Introduction to data science and statistical programming with R

by Thomas Mailund

Data Science is a buzzword these days. Everyone wants to do data science. What it really is is a combination of statistics and machine learning where you want to pull some information out of a data set you have. This book will not attempt to present data science for more than it is. It will teach you how to go from a data set you have to how to model your data and perhaps got some knowledge out of your data. That is, after all, all you can hope to get out of data.
The book is based on a few classes I have held on R programming and data analysis. It is just the experiences of what I have learned doing data analysis that I try to teach my students. Doing data science is not actually an exact science. It is more of an art. You learn by doing. So all I can do in this book is showing you how I approach data analysis, so that is what I do.
The first half of the book concerns how to do data analysis. The second how to write R packages for distributing your new data analysis methods.

469 pages, ebook

Published July 1, 2016

Reviews

[Maria Izabel · Rating 5 out of 5]

This book is made for those who have learned R by using and never understood very much its structure. Thomas Mailund writes about statistical programming as if it was a fairy-tale by bringing complex assumptions into the level of most of the readers. With such a smooth style it is impossible to not be involved and learn about R, supervised/unsupervised learning, unit testing and more.