Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis...

The cost of statistical computing software has precluded many universities from installing these valuable computational and analytical tools. R, a powerful open-source software package, was created in response to this issue. It has enjoyed explosive growth since its introduction, owing to its coherence, flexibility, and free availability....

Since the publication of the bestselling first edition, many advances have been made in exploratory data analysis (EDA). Covering innovative approaches for dimensionality reduction, clustering, and visualization, Exploratory Data Analysis with MATLAB^®, Second Edition uses numerous examples and applications to...

• Explore how to analyze your data in various innovative ways and turn them into insight
• Learn to use the D3.js visualization tool for exploratory data analysis
• ...

The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical...

• Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data
• Get beyond the theory and implement real-world projects in data science using...

• Learn functional programming with an easy-to-follow combination of theory and tutorials
• Build a complete automated trading system with the help of code snippets
• Use F#...