Learn R for Applied Statistics: With Data Visualizations, Regressions, and Statistics, Hui Eric Goh Ming
Автор: Chun-houh Chen; Wolfgang Karl H?rdle; Antony Unwin Название: Handbook of Data Visualization ISBN: 3662500744 ISBN-13(EAN): 9783662500743 Издательство: Springer Рейтинг: Цена: 62888.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Antony Unwin, Chun-houh Chen, Wolfgang K. H?rdle 1. 1 Computational Statistics and Data Visualization . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Data Visualization and Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Presentation and Exploratory Graphics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Graphics and Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1. 2 The Chapters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Summary and Overview; Part II. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Summary and Overview; Part III. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Summary and Overview; Part IV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 The Authors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1. 3 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4 Antony Unwin, Chun-houh Chen, Wolfgang K. H?rdle Computational Statistics 1. 1 and Data Visualization Tis book is the third volume of the Handbook of Computational Statistics and c- ers the ?eld of data visualization. In line with the companion volumes, it contains a collection of chapters by experts in the ?eld to present readers with an up-to-date and comprehensive overview of the state of the art. Data visualization is an active area of application and research, and this is a good time to gather together a summary of current knowledge. Graphic displays are ofen very e?ective at communicating information. Tey are also very ofen not e?ective at communicating information. Two important reasons for this state of a?airs are that graphics can be produced with a few clicks of the mouse without any thought and the design of graphics is not taken seriously in many scienti?c textbooks.
Автор: Healy Kieran Название: Data Visualization: A Practical Introduction ISBN: 0691181624 ISBN-13(EAN): 9780691181622 Издательство: Wiley Рейтинг: Цена: 6653.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
An accessible primer on how to create effective graphics from data
This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way.
Data Visualization builds the reader's expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective "small multiple" plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible.
Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings.
Provides hands-on instruction using R and ggplot2
Shows how the "tidyverse" of data analysis tools makes working with R easier and more consistent
Includes a library of data sets, code, and functions
Автор: Korosteleva, Olga (california State University, Long Beach, Usa) Guo, Weibin Название: Advanced regression models with sas and r ISBN: 1138049018 ISBN-13(EAN): 9781138049017 Издательство: Taylor&Francis Рейтинг: Цена: 14086.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Advanced Regression Models with SAS and R exposes the reader to the modern world of regression analysis. The material covered by this book consists of regression models that go beyond linear regression, including models for right-skewed, categorical and hierarchical observations. The book presents the theory as well as fully worked-out numerical examples with complete SAS and R codes for each regression. The emphasis is on model accuracy and the interpretation of results. For each regression, the fitted model is presented along with interpretation of estimated regression coefficients and prediction of response for given values of predictors.
Features:
Presents the theoretical framework for each regression.
Discusses data that are categorical, count, proportions, right-skewed, longitudinal and hierarchical.
Uses examples based on real-life consulting projects.
Provides complete SAS and R codes for each example.
Includes several exercises for every regression.
Advanced Regression Models with SAS and R is designed as a text for an upper division undergraduate or a graduate course in regression analysis. Prior exposure to the two software packages is desired but not required.
The Author:
Olga Korosteleva is a Professor of Statistics at California State University, Long Beach. She teaches a large variety of statistical courses to undergraduate and master's students. She has published three statistical textbooks. For a number of years, she has held the position of faculty director of the statistical consulting group. Her research interests lie mostly in applications of statistical methodology through collaboration with her clients in health sciences, nursing, kinesiology, and other fields.
Автор: Embarak, Dr. Ossama Название: Data analysis and visualizations using python ISBN: 1484241088 ISBN-13(EAN): 9781484241080 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming techniques used in data science. Moving on to data visualization, you will see how it caters to modern business needs and forms a key factor in decision-making. You will also take a look at some popular data visualization libraries in Python.
Shifting focus to data structures, you will learn the various aspects of data structures from a data science perspective. You will then work with file I/O and regular expressions in Python, followed by gathering and cleaning data. Moving on to exploring and analyzing data, you will look at advanced data structures in Python. Then, you will take a deep dive into data visualization techniques, going through a number of plotting systems in Python.
In conclusion, you will complete a detailed case study, where you’ll get a chance to revisit the concepts you’ve covered so far.
