his PhD from Michigan State University in 1979 in quantitative analysis, and currently is a professor of quantitative analysis in the School of Business at Portland State University. He has published extensively in the social and behavioral sciences with a focus on quantitative methods. His lessR package has been in development since 2009.

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Page Count

252

Publisher

CRC Press

Published Date

ISBN 10

0429894929

ISBN 13

9780429894923

Behavior Analysis and Learning

A Biobehavioral Approach, Sixth Edition

By: W. David Pierce,Carl D. Cheney

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Behavior Analysis and Learning

A Biobehavioral Approach, Sixth Edition

By: W. David Pierce,Carl D. Cheney

Using a consistent Skinnerian perspective, Behavior Analysis and Learning: A Biobehavioral Approach, Sixth Edition provides an advanced introduction to the principles of behavior analysis and learned behaviors, covering a full range of principles from basic respondent and operant conditioning through applied behavior analysis into cultural design. The textbook uses Darwinian, neurophysiological, and biological theories and research to inform B. F. Skinner’s philosophy of radical behaviorism. The sixth edition expands focus on neurophysiological mechanisms and their relation to the experimental analysis of behavior, providing updated studies and references to reflect current expansions and changes in the field of behavior analysis. By bringing together ideas from behavior analysis, neuroscience, and epigenetics under a selectionist framework, this textbook facilitates understanding of behavior at environmental, genetic, and neurophysiological levels. This "grand synthesis" of behavior, neuroscience, and neurobiology roots behavior firmly in biology. The book includes special sections, "New Directions," "Focus On," "Note On," "On the Applied Side," and "Advanced Section," which enhance student learning and provide greater insight on specific topics. This book is a valuable resource for advanced undergraduate and graduate students in psychology or other behavior-based disciplines, especially behavioral neuroscience. For additional resources to use alongside the textbook, consult the Companion Website at www.routledge.com/cw/pierce.

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Page Count

622

Publisher

Taylor & Francis

Published Date

ISBN 10

135177980X

ISBN 13

9781351779807

R Data Analysis without Programming

Explanation and Interpretation

By: David W. Gerbing

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R Data Analysis without Programming

Explanation and Interpretation

By: David W. Gerbing

The new edition of this innovative book, R Data Analysis without Programming, prepares the readers to quickly analyze data and interpret statistical results using R. Professor Gerbing has developed lessR, a ground-breaking method in alleviating the challenges of R programming. The lessR extends R, removing the need for programming. This edition expands upon the first edition’s introduction to R through lessR, which enables the readers to learn how to organize data for analysis, read the data into R, and generate output without performing numerous functions and programming exercises first. With lessR, readers can select the necessary procedure and change the relevant variables with simple function calls. The text reviews and explains basic statistical procedures with the lessR enhancements added to the standard R environment. Using lessR, data analysis with R becomes immediately accessible to the novice user and easier to use for the experienced user. Highlights along with content new to this edition include: Explanation and Interpretation of all data analysis techniques; much more than a computer manual, this book shows the reader how to explain and interpret the results. Introduces the concepts and commands reviewed in each chapter. Clear, relaxed writing style more effectively communicates the underlying concepts than more stilted academic writing. Extensive margin notes highlight, define, illustrate, and cross-reference the key concepts. When readers encounter a term previously discussed, the margin notes identify the page number for the initial introduction. Scenarios that highlight the use of a specific analysis followed by the corresponding R/lessR input, output, and an interpretation of the results. Numerous examples of output from psychology, business, education, and other social sciences, that demonstrate the analysis and how to interpret results. Two data sets are analyzed multiple times in the book, provide continuity throughout. Comprehensive: A wide range of data analysis techniques are presented throughout the book. Integration with machine learning as regression analysis is presented from both the traditional perspective and from the modern machine learning perspective. End of chapter problems help readers test their understanding of the concepts. A website at www.lessRstats.com that features the data sets referenced in both standard text and SPSS formats so readers can practice using R/lessR by working through the text examples and worked problems, R/lessR videos to help readers better understand the program, and more. This book is ideal for graduate and undergraduate courses in statistics beyond the introductory course, research methods, and/or any data analysis course, taught in departments of psychology, business, education, and other social and health sciences; this book is also appreciated by researchers doing data analysis. Prerequisites include basic statistical knowledge, though the concepts are explained from the beginning in the book. Previous knowledge of R is not assumed.

