Shiny application to learn confidence interval (t-dist)

app.R

##
p_stat_t <- function(v, df = 1, 
                     alternative = "two.sided"){
    if (!alternative %in% c("two.sided", "less", "greater")) {
        stop("alternative must be either \"two.sided\", \"less\", or \"greater\".")
    }
    if(alternative == "two.sided"){
        p0 <- 2*pt(abs(v), df, lower.tail = FALSE)
    }else if(alternative == "less"){
        p0 <- pt(v, df)
    }else if(alternative == "greater"){
        p0 <- pt(v, df, lower.tail = FALSE)
    }
    return(p0)
}

q_stat_t <- function(p, df = 1, 
                     alternative = "two.sided"){
    if (!alternative %in% c("two.sided", "less", "greater")) {
        stop("alternative must be either \"two.sided\", \"less\", or \"greater\".")
    }
    if(alternative == "two.sided"){
        q0 <- qt(p/2, df)#*sign(v)
    }else if(alternative == "less"){
        q0 <- qt(p, df)
    }else if(alternative == "greater"){
        q0 <- qt(p, df, lower.tail = FALSE)
    }
    return(q0)
}
##

require(shiny)

ui <- fluidPage(
    
    # Application title
    titlePanel("Learn to confidence interval"),
    
    sidebarLayout(
        sidebarPanel(
            sliderInput("alpha",
                        "alpha (false positive rate):",
                        min = 0.01,
                        max = 0.5,
                        value = 0.1)
        ),
        sidebarPanel(
            sliderInput("mu0",
                        "mean of the model of the null hpothesis:",
                        min = -4,
                        max = 4,
                        value = 0,
                        step=0.1)
        )),
    mainPanel(plotOutput("distPlot"))
)

server <- function(input, output) {
    
    output$distPlot <- renderPlot({
        mu0 <- input$mu0
        stat <- 1
        invse <- 1
        curve(p_stat_t((x-mu0)*invse, df=9), -4, 4,
              ylim=c(-0.05, 1.1),
              xlab="mean", ylab="alpha", n=501)
        arrows(stat-1/invse,0,stat+1/invse,0,
              angle=90, code=3, length=0.1, col="grey")
        alpha <- input$alpha
        q <- q_stat_t(alpha, df=9)
        sig <- p_stat_t((stat-mu0)*invse, df=9)<=alpha
        points(x=stat, y=0,
               pch=ifelse(sig,4,1),
               col=ifelse(sig,"firebrick","steelblue"),lwd=2)
        abline(h=alpha, lty=2)
        abline(v=stat+q, lty=2)
        abline(v=stat-q, lty=2)
        legend("topright",
               legend = c("positive","negative"),
               col=c("firebrick","steelblue"),
               pch=c(4, 1), lwd=2, lty=0,
               box.lwd = 0)
    })
}

# Run the application 
shinyApp(ui = ui, server = server)