Data analysis for the life sciences with R

✍ Scribed by Irizarry, Rafael A.; Love, Michael I

Publisher: Chapman and Hall/CRC
Year: 2017
Tongue: English
Leaves: 376
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained

✦ Table of Contents

Content: 1. Getting started --
2. Inference --
3. Exploratory data analysis --
4. Matrix algebra --
5. Linear models --
6. Inference for high dimensional data --
7. Statistical models --
8. Distance and dimension reduction --
9. Basic machine Learning --
10. Batch effects.

✦ Subjects

Research;Statistical methods;Life sciences;REFERENCE;Questions & Answers

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