Video description
R Programming LiveLessons: Fundamentals to Advanced is a tour through the most important parts of R, the statistical programming language, from the very basics to complex modeling. It covers reading data, programming basics, visualization, data munging, regression, classification, clustering, modern machine learning and more.
About the Author:
Data scientist, Columbia University adjunct Professor, author and organizer of the New York Open Statistical Programming meetup Jared P. Lander presents the 20 percent of R functionality to accomplish 80 percent of most statistics needs. This video is based on the material in R for Everyone and is a condensed version of the course Mr. Lander teaches at Columbia. You start with simply installing R and setting up a productive work environment. You then learn the basics of data and programming using these skills to munge and prepare data for analysis. You then learn visualization, modeling and predicting and close with generating reports and websites and building R packages.
Table of contents
 Introduction
 Lesson 1: Getting Started with R
 Lesson 2: The Basic Building Blocks in R
 Lesson 3: Advanced Data Structures in R
 Lesson 4: Reading Data into R

Lesson 5: Making Statistical Graphs
 Learning objectives
 5.1 Find the diamonds data
 5.2 Make histograms with base graphics
 5.3 Make scatterplots with base graphics
 5.4 Make boxplots with base graphics
 5.5 Get familiar with ggplot2
 5.6 Plot histograms and densities with ggplot2
 5.7 Make scatterplots with ggplot2
 5.8 Make boxplots and violin plots with ggplot2
 5.9 Make line plots
 5.10 Create small multiples
 5.11 Control colors and shapes
 5.12 Add themes to graphs

Lesson 6: Basics of Programming
 Learning objectives
 6.1 Write the classic 'Hello, World!' example
 6.2 Understand the basics of function arguments
 6.3 Return a value from a function
 6.4 Gain flexibility with do.call
 6.5 Use if statements to control program flow
 6.6 Stagger if statements with else
 6.7 Check multiple statements with switch
 6.8 Run checks on entire vectors
 6.9 Check compound statements
 6.10 Iterate with a for loop
 6.11 Iterate with a while loop
 6.12 Control loops with break and next
 Lesson 7: Data Munging
 Lesson 8: Manipulating Strings
 Lesson 9: Basic Statistics

Lesson 10: Linear Models
 Learning objectives
 10.1 Fit simple linear models
 10.2 Explore the data
 10.3 Fit multiple regression models
 10.4 Fit logistic regression
 10.5 Fit Poisson regression
 10.6 Analyze survival data
 10.7 Assess model quality with residuals
 10.8 Compare models
 10.9 Judge accuracy using crossvalidation
 10.10 Estimate uncertainty with the bootstrap
 10.11 Choose variables using stepwise selection
 Lesson 11: Other Models
 Lesson 12: Time Series
 Lesson 13: Clustering
 Lesson 14: Reports and Slideshows with knitr
 Lesson 15: Package Building
 Summary
Product information
 Title: R Programming LiveLessons (Video Training): Fundamentals to Advanced
 Author(s):
 Release date: September 2013
 Publisher(s): Pearson
 ISBN: 0133578860
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