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An Introduction to Data Analysis R: Hands-on Coding, Mining, Visualization and Statistics from Scratch
Coles
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An Introduction to Data Analysis R: Hands-on Coding, Mining, Visualization and Statistics from Scratch in Brampton, ON
By None
Current price: $109.69
Original price: $137.06

Coles
An Introduction to Data Analysis R: Hands-on Coding, Mining, Visualization and Statistics from Scratch in Brampton, ON
By None
Current price: $109.69
Original price: $137.06
Loading Inventory...
Size: Kobo eBook
*Product information and pricing may vary - to confirm current pricing, availability, shipping, and return information please contact Coles. In the event of a pricing discrepancy, the retailer's price will apply.
This textbook offers an easy-to-follow, practical guide to modern data analysis using the programming language R. The chapters cover topics such as the fundamentals of programming in R, data collection and preprocessing, including web scraping, data visualization, and statistical methods, including multivariate analysis, and feature exercises at the end of each section. The text requires only basic statistics skills, as it strikes a balance between statistical and mathematical understanding and implementation in R, with a special emphasis on reproducible examples and real-world applications. This textbook is primarily intended for undergraduate students of mathematics, statistics, physics, economics, finance and business who are pursuing a career in data analytics. It will be equally valuable for master students of data science and industry professionals who want to conduct data analyses.
This textbook offers an easy-to-follow, practical guide to modern data analysis using the programming language R. The chapters cover topics such as the fundamentals of programming in R, data collection and preprocessing, including web scraping, data visualization, and statistical methods, including multivariate analysis, and feature exercises at the end of each section. The text requires only basic statistics skills, as it strikes a balance between statistical and mathematical understanding and implementation in R, with a special emphasis on reproducible examples and real-world applications. This textbook is primarily intended for undergraduate students of mathematics, statistics, physics, economics, finance and business who are pursuing a career in data analytics. It will be equally valuable for master students of data science and industry professionals who want to conduct data analyses.






















