Instantly share code, notes, and snippets.

# jrnold/server.R

Last active December 26, 2015 08:49
Show Gist options
• Save jrnold/7124461 to your computer and use it in GitHub Desktop.
Confidence interval simulation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. Learn more about bidirectional Unicode characters
 library("shiny") library("ggplot2") library("plyr") norm_mean <- 0 norm_sd <- 1 ##' Take sample from normal dist and calculate confidence interval for normal smpl_mean_sample_ci <- function(n, p=0.95, pop_mean=0, pop_sd=1) { smpl <- rnorm(n, norm_mean, norm_sd) smpl_sd <- sd(smpl) smpl_mean <- mean(smpl) tailprob <- (1 - p) / 2 q <- -qt(tailprob, df=(n - 1), lower.tail=TRUE) se <- smpl_sd / sqrt(n) ci <- data.frame(ci_lb = smpl_mean - q * se, ci_ub = smpl_mean + q * se) ci } shinyServer(function(input, output) { sample_ci <- reactive({ input\$draw mutate(rdply(input\$nsamples, smpl_mean_sample_ci(input\$smplsize, input\$confidence / 100)), n = seq_len(input\$nsamples), contains_mean = ((0 > ci_lb) & (0 < ci_ub))) }) output\$plot <- renderPlot({ print(ggplot(sample_ci(), aes(x = n, ymin = ci_lb, ymax = ci_ub, colour = contains_mean)) + geom_hline(xintercept = 0, colour="blue") + geom_linerange() + coord_flip() + scale_x_continuous("samples") + scale_y_continuous(sprintf("%d%% CI", input\$confidence)) + scale_colour_manual(values = c("red", "black")) + theme(legend.position = "none", axis.text.y = element_blank(), axis.ticks.y = element_blank())) }) output\$npct <- renderText({ c("Percent of CI containing the population mean:", round(mean(sample_ci()\$contains_mean) * 100, 2), "%") }) })
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. Learn more about bidirectional Unicode characters
 library("shiny") shinyUI(pageWithSidebar( headerPanel("Confidence Intervals"), sidebarPanel( actionButton("draw", "Draw samples"), numericInput("confidence", "Confidence (%):", 95, min = 1, max = 99, step=1), numericInput("smplsize", "Sample sizes:", 100, min = 2, max = 1000, step=1), numericInput("nsamples", "Number of samples:", 100, min = 1, max = 500, step=1) ), mainPanel( textOutput("npct"), plotOutput("plot"), p("The population has a mean of 0 and a standard deviation of 1.", "Intervals including the population mean are colored red, those not including the population mean are colored black") )))