Visualising Rnorm

• Commonly found in nature
• Central Limit Theorem: all sampling distributions of unbiased estimators converge to a normal distribution
• Centred around a mean value
• Spread is determined by the standard deviation

• Visualising the basic properties of normal distributions
  • How the distribution depends on the mean
  • How the distribution depends on the standard deviation
• The general shape of the distribution doesn't change
  • but the axes shift

The UI

sliderInput("n", "Number of Points",
                min=100, max=1000, step=50, value=500),
sliderInput("mu", "Mean", -10, 10, value=0),
sliderInput("sd", "Standard Deviation", 0, 10, value=1)

The Server (Simplified Code)

x <- function(){
        x <- rnorm(input$n, input$mu, input$sd)
    }
data <- x()
mean(data)
sd(data)
hist(data)