Lectures

Possible lecture titles

• Intro lecture
• R for newbies
• Excel Hell
• Getting data into R
• Reproducible science
• Tidying data in R
• Stats
• Data viz

May 19 for 4 weeks

Lecture preparation schedule

• May 19

  • Intro lecture
    • introduce how the workshop will work
      • etherpad as a collaborative tool
      • live coding
      • pair programming
      • sticky notes
      • join collaborative google sheet for feedback
  • R for newbies - (v1) Steve (v2)

• May 26

  • Excel Hell - (v1) Ed (v2)
    • live coding / practical session tidying a dirty sheet
  • Getting data into R - (v1) Ahmed (v2) Ed
    • live coding importing the data
    • let's add googlesheets to this but not the reproducible angle yet
    • simple summary functoions in R for looking at your data
      • ls()
      • summary()
      • mean()
      • nrows()
      • ncols()
      • names()

• June 2

  • Reproducible science - (v1) Danny (v2) Finn
    • back story - requirements for publications
    • teach the google sheets pipeline
    • using git in R studio??
  • Tidying data in R - (v1) Ahmed (v2) Steve
    • dplyr
    • tidyr

• June 9

  • Data viz - (v1) Finn (v2) Danny ?do dataviz before stats because we want to emphasise the importance of looking at your data; therefore just focus on histograms/bar and scatter plots
    • inspect before testing concept so dataviz of distribution before ttest etc
    • ggplot2
  • Stats - (v1) Sundiya (v2)
    • choose your test diagram
    • simple tests
  • Revisit ggplot with all the nicer options for facetting, colour size
    • maybe get them to plot hrate and mortality with