Data Products Pursuasive Presentation

Mark Bulkeley
2016-06-06

Interactive Linear Regression

Showing students how regression changes is important:

  • It's interactive - instant feedback
  • Reenforces ideas and concepts taught in classroom setting
  • Relevant interface: on the web where students are at home

What dataset is used?

  • The mtcars dataset is used given students' familiarity with it.
'data.frame':   32 obs. of  11 variables:
 $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
 $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
 $ disp: num  160 160 108 258 360 ...
 $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
 $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
 $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
 $ qsec: num  16.5 17 18.6 19.4 17 ...
 $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
 $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
 $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
 $ carb: num  4 4 1 1 2 1 4 2 2 4 ...

Plot Functionality is Impressive

  • The shiny app allows for simple plotting that depends on the inputs from the check boxes
  • Familiarity that you have with ggplot2 readily transfers to the web application!
  • The below shows the sample graph from the shiny application.

plot of chunk unnamed-chunk-2

Code can be Shared Across Applications

  • With proper planning and structuring, you can share important code between applications.
    • Assume you had a special model that you'd apply to data in a similar way.
    • Write that once and then reference from both of your shiny applications
  • Efficient and quick
    • Turn ad hoc analysis into web applications quickly and easily
    • Allow management to tweak variables themselves so you don't sit in meetings endlessly changing input variables
    • Capture key outputs simply for static reports

Summary

  • Use interactive Shiny applications to teach the linear regression interactively!
  • See an example application here: Interactive Linear Regression
  • The R code to build it can be found on GitHub (see the app.R file).