• Go to github.com/majerus/paideia_reed_college/R_for_beginners
  • Unzip paideia.zip
  • Open slides.html
• Open RStudio:
  • Open a Finder window
  • Then click on Applications > RStudio

• R is statistical software that is command-line based. It has its own default interface.
• RStudio is a program which IMO has a more intuitive and user friendly interface.

Like getting under hood of a car!

In increasing order of relevance:

• Can get slow
• Unstructured technical help: mostly online
• Requires programming knowledge
• It is not point and click software
• Steep learning curve

In increasing order of relevance:

• Open source
• People can contribute extensions called packages to R from statistics, biology, economics, social sciences, political science, etc.
• Free!

• "Learn by doing"
• Feel free to run ahead
• Important topics will be covered as we go
• We are only getting you started

• Console Window: is where you run/execute commands. The > is the prompt; it means R is ready to receive commands. If you don’t see a > and want to restart, press ESC.
• R Script Window: You can edit and save your files here.

1. Tab: complete command and variable names
2. (From console) Up: scroll thru previous commands
3. (From editor) CMD+Enter or Control+Enter: execute in console either current line or highlighted code

Your turn. Open Paideia.R in RStudio

• Difference between R console and R scripts
• Comments: it’s good practice to include them
• Variables and how to assign them
• Vectors and matrices
• Functions and their arguments
• Help files

Questions

• Did students who handed in their final exams earlier do better?
• Did the final exam grade vary much by major?

Data: for each student who took MATH 141 Intro to Prob & Stats in Fall 2013

• Exam score
• Time to submission
• Major (3 categories): Econ, Bio, Rest

Data is saved in Comma Separated Value (CSV) file format.

• Open your Excel/OpenOffice spreadsheet and save as CSV
• Import CSV into R
• Exploratory data analysis on numerical variables: summary statistics and basic visualizations

Question: What did the San Francisco OkCupid online dating pool look like in June 2012?

• What were the users sex and sexual orientation?
• How tall were they? Then split by male and female.

Data: This is the result of a Python script that scraped the OkCupid website. We consider the n=59,946 users who were

• members on 2012/06/26
• within 25 miles of SF
• online in the last year
• have at least one photo Their public profiles were pulled on 2012/06/30. i.e. only data that’s visible to the public

• How to do basic exploratory data analysis on categorical variables
  • table() to get frequency counts
  • make basic visualizations: barplots and mosaicplots
• How to make histograms of numerical data
• How to get subsets of data, e.g. only men vs only women.

Question: Who will people who attend my goodbye party know?

Data: 41 x 41 matrix of TRUE/FALSEs indicating for all pairs of people if I think they know each other.

Tool: We will use the network package to create a visual social network graph, contributed by a team of sociologists and statisticians.

• Couples are Brangelina'ed into single units
• Bubble sizes are proportional to log(# of the people the person knows)
• I'm included at the center for two reasons: 1) raging narcissism & 2) graph aesthetics

• How to install and load an R package
• How to export a plot to .png format

• lists: vectors of different types of objects at the same time (strings, numerical).
• computer programming: if/else statements, for loops, etc.

• Rich Majerus from Data at Reed has posted tutorials to execute some basic tasks.
• Swirl Stats: http://swirlstats.com/. Package to learn R, in R.
• But most importantly, it’s best to learn by doing. Figure out a project of reasonable scope and hack it out.