<span><u><b>What's Special about this Book:</b></u><br>The ideal reader for this book will be quantitatively literate and has a basic understanding of statistical concepts and R programming. The student should have a basic understanding of statistical inference such as contained in "Statistical infe
Regression Models for Data Science in R
โ Scribed by coll
- Year
- 2022
- Tongue
- English
- Leaves
- 83
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Table of Contents
Beginning
๐ SIMILAR VOLUMES
The classical Poisson, geometric and negative binomial regression models for count data belong to the family of generalized linear models and are available at the core of the statistics toolbox in the R system for statistical computing. After reviewing the conceptual and computational features of th
<span><p>Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R.</p><
Rรฉsumรฉ : Presenting best practices for data analysis and software development in R, this comprehensive book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. --
Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R.<br /><i>Data