# BlogAnalytics 2014-11-10 12:03:00

November 10, 2014
By

(This article was first published on BlogAnalytics, and kindly contributed to R-bloggers)

## View Confidence Interval Dynamically

This is a simple effort for dynamic view of confidence interval in a normal distribution. The  link provides a interactive interface which helps users to understand normal distribution and confidence interval.

Its a simple application that takes the mean, standard deviation, upper bound and lower bound, and marks the confidence interval in the normal distribution.

Application is created by Shiny App. Shiny App is a very simple R tool to create interactive apps on browser. Which can be hosted online.

Shiny app tutorials are available here.
Below is the code for the above app.

`ui.RshinyUI(fluidPage(  titlePanel("Confidence Interval",windowTitle = "Normal Distribution Confidence Interval"),  sidebarLayout(    sidebarPanel(      p("Provide the mean, Standard Deviation,         Upper Bound and Lower Bound to plot confidence Interval on Normal Plot"),      numericInput("mean", label = h4("Mean"), value = 0),      numericInput("sd", label = h4("Standard Deviation(not Variance)"), value = 1),      numericInput("lb", label = h4("Lower Bound"), value = -1),      numericInput("ub", label = h4("Upper Bound"), value = 1)       ),    mainPanel(plotOutput("map"))        )    )  ) server.Rnormal = function(mean, sd, lb,ub){  x <- seq(-4,4,length=100)*sd + mean  hx <- dnorm(x,mean,sd)   plot(x, hx, type="n", ylab="",       main="Normal Distribution", axes=FALSE)   i <- x >= lb & x <= ub  lines(x, hx)  polygon(c(lb,x[i],ub), c(0,hx[i],0), col="red")   area <- pnorm(ub, mean, sd) - pnorm(lb, mean, sd)  result <- paste("P(",lb,"< IQ <",ub,") =",                  signif(area, digits=3))  mtext(result,3)  axis(1, at=seq(mean-4*sd, mean+4*sd, sd), pos=0) } shinyServer(function(input, output){   output\$map = renderPlot({normal(input\$mean,input\$sd,input\$lb,input\$ub)    })       }   )`

To host an app online follow the below steps:
2 – It will ask to create a “shinyapps.io” account (eg . “myshinyapps.io”). once you create your shinyapp.io account, it will give a token.
3- Install packages “shiny” and “shinyApps”. (to install “shinyApp” follow the instruction here.
4- Create your shiny app and test locally.
5- Once done, go to your shinyapp.io account, and deploy your app using below R command

deployApp(“”, appName = “name of your app”,

account = “shinyapps.io account name”, upload = TRUE)

find my app at
https://sahuvaibhav.shinyapps.io/Stats/

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