Basic Statistics Calculator

Data input:

Input values can be separated by
newlines, spaces, commas, or tabs.

Basic statistics


                    

Histogram

Box plot

Test of normality


                    

Q-Q plot



R session info

                  
Note

This web application is developed with Shiny.


List of Packages Used
library(shiny)
library(psych)
library(beeswarm)
library(DescTools)

Code

Source code for this application is based on "The handbook of Research in Foreign Language Learning and Teaching" (Takeuchi & Mizumoto, 2012).

The code for this web application is available at GitHub.

If you want to run this code on your computer (in a local R session), run the code below:
library(shiny)
runGitHub("bs","mizumot")


Citation in Publications

Mizumoto, A. (2015). Langtest (Version 1.0) [Web application]. Retrieved from http://langtest.jp


Article

Mizumoto, A., & Plonsky, L. (2015). R as a lingua franca: Advantages of using R for quantitative research in applied linguistics. Applied Linguistics, Advance online publication. doi:10.1093/applin/amv025


Recommended

To learn more about R, I suggest this excellent and free e-book (pdf), A Guide to Doing Statistics in Second Language Research Using R, written by Dr. Jenifer Larson-Hall.

Also, if you are a cool Mac user and want to use R with GUI, MacR is defenitely the way to go!


Author

Atsushi MIZUMOTO, Ph.D.
Associate Professor of Applied Linguistics
Faculty of Foreign Language Studies /
Graduate School of Foreign Language Education and Research,
Kansai University, Osaka, Japan


Code for "Basic Statistics Calculator"
by Atsushi Mizumoto

show with app
library(shiny)
library(psych)
library(beeswarm)
library(DescTools)


shinyServer(function(input, output) {
    
    options(warn=-1)
    
    bs <- reactive({
        x <- input$textarea.in
        x <- as.numeric(unlist(strsplit(x, "[\n, \t]")))
        result <- describe(x)[2:13]
        row.names(result) <- ""
        
        ndigits <- input$numdigits # decimal points
        
        ci <- round(MeanCI(x, conf.level=0.95), ndigits)
        
        print(result, digits=ndigits)  # rounding to the specified number of digits
        
        cat("\n", "[95% confidence intervals of the mean]", "\n")
        
        return(ci)
    })



    makedistPlot <- function(){
        x <- input$textarea.in
        x <- as.numeric(unlist(strsplit(x, "[\n, \t]")))
        
        x <- x[!is.na(x)]
        
        simple.bincount <- function(x, breaks) {
            nx <- length(x)
            nbreaks <- length(breaks)
            counts <- integer(nbreaks - 1)
            for (i in 1:nx) {
                lo <- 1
                hi <- nbreaks
                if (breaks[lo] <= x[i] && x[i] <= breaks[hi]) {
                    while (hi - lo >= 2) {
                        new <- (hi + lo) %/% 2
                        if(x[i] > breaks[new])
                        lo <- new
                        else
                        hi <- new
                    }
                    counts[lo] <- counts[lo] + 1
                }
            }
            return(counts)
        }
        
        nclass <- nclass.FD(x)
        breaks <- pretty(x, nclass)
        counts <- simple.bincount(x, breaks)
        counts.max <- max(counts)
        
        h <- hist(x, las=1, breaks="FD", xlab= "Red vertical line shows the mean.",
        ylim=c(0, counts.max*1.2), main="", col = "cyan")
        rug(x)
        abline(v = mean(x, na.rm=T), col = "red", lwd = 2)
        xfit <- seq(min(x, na.rm=T), max(x, na.rm=T))
        yfit <- dnorm(xfit, mean = mean(x, na.rm=T), sd = sd(x, na.rm=T))
        yfit <- yfit * diff(h$mids[1:2]) * length(x)
        lines(xfit, yfit, col = "blue", lwd = 2)
    }


    output$distPlot <- renderPlot({
        print(makedistPlot())
    })
    
    
    
    makeboxPlot <- function(){
        x <- input$textarea.in
        x <- as.numeric(unlist(strsplit(x, "[\n, \t]")))
        
        boxplot(x, horizontal=TRUE, xlab= "Mean and +/-1 SD are displayed in red.")
        
        points(mean(x, na.rm=T), 0.9, pch = 18, col = "red", cex = 2)
        arrows(mean(x, na.rm=T), 0.9, mean(x, na.rm=T) + sd(x, na.rm=T), length = 0.1, angle = 45, col = "red")
        arrows(mean(x, na.rm=T), 0.9, mean(x, na.rm=T) - sd(x, na.rm=T), length = 0.1, angle = 45, col = "red")

        if (input$beeswarm == F) {
            
            NULL
            
        } else {
            
            beeswarm(x, horizontal=TRUE, col = 4, pch = 16, add = TRUE)
        
        }
    }
    
    
    output$boxPlot <- renderPlot({
        print(makeboxPlot())
    })
    
    
    
    testnorm <- reactive({
        x <- input$textarea.in
        x <- as.numeric(unlist(strsplit(x, "[\n, \t]")))
        list(ks.test(scale(x), "pnorm"), shapiro.test(x))
    })
    
    
    
    makeqqPlot <- function(){
        x <- input$textarea.in
        x <- as.numeric(unlist(strsplit(x, "[\n, \t]")))
        qqnorm(x, las=1)
        qqline(x, col=2)
    }
    
    output$qqPlot <- renderPlot({
        print(makeqqPlot())
     })
    
    
    
    info <- reactive({
        info1 <- paste("This analysis was conducted with ", strsplit(R.version$version.string, " \\(")[[1]][1], ".", sep = "")
        info2 <- paste("It was executed on ", date(), ".", sep = "")
        cat(sprintf(info1), "\n")
        cat(sprintf(info2), "\n")
    })
    
    output$info.out <- renderPrint({
        info()
    })

    
    
    output$textarea.out <- renderPrint({
        bs()
    })
    
    output$testnorm.out <- renderPrint({
        testnorm()
    })
    
})
library(shiny)


shinyUI(pageWithSidebar(


    headerPanel("Basic Statistics Calculator"),


    sidebarPanel(

    p("Data input:"),
    tags$textarea(id="textarea.in", rows=30, cols=10, "44\n32\n37\n44\n40\n44\n45\n36\n37\n42\n38\n47\n26\n41\n27\n39\n47\n41\n36\n44\n39\n49\n40\n25\n33\n39\n36\n45\n32\n51\n47\n39\n43\n38\n42\n35\n29\n33\n40\n37\n38\n34\n36\n43\n38\n39\n26\n30\n41\n35\n30\n39\n46\n39\n43\n46\n33\n48\n44\n45\n42\n45\n46\n53\n47\n47\n51\n33\n40\n43\n48\n37\n31\n40\n40\n49\n43\n49\n46\n38\n40\n51\n40\n44\n45\n53\n46\n42\n44\n46\n29\n38"),
    p('Input values can be separated by', br(),
      'newlines, spaces, commas, or tabs.')
    ),


mainPanel(
    tabsetPanel(

    tabPanel("Main",

        h3("Basic statistics"),

        numericInput("numdigits", "Number of decimal points:", 3),

        verbatimTextOutput("textarea.out"),

        br(),

        h3("Histogram"),

        plotOutput("distPlot"),

        h3("Box plot"),

        checkboxInput("beeswarm", label = strong("Plot individual data points."), value = T),

        plotOutput("boxPlot"),

        h3("Test of normality"),
        verbatimTextOutput("testnorm.out"),

        br(),

        h3("Q-Q plot"),

        plotOutput("qqPlot", width="70%"),

        br(),
        br(),

        strong('R session info'),
        verbatimTextOutput("info.out")

        ),

    tabPanel("About",

        strong('Note'),
            p('This web application is developed with',
            a("Shiny.", href="http://shiny.rstudio.com/", target="_blank"),
            ''),

        br(),

        strong('List of Packages Used'), br(),
        code('library(shiny)'),br(),
        code('library(psych)'),br(),
        code('library(beeswarm)'),br(),
        code('library(DescTools)'),br(),


        br(),

        strong('Code'),
            p('Source code for this application is based on',
            a('"The handbook of Research in Foreign Language Learning and Teaching" (Takeuchi & Mizumoto, 2012).', href='http://mizumot.com/handbook/', target="_blank")),

            p('The code for this web application is available at',
            a('GitHub.', href='https://github.com/mizumot/bs', target="_blank")),

            p('If you want to run this code on your computer (in a local R session), run the code below:',
            br(),
            code('library(shiny)'),br(),
            code('runGitHub("bs","mizumot")')
            ),

            br(),

        strong('Citation in Publications'),
            p('Mizumoto, A. (2015). Langtest (Version 1.0) [Web application]. Retrieved from http://langtest.jp'),

            br(),

        strong('Article'),
            p('Mizumoto, A., & Plonsky, L. (2015).', a("R as a lingua franca: Advantages of using R for quantitative research in applied linguistics.", href='http://applij.oxfordjournals.org/content/early/2015/06/24/applin.amv025.abstract', target="_blank"), em('Applied Linguistics,'), 'Advance online publication. doi:10.1093/applin/amv025'),

            br(),

        strong('Recommended'),
            p('To learn more about R, I suggest this excellent and free e-book (pdf),',
            a("A Guide to Doing Statistics in Second Language Research Using R,", href="http://cw.routledge.com/textbooks/9780805861853/guide-to-R.asp", target="_blank"),
            'written by Dr. Jenifer Larson-Hall.'),

            p('Also, if you are a cool Mac user and want to use R with GUI,',
            a("MacR", href="http://www.urano-ken.com/blog/2013/02/25/installing-and-using-macr/", target="_blank"),
            'is defenitely the way to go!'),

        br(),

        strong('Author'),
            p(a("Atsushi MIZUMOTO,", href="http://mizumot.com", target="_blank"),' Ph.D.',br(),
            'Associate Professor of Applied Linguistics',br(),
            'Faculty of Foreign Language Studies /',br(),
            'Graduate School of Foreign Language Education and Research,',br(),
            'Kansai University, Osaka, Japan'),

            br(),

        a(img(src="http://i.creativecommons.org/p/mark/1.0/80x15.png"), target="_blank", href="http://creativecommons.org/publicdomain/mark/1.0/")
    )
    )
)
))
Code license: GPL-3