Help Requested! Shiny Interface: Conditional Output/Variable Carry-Over

shiny
, ,
1

Hello! I am working on making a game for students to practice estimating the standard deviation of a set of data using a histogram and a given sample size.

How could I incorporate the sd(x) stored in y (line 50; two asterisks surrounding) into lines 55-58 (three asterisks surrounding) for the logical ifelse statement (since they are within different output command sequences)?

Secondly, how could I get the code to regenerate new values for lines 44-49 (one set of asterisks surrounding) each time a student selects a new sample size.

library(shiny)

ui <- fluidPage(

    titlePanel("Standard Deviation Estimation Practice"),

    # Sidebar with a slider input for sample size
    sidebarLayout(
        sidebarPanel( 
            sliderInput("samplesize", h3("Enter a positive whole number as a sample size"), min = 10, max = 500, value = 250),
            submitButton("Submit"),
            numericInput("guess", "What is your estimation of the standard deviation of the data in the histogram?", ""),
            submitButton("Submit")
        ),

        # Show a plot of the generated distribution and pose question
        mainPanel(
           plotOutput("distPlot"),
           textOutput("result")
        )
    )
)


server <- function(input, output)({
    
    output$distPlot <- renderPlot({
        
        
        
        *
        seed1 <- sample.int(1000000, 1)
        set.seed(seed1)
        sd1 <- sample.int(25, 1)
        mean1 <- sample((-300):400, 1)
        x <- rnorm(n = input$samplesize, mean = mean1, sd = sd1)
        **y <- sd(x)**         *
        
        # draw the histogram with the specified number of bins
        hist(x, main = "Histogram", xlab = "Sample Values", ylab = "Frequency Count", col = 'darkgray', border = 'white')
        
    })
    
    output$result <- renderText({
        ***ifelse(q >= (y - 0.5), ifelse(q <= (y + 0.5), 
                     "That is a correct estimation! Good job! Enter a new sample size.", 
                     "That estimate is too big. Try again!"),
                     "That estimate is too small. Try again!")***
    })
})

shinyApp(ui = ui, server = server)

Thank you for your help!

2 
library(shiny)

ui <- fluidPage(
  titlePanel("Standard Deviation Estimation Practice"),

  # Sidebar with a slider input for sample size
  sidebarLayout(
    sidebarPanel(
      sliderInput("samplesize", h3("Enter a positive whole number as a sample size"), min = 10, max = 500, value = 250),
      actionButton(
        inputId = "submit_hist",
        label = "Press for new Histogram"
      ),
      numericInput("guess", "What is your estimation of the standard deviation of the data in the histogram?", ""),
    ),
    # Show a plot of the generated distribution and pose question
    mainPanel(
      plotOutput("distPlot"),
      textOutput("result")
    )
  )
)


server <- function(input, output) {
  x_val <- eventReactive(input$submit_hist, {
    seed1 <- sample.int(1000000, 1)
    set.seed(seed1)
    sd1 <- sample.int(25, 1)
    mean1 <- sample((-300):400, 1)
    rnorm(n = req(input$samplesize), mean = mean1, sd = sd1)
  })

  y_val <- reactive({
    sd(req(x_val()))
  })

  output$distPlot <- renderPlot({
    # draw the histogram with the specified number of bins
    hist(req(x_val()),
      main = "Histogram",
      xlab = "Sample Values",
      ylab = "Frequency Count",
      col = "darkgray",
      border = "white"
    )
  })

  output$result <- renderText({
    q <- req(input$guess)
    if (!isTruthy(q)) {
      return(NULL)
    }
    # print(y_val())
    ifelse(q >= (y_val() - 0.5), ifelse(q <= (y_val() + 0.5),
      "That is a correct estimation! Good job! Enter a new sample size.",
      "That estimate is too big. Try again!"
    ),
    "That estimate is too small. Try again!"
    )
  })
}

shinyApp(ui = ui, server = server)
3

Thank you very much for the help, Nir! There's no way I would have found that solution on my own.

One additional question, if you are able: how does the data from the "rnorm" function end up being stored in "x_val" when there are the four other lines (i.e. set.seed, sd1, and mean1)?

Thank you again. Stay safe and healthy!