Shiny App for Checking n, p assumptions

app.R

library(shiny)
inputPanel(
  numericInput("n", label = "Sample size:", value = 300),
  
  sliderInput("p", label = "Population proportion:",
              min = 0, max = 1, value = 0.1, step = 0.01),
  
  numericInput("x_min", label = "Min for x-axis:", value = 0, min = 0, max = 1),
  numericInput("x_max", label = "Max for x-axis:", value = 1, min = 0, max = 1)
)

library(ggplot2)
library(shiny)

server <- function(input, output) {
  output$histPlot <- renderPlot({
    pp <- data.frame(p_hat = rep(0, 5000))
    for(i in 1:5000){
      samp <- sample(c(TRUE, FALSE), input$n, replace = TRUE, 
        prob = c(input$p, 1 - input$p))
      pp$p_hat[i] <- sum(samp == TRUE) / input$n
    }
    bw <- diff(range(pp$p_hat)) / 30
    ggplot(data = pp, aes(x = p_hat)) +
      geom_histogram(binwidth = bw) +
      xlim(input$x_min, input$x_max) +
      ggtitle(paste0("Distribution of p_hats, drawn from p = ", input$p, ", n = ", input$n))
  })
}

ui <- fluidPage(
  inputPanel(
    numericInput("n", label = "Sample size:", value = 300),
    
    sliderInput("p", label = "Population proportion:",
      min = 0, max = 1, value = 0.1, step = 0.01),
    
    numericInput("x_min", label = "Min for x-axis:", value = 0, min = 0, max = 1),
    numericInput("x_max", label = "Max for x-axis:", value = 1, min = 0, max = 1)
  ),
  mainPanel(
    plotOutput("histPlot")
  )
)

shinyApp(ui = ui, server = server)