ShinyProject.md

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Adding Data to a Model: A Shiny App

author: Paul Clark date: 06-04-2017 autosize: true css: ie11fix.css

See app at https://clarpaul.shinyapps.io/add_point/

For all code, see repo https://github.com/clarpaul/DevDataProducts_Project/
App code in subfolder "Add_Point"

The app is to learn about linear regression

Primary Goals

• Visualize regression statistics
  • Correlation coefficients
  • P-values
• Understand how adding data affects p-values
• See how differently positioned points impact the regression
  • Which points most affect the best-fit line
  • I.e., which points are high vs. low leverage/influence
• Have fun!

Operation of the app

1. The app displays a 2D scatterplot and regression line
2. The user clicks plot locations to add observations in red
3. With each added observation, the app updates and displays...
   • the observation's coordinates
   • the regression line for the scatterplot
   • the equation for the line
   • the correlation coef and p-value of the slope/regression
4. Input widgets include...
   • check-box to show or hide the original trend line
   • button to clear added points and start over

View 1: Regression plot before adding data

class: small-code

plot(mtcars$mpg, mtcars$hp, 
   main = paste0("Horsepower",
     " vs. Miles-per-gallon"), 
   xlab = "MPG", ylab = "HP", 
   bty = "n", pch = 16,
   xlim = c(10, 35), 
   ylim = c(50, 350))
mtext("R `mtcars` dataset")
model1 <- lm(hp ~ mpg,
   data = mtcars)
abline(model1, col = "red",
   lwd = 2)

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View 2: Full application after adding data