What You Will Learn
Use Python programming techniques for data scienceMaster data collections in Python Create engaging visualizations for BI systemsDeploy effective strategies for gathering and cleaning dataIntegrate the Seaborn and Matplotlib plotting systems
Who This Book Is For
Developers with basic Python programming knowledge looking to adopt key strategies for data analysis and visualizations using Python.
Автор: Gerbing, David Название: R Visualizations ISBN: 1138599638 ISBN-13(EAN): 9781138599635 Издательство: Taylor&Francis Рейтинг: Цена: 12554.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is focused on one of the two major topics of doing data analysis: data visualization, aka, computer graphics. In one place the 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 basic visualizations with any of R visualization systems.
Описание: This book describes interactive data visualization using the R package plotly. It focuses on tools and techniques that data analysts should find useful for asking follow-up questions from their data using interactive web graphics. A basic understanding of R is assumed.
Автор: Tierny Julien Название: Topological Data Analysis for Scientific Visualization ISBN: 3319715062 ISBN-13(EAN): 9783319715063 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 1. Introduction.- 2. Background: 2.1 Data representation.- 2.2 Topological abstractions.- 2.3 Algorithms and applications.- 3. Abstraction: 3.1 Efficient topological simplification of scalar fields.- 3.2 Efficient Reeb graph computation for volumetric meshes.- 4. Interaction: 4.1 Topological simplification of isosurfaces.- 4.2 Interactive editing of topological abstractions.- 5. Analysis: 5.1 Exploration of turbulent combustion simulations.- 5.2 Quantitative analysis of molecular interactions.- 6. Perspectives: 6.1 Emerging constraints.- 6.2 Emerging data types.- 7. Conclusion.
Автор: Peter Goos, David Meintrup Название: Statistics with JMP: Hypothesis Tests, ANOVA and Regression ISBN: 1119097150 ISBN-13(EAN): 9781119097150 Издательство: Wiley Рейтинг: Цена: 9654.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Statistics with JMP: Hypothesis Tests, ANOVA and Regression
Peter Goos, University of Leuven and University of Antwerp, Belgium
David Meintrup, University of Applied Sciences Ingolstadt, Germany
A first course on basic statistical methodology using JMP
This book provides a first course on parameter estimation (point estimates and confidence interval estimates), hypothesis testing, ANOVA and simple linear regression. The authors approach combines mathematical depth with numerous examples and demonstrations using the JMP software.
Key features:
Provides a comprehensive and rigorous presentation of introductory statistics that has been extensively classroom tested.
Pays attention to the usual parametric hypothesis tests as well as to non-parametric tests (including the calculation of exact p-values).
Discusses the power of various statistical tests, along with examples in JMP to enable in-sight into this difficult topic.
Promotes the use of graphs and confidence intervals in addition to p-values.
Course materials and tutorials for teaching are available on the book's companion website.
Masters and advanced students in applied statistics, industrial engineering, business engineering, civil engineering and bio-science engineering will find this book beneficial. It also provides a useful resource for teachers of statistics particularly in the area of engineering.
Автор: Fox John, Weisberg Sanford Название: An R Companion to Applied Regression ISBN: 1544336470 ISBN-13(EAN): 9781544336473 Издательство: Sage Publications Рейтинг: Цена: 18058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied regression analysis.
Описание: This book describes interactive data visualization using the R package plotly. It focuses on tools and techniques that data analysts should find useful for asking follow-up questions from their data using interactive web graphics. A basic understanding of R is assumed.
Описание: Create compelling business infographics with SAS and familiar office productivity tools.
A picture is worth a thousand words, but what if there are a billion words? When analyzing big data, you need a picture that cuts through the noise. This is where infographics come in. Infographics are a representation of information in a graphic format designed to make the data easily understandable. With infographics, you don't need deep knowledge of the data. The infographic combines story telling with data and provides the user with an approachable entry point into business data.
Infographics Powered by SAS: Data Visualization Techniques for Business Reporting shows you how to create graphics to communicate information and insight from big data in the boardroom and on social media.
Learn how to create business infographics for all occasions with SAS and learn how to build a workflow that lets you get the most from your SAS system without having to code anything, unless you want to This book combines the perfect blend of creative freedom and data governance that comes from leveraging the power of SAS and the familiarity of Microsoft Office.
Topics covered in this book include:
SAS Visual Analytics
SAS Office Analytics
SAS/GRAPH software (SAS code examples)
Data visualization with SAS
Creating reports with SAS
Using reports and graphs from SAS to create business presentations
Using SAS within Microsoft Office
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