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README.md

D-Lab R-FUN!damentals introductory workshop series

This is the repository for D-Lab's introductory R-Fundamentals workshop series.

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Laptop required. Before Part 1 be sure to:

  1. Download and install R
  2. Download and install RStudio Desktop Open Source License FREE
  3. Download the R-Fundamentals workshop materials to your Desktop
  • Click the green “Clone or download” button
  • Click “Download Zip”
  • Extract the files some place convenient (i.e., Desktop)
    • if you are a Git user, simply clone this repository

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Learning objectives
Part 1:

  1. Variable definition (three piece recipe): X <- 5
  2. Data types: numeric, integer, character, logical, factor
  3. Data structures: vector, list, matrix, data frame
  4. Pseudo-random generation: set.seed, seq, :, runif, rnorm, sample
  5. Save and practice: write.csv() and swirl()

Part 2:

  1. Set your working directory to the R-Fundamentals "data" folder.
  2. Load the animals data frame
  3. Load the sleep_VIM data set
  4. Subsetting: one ($) versus two dimensions ([ , ])
  5. Identify and count missing data: sum and is.na
  6. Wide and long format data: melt and dcast

Part 3:

  1. Summarizing data: summary, describe, table
  2. Plotting data: hist, plot, boxplot
  3. ggplot2: +, three parts: data, aes, geom
  4. Testing: t.test, aov, TukeyHSD, cor.test, lm

Part 4:

  1. For loops: for, if, else, ifelse
  2. Functions: function
  3. Automation - Monte Carlo simulation: sample, die_roll_mean, replicate, hist
  4. The birthday problem

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Visit the D-Lab homepage and compact calendar. We offer a variety of:

  1. workshop trainings
  2. working groups
  3. consulting services
  4. data services

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Visit these sites for R help:
Quick-R
UCLA idre
R-bloggers
Stack Overflow - R

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View course offerings at UC Berkeley:
Department of Statistics
Data Science
School of Information
Interdepartmental Group in Biostatistics
data8
EECS