author: Yamina Touhami

date: 25/10/2014

A Poisson distribution is the probability distribution that results from a Poisson experiment, which is a statistical experiment that has the following properties:

• The experiment results in outcomes that can be classified as successes or failures.
• The average number of successes (μ) that occurs in a specified region is known.
• The probability that a success will occur is proportional to the size of the region.
• The probability that a success will occur in an extremely small region is virtually zero.
• The specified region could take many forms. For instance, it could be a length, an area, a volume, a period of time, etc.

library(shiny)
library(ggplot2)
library(eeptools)
shinyUI(pageWithSidebar(

  # Title
  headerPanel("Visualizing the Poisson Distribution"),

  sidebarPanel(
    sliderInput("obs","Number of observations:",
                min=0,max=1000,value=100),
    sliderInput("lambda","vector of non-negative means:",
                min=1,max=20,value=5)

    ),

  # GGPLOT

  mainPanel(
    plotOutput("distPlot")
  )

))

<!–html_preserve–>

<!–/html_preserve–>

library(shiny)

shinyServer(function(input,output){

  output$distPlot<-reactivePlot(function(){

    dist<-rpois(input$obs, input$lambda)

    p<-qplot(dist,binwidth=0.02)+geom_vline
    (xintercept=mean(dist))+theme_dpi()

    p<-p+coord_cartesian(xlim=c(-5,30))
    +geom_vline(xintercept=median(dist),
                color=I("red"))

    print(p)
  })


})

Specifiy the following using slider bars & dropdown box:

• The number of observations
• The value of the non-negative mean of the Poisson distribution

This applet was made as a project for Coursera's class on Developing Data Products.

It was written in R and hosted by shiny apps at https://tensoriel.shinyapps.io/Newapp