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Page Count

591

Publisher

Taylor & Francis

Published Date

ISBN 10

1000812901

ISBN 13

9781000812909

R for Data Science Cookbook

By: Yu-Wei, Chiu (David Chiu)

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R for Data Science Cookbook

By: Yu-Wei, Chiu (David Chiu)

Over 100 hands-on recipes to effectively solve real-world data problems using the most popular R packages and techniques About This Book Gain insight into how data scientists collect, process, analyze, and visualize data using some of the most popular R packages Understand how to apply useful data analysis techniques in R for real-world applications An easy-to-follow guide to make the life of data scientist easier with the problems faced while performing data analysis Who This Book Is For This book is for those who are already familiar with the basic operation of R, but want to learn how to efficiently and effectively analyze real-world data problems using practical R packages. What You Will Learn Get to know the functional characteristics of R language Extract, transform, and load data from heterogeneous sources Understand how easily R can confront probability and statistics problems Get simple R instructions to quickly organize and manipulate large datasets Create professional data visualizations and interactive reports Predict user purchase behavior by adopting a classification approach Implement data mining techniques to discover items that are frequently purchased together Group similar text documents by using various clustering methods In Detail This cookbook offers a range of data analysis samples in simple and straightforward R code, providing step-by-step resources and time-saving methods to help you solve data problems efficiently. The first section deals with how to create R functions to avoid the unnecessary duplication of code. You will learn how to prepare, process, and perform sophisticated ETL for heterogeneous data sources with R packages. An example of data manipulation is provided, illustrating how to use the “dplyr” and “data.table” packages to efficiently process larger data structures. We also focus on “ggplot2” and show you how to create advanced figures for data exploration. In addition, you will learn how to build an interactive report using the “ggvis” package. Later chapters offer insight into time series analysis on financial data, while there is detailed information on the hot topic of machine learning, including data classification, regression, clustering, association rule mining, and dimension reduction. By the end of this book, you will understand how to resolve issues and will be able to comfortably offer solutions to problems encountered while performing data analysis. Style and approach This easy-to-follow guide is full of hands-on examples of data analysis with R. Each topic is fully explained beginning with the core concept, followed by step-by-step practical examples, and concluding with detailed explanations of each concept used.

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Page Count

452

Publisher

Packt Publishing Ltd

Published Date

ISBN 10

1784392049

ISBN 13

9781784392048

R: Recipes for Analysis, Visualization and Machine Learning

By: Viswa Viswanathan,Shanthi Viswanathan,Atmajitsinh Gohil,Yu-Wei, Chiu (David Chiu)

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R: Recipes for Analysis, Visualization and Machine Learning

By: Viswa Viswanathan,Shanthi Viswanathan,Atmajitsinh Gohil,Yu-Wei, Chiu (David Chiu)

Get savvy with R language and actualize projects aimed at analysis, visualization and machine learning About This Book Proficiently analyze data and apply machine learning techniques Generate visualizations, develop interactive visualizations and applications to understand various data exploratory functions in R Construct a predictive model by using a variety of machine learning packages Who This Book Is For This Learning Path is ideal for those who have been exposed to R, but have not used it extensively yet. It covers the basics of using R and is written for new and intermediate R users interested in learning. This Learning Path also provides in-depth insights into professional techniques for analysis, visualization, and machine learning with R – it will help you increase your R expertise, regardless of your level of experience. What You Will Learn Get data into your R environment and prepare it for analysis Perform exploratory data analyses and generate meaningful visualizations of the data Generate various plots in R using the basic R plotting techniques Create presentations and learn the basics of creating apps in R for your audience Create and inspect the transaction dataset, performing association analysis with the Apriori algorithm Visualize associations in various graph formats and find frequent itemset using the ECLAT algorithm Build, tune, and evaluate predictive models with different machine learning packages Incorporate R and Hadoop to solve machine learning problems on big data In Detail The R language is a powerful, open source, functional programming language. At its core, R is a statistical programming language that provides impressive tools to analyze data and create high-level graphics. This Learning Path is chock-full of recipes. Literally! It aims to excite you with awesome projects focused on analysis, visualization, and machine learning. We'll start off with data analysis – this will show you ways to use R to generate professional analysis reports. We'll then move on to visualizing our data – this provides you with all the guidance needed to get comfortable with data visualization with R. Finally, we'll move into the world of machine learning – this introduces you to data classification, regression, clustering, association rule mining, and dimension reduction. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: R Data Analysis Cookbook by Viswa Viswanathan and Shanthi Viswanathan R Data Visualization Cookbook by Atmajitsinh Gohil Machine Learning with R Cookbook by Yu-Wei, Chiu (David Chiu) Style and approach This course creates a smooth learning path that will teach you how to analyze data and create stunning visualizations. The step-by-step instructions provided for each recipe in this comprehensive Learning Path will show you how to create machine learning projects with R.

