Data Analysis for the Life Sciences with R

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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

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Title Statements

Full title :Data Analysis for the Life Sciences with R / Rafael A. Irizarry ; Michael I. Love

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Edition Statements

Publication Date:2016

Publication Statements

Publisher(s):Chapman and Hall/CRC
Place of Publication:Data Analysis for the Life Sciences with
Language:eng
Publication Date:2016

Notes

Introduction. Getting started. Inference. Exploratory data analysis. Robust summaries. Matrix algebra. Linear models. Inference for high dimensional data. Statistical models. Distance and dimension reduction. Statistical models. Distance and dimension reduction. Basic machine learning. Batch effects