June 2016
Beginner to intermediate
398 pages
8h 51m
English
Overview
"Simulation for Data Science with R" introduces data professionals to fundamental and advanced simulation techniques using R. You'll understand essential statistical modeling concepts and learn to apply simulation methods to tackle data challenges and enhance your decision-making skills.
What this Book will help me do
- Master five popular simulation methodologies including Monte Carlo and Agent-Based Modeling.
- Learn to simulate real-world data to uncover patterns and enhance predictions.
- Enhance your R programming expertise by exploring its advanced statistical features.
- Gain hands-on experience solving statistical problems through practical examples.
- Develop comprehensive statistical models aimed at real-world decision support.
Author(s)
Matthias Templ is a seasoned data science expert with extensive experience in statistical modeling and simulations using R. His work is rooted in real-world problem solving, outlining frameworks that are practical and research-driven. With a dedication to education, Matthias conveys his knowledge in an accessible and supportive manner.
Who is it for?
If you're experienced in computational methods and wish to refine your understanding of R for advanced statistical simulations, this book is for you. It's ideal for analysts or scientists aiming to enhance their decision-making with simulated data models. Prior experience with R is recommended to fully engage with the rigorous concepts presented.
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