server.R

# server.R

library("shiny")
library("ggplot2")    # Grammar of Graphics for plots
library("eeptools")   # Convenience functions for education data

# static function
rnormcor <- function(x,rho) {rnorm(1,rho*x,sqrt(1-rho^2))}

shinyServer(
  function(input,output){ 
    
    output$distPlot <- renderPlot({
    a <- rnorm(input$obs)
    b <- sapply(a, rnormcor, rho = input$rho)
    p <- qplot(a, b, alpha = 0.5)
    p <- p + scale_alpha(guide = "none")
    p <- p + geom_smooth(method = "lm", se = TRUE, level = .99
      , fill = "blue", colour = "darkblue", alpha = 0.2, size = 1)
    p <- p + theme_dpi()
    p <- p + labs(x = "", y = "", title = paste0("Correlation = ", input$rho, ", Confidence Level = .99"))
    # p <- p + geom_text(aes(x = -1, y = 3, label = paste0("Corr. = ", input$rho)), size = 8)
    print(p)
    })
    
})

ui.R

# https://gist.github.com/jknowles/4484910

# ui.R

library("shiny")
library("ggplot2")    # Grammar of Graphics for plots
library("eeptools")   # Convenience functions for education data

shinyUI(
  pageWithSidebar(
    headerPanel(h3("Exploring Properties of Distributions"))
    ,
    sidebarPanel(
      sliderInput("obs"
        , "Number of observations:"
        , min = 200
        , max = 5000
        , value = 500
        , step = 250
      )
      , br(), br(),
      sliderInput("rho"
        , "Correlation Coefficient"
        , min = -1
        , max = 1
        , value = 0
        , step = 0.1
      )
    )
    ,
    mainPanel(plotOutput("distPlot"))
  )
)

very nice app by jknowles, thanks for sharing! marginal edits above