Workshop schedule

jp, 02 November 2017

About twenty people came out to a brief introductory talk I gave about the workshop series, with roughly an even split of first and second years. Many people seemed excited!

Here’s the workshop schedule I pitched:

  • Spreadsheets
    • cell references, formulas, H/VLOOKUP
    • Google sheets vs Excel
  • Cleaning up data
    • Using OpenRefine
  • Introduction to programming with R
    • What is an IDE, Installing/loading libraries
    • Getting help
    • Running code, variables, and data.frames
  • Data visualization with R
    • tidyverse
    • Loading data from spreadsheets/CSVs
    • ggplot
  • Data analysis with R
    • tidy data
    • computed columns
    • merge, aggregate, filter data frames
  • Basic statistics with R
    • model fitting, hypothesis testing
  • (optional) Data safety online and offline:
    • 2FA, pw managers, adblock, crypto

There was also interest in having open sessions/”office hours” where there was no directed learning, but learners could gather and work on lessons, or their own projects. I like this idea, and I could use this time to teach the more proficient or focused learners about other topics such as databases, version control, python, etc, or work directly on their research topics.

Early results from a short online survey about the workshops tell me that (0f 13 responses so far):

  • There is a general interest in learning to program and do statistics, but the majority of students have no specific interests or ongoing research projects they are tackling right now that are motivating their interest in these workshops.
  • 40% have little to no experience with computing outside of Excel, and the others have had minimal contact with R/Python during undergrad but don't consider themselves proficient (except for two that do).
  • 70% are interested in a data safety workshop.