Data Analysis for the Life Sciences with R

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.

chapter 1 | 12 pages

Getting Started

chapter 2 | 56 pages

Inference

chapter 3 | 34 pages

Exploratory Data Analysis

chapter 4 | 22 pages

Matrix Algebra

chapter 5 | 52 pages

Linear Models

chapter 6 | 32 pages

Inference for High Dimensional Data

chapter 7 | 28 pages

Statistical Models

chapter 8 | 36 pages

Distance and Dimension Reduction

chapter 9 | 32 pages

Basic Machine Learning

chapter 10 | 38 pages

Batch Effects

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