Draw a normal distribution with a given number of observations. Demonstrate what sample sizes and approximations can mean.

server.R

library(shiny)

shinyServer(function(input,output){
  
  output$distPlot<-reactivePlot(function(){
    dist<-rnorm(input$obs)
    p<-qplot(dist,binwidth=0.1)+geom_vline(xintercept=mean(dist))+theme_dpi()
    p<-p+coord_cartesian(xlim=c(-4,4))+geom_vline(xintercept=median(dist),color=I("red"))
    print(p)
  })
  
    
})

ui.R

library(shiny)
library(ggplot2)
library(eeptools)
shinyUI(pageWithSidebar(
  
  # Title
  headerPanel("Normality"),
  
  sidebarPanel(
    sliderInput("obs","Number of observations:",
                min=0,max=1000,value=100)
    ),
  
  # GGPLOT
  
  mainPanel(
    plotOutput("distPlot")
    )
  
  
  
  ))