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958

Publisher

Packt Publishing Ltd

Published Date

ISBN 10

178728879X

ISBN 13

9781787288799

A Topical Guide to Schenkerian Literature

An Annotated Bibliography with Indices

By: David Carson Berry

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A Topical Guide to Schenkerian Literature

An Annotated Bibliography with Indices

By: David Carson Berry

To the growing list of Pendragon Press publications devoted to the work of Heinrich Schenker, we wish to announce the addition of this much-needed bibliography. The author, a student of Allen Forte, has created a work useful to a wide range of researchers music theorists, musicologists, music librarians and teachers. The Guide is the largest Schenkerian reference work ever published. At nearly 600 pages, it contains 3600 entries (2200 principal, 1400 secondary) representing the work of 1475 authors. Fifteen broad groupings encompass seventy topical headings, many of which are divided and subdivided again, resulting in a total of 271 headings under which entries are collected.

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610

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Pendragon Press

Published Date

ISBN 10

1576470954

ISBN 13

9781576470954

Medical Charlatanism in Early Modern Italy

By: David Gentilcore

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Medical Charlatanism in Early Modern Italy

By: David Gentilcore

From the mid-sixteenth century onwards, the Italian Protomedicato tribunals, Colleges of Physicians, or Health Offices (jurisdiction varied from state to state) required charlatans to submit their wares for inspection and, upon approval, pay a licence fee in order to set up a stage from which to perform and sell them. The licensing of charlatans became an administrative routine. As far as the medical magistracies were concerned, charlatans had a defineable identity, constituting a specific trade or occupation. This book studies the way charlatans were represented, by contemporaries and by historians, how they saw themselves and, most importantly, it reconstructs the place of charlatans in early modern Italy. It explores the goods and services charlatans provided, their dealings with the public and their marketing strategies. It does so from a range of perspectives: social, cultural, economic, political, geographical, biographical and, of course, medical. Charlatans are not just some curiosity on the fringes of medicine: they offered health care to an extraordinarily wide sector of the population. Moreover, from their origins in Renaissance Italy, the Italian ciarlatano was the prototype for itinerant medical practitioners throughout Europe. This book offers a different look at charlatans. It is the first to take seriously the licences issued to charlatans in the Italian states, compiling them into a 'charlatans database' of over 1,300 charlatans active throughout Italy over the course of some three centuries. In addition, it makes use of other types of archival documents, such as trial records and wills, to give the charlatans a human face, as well as a wide range of artistic and printed sources, not forgetting the output of the charlatans themselves, in the form of handbills and pamphlets.

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Page Count

446

Publisher

OUP Oxford

Published Date

ISBN 10

0191514292

ISBN 13

9780191514296

Book's by David R. Sessions

R Visualizations

R Visualizations

Behavior Analysis and Learning

Behavior Analysis and Learning

R Data Analysis without Programming

R Data Analysis without Programming

R for Data Science Cookbook

R for Data Science Cookbook

R: Recipes for Analysis, Visualization and Machine Learning

R: Recipes for Analysis, Visualization and Machine Learning

A Topical Guide to Schenkerian Literature

A Topical Guide to Schenkerian Literature

Medical Charlatanism in Early Modern Italy

Medical Charlatanism in Early Modern Italy

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