• Introduction
  • Syllabus
  • Assignments
    • Homework
    • Labs
    • Data Project
    • Final exam
    • Meetup Presentation
  • The DATA606 R Package
  • Using R Markdown

A little about me:

• Currently Executive Director at Excelsior College
  • Principal Investigator for a Department of Education Grant (part of their FIPSE First in the World program) to develop a Diagnostic Assessment and Achievement of College Skills (www.DAACS.net)
• Authored over a dozen R packages including:
  • likert
  • sqlutils
  • timeline
• Specialize in propensity score methods. Three new methods/R packages developed include:
  • multilevelPSA
  • TriMatch
  • PSAboot

Syllabus and course materials are here: http://data606.net

The site is built using the Blogdown R package and hosted on Github.

We will use Blackboard primary only for submitting assignments. Please submit:

• A PDF or link to the built HTML (e.g. Rpubs, Github)
• For labs, also include your Rmarkdown file

See http://data606.net/schedule/ for up-to-date calendar.

• Getting Acquainted (1%)
• Homework (16%)
  • Approximately six problems per chapter.
  • Answers can be handwritten or typed (I suggest using R Markdown)
  • Submit a PDF on Blackboard.
• Labs (40%)
  • Labs are designed to introduce to you doing statistics with R.
  • Answer the questions in the main text as well as the “On Your Own” section.
  • Submit both the R Markdown file and PDF of the output on Blackboard.
• Data Project (20%)
  • This allows you to analyze a dataset of your choosing. Projects will be shared with the class. This provides an opportunity for everyone to see different approaches to analyzing different datasets.
  • Proposal is due March 7th (5%); Final project is due May 16th (15%).
• Final exam (18%)
• Meetup Presentation (5%)
  • Present one practice problem during our weekly meetups. Signup using the Google Spreadsheet.

• Slack Channel: https://data606spring2019.slack.com
  • Click here to join the group
• Github Issues - Use this for issues or problems with the course or DATA606 package: https://github.com/jbryer/DATA606Fall2018/issues
• Email: jason.bryer@gmail.com
• Phone/GoToMeeting: Please email to schedule a time to meet.

The package can be installed from Github using the devtools package.

devtools::install_github('jbryer/DATA606')

Download the Setup.R script here: https://github.com/jbryer/DATA606Spring2019/blob/master/R/Setup.R

Important Functions

• library('DATA606') - Load the package
• vignette(package='DATA606') - Lists vignettes in the DATA606 package
• vignette('os3') - Loads a PDF of the OpenIntro Statistics book
• data(package='DATA606') - Lists data available in the package
• getLabs() - Returns a list of the available labs
• viewLab('Lab0') - Opens Lab0 in the default web browser
• startLab('Lab0') - Starts Lab0 (copies to getwd()), opens the Rmd file
• shiny_demo() - Lists available Shiny apps

R Markdown files are provided for all the labs. You can start a lab using the DATA606::startLab function.

However, creating new R Markdown files in RStudio can be done by clicking File > New File > R Markdown.