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

A little about me:

• 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) at Excelsior College
• Research Data Associate at Cornell University
• 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. Each page of the site has a “Improve this page” link at the bottom right, use that to start a pull request 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)

PDFs are preferred for the homework as there is some LaTeX formatting in the R markdown files. The tineytex R package helps with install LaTeX, but you can also install LaTeX using (MiKTeX (for Windows) and BasicTeX (for Mac) See this page for more information: https://spring2020.data606.net/course-overview/software/

• Getting Acquainted (1%)
• Homework (18%)
• 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.
• Data Project (18)
  • 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 29th (5%); Final project is due May 10th (15%).
• Final exam (18%)
• Meetup Presentation (5%)
  • Present one practice problem during our weekly meetups. Signup using the Google Spreadsheet.
  • Please select odd number questions only!

• Slack Channel: https://data606spring2020.slack.com
  • Click here to join the group
• There is a general CUNY MSDS Slack channel click here to join it.
• Github Issues - Use this for issues or problems with the course or DATA606 package: https://github.com/jbryer/DATA606Spring2020/issues
• Email: jason.bryer@sps.cuny.edu
• Phone/GoToMeeting: Please email to schedule a time to meet.
• Office hours will typically be:
  • Mondays from 8:30pm to 9:30pm
  • Fridays from 11:00am to 12:00pm
  • Please use the Calendly link on the course homepage.
  • I will use the dame GoToMeeting link that we use for the Wednesday night meetups.

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/DATA606Spring2020/blob/master/R/Setup.R

Important Functions

• library('DATA606') - Load the package
• vignette(package='DATA606') - Lists vignettes in the DATA606 package
• vignette('os4') - 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('Lab1') - Opens Lab1 in the default web browser
• startLab('Lab1') - Starts Lab1 (copies to getwd()), opens the Rmd file
• shiny_demo() - Lists available Shiny apps

R Markdown files are provided for all the labs and homework.

• You can download R markdown template files for the homework by right clicking and selecting “Save file as…” from the Homework page.
• 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.

For more information about R Markdown, check out the RStudio page at https://rmarkdown.rstudio.com/