Statistics with R for Data Visualization

Mohsen Nady

ISBN 10: 1774699583 / ISBN 13: 9781774699584

Published by Arcler Press, CA, 2024

About this Item

This book covers the use of R programming language for data visualization. The large real-world datasets can be quickly visualized to gain several insights from it using R. Whether the data is already clean or needs some preliminary steps before data visualization like data cleaning and wrangling, all these can be done using R to produce elegant, publication-ready, and exciting plots. This book covers different plot types from simple ones like univariate and bivariate plots (histograms, box plots, violin plots, scatter plots, density plots, bar graphs, pie charts, tree maps, beeswarm plots, Cleveland dot charts, line plots, etc) to more complex ones like mapping and visualizing patterns of missing data (upset plots, different Stamen map types with different zoom levels). All these were shown using free real-world data sets to illustrate the diverse capability of R for data visualization.

Seller Inventory # LU-9781774699584

Bibliographic Details

• Title: Statistics with R for Data Visualization
• Publisher: Arcler Press, CA
• Publication Date: 2024
• Language: English
• ISBN 10: 1774699583
• ISBN 13: 9781774699584
• Binding: Hardback
• Condition: New
• Weight: 394 grams

About this title

Synopsis

This book covers the use of R programming language for data visualization. The large real-world datasets can be quickly visualized to gain several insights from it using R. Whether the data is already clean or needs some preliminary steps before data visualization like data cleaning and wrangling, all these can be done using R to produce elegant, publication-ready, and exciting plots. This book covers different plot types from simple ones like univariate and bivariate plots (histograms, box plots, violin plots, scatter plots, density plots, bar graphs, pie charts, tree maps, beeswarm plots, Cleveland dot charts, line plots, etc) to more complex ones like mapping and visualizing patterns of missing data (upset plots, different Stamen map types with different zoom levels). All these were shown using free real-world data sets to illustrate the diverse capability of R for data visualization.

About the Author

Mohsen Nady is a pharmacist with a M.D. in Microbiology and a Diploma in Industrial Pharmacy. Besides, Mohsen has more than 10 years of experience in Statistics and Data Analytics. Mohsen has applied his skills to different projects related to Genomics, Microbiology, Biostatistics, Six Sigma, Data Analytics, Data Visualization, Building Apps, Geography, Market Analysis, Business Analysis, Machine Learning, etc. Mohsen also published his thesis in a high-impact journal that attracted many citations, where all the statistical analyses were performed by him in addition to the methodological part. Furthermore, Mohsen has earned different certificates, from top universities (Harvard, Johns Hopkins, Denmark, etc) in Statistics, Data Analytics, Data Visualization, and Machine Learning that highlight his outstanding diverse skills.