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library(shiny)
shinyServer(function(input,output,session){
observe({
inFile <- input$file1
if(is.null(inFile))
dt <- read.table('means_data.txt', header=T, sep='\t')
else dt <- read.csv(inFile$datapath, header=input$header,
sep=input$sep)
updateSelectInput(session, "variable", choices=names(dt))
})
output$inputData <- renderTable({
inFile <- input$file1
if(is.null(inFile))
dt <- read.table('means_data.txt', header=T, sep='\t')
else dt <- read.csv(inFile$datapath, header=input$header,
sep=input$sep)
dt
})
output$statistic <- renderTable({
inFile <- input$file1
if(is.null(inFile))
dt <- read.table('means_data.txt', header=T, sep='\t')
else dt <- read.csv(inFile$datapath, header=input$header,
sep=input$sep)
y <- na.omit(dt[, input$variable]) # Para sacar los NA de la variable
res <- data.frame(Media=mean(y), Varianza=var(y), n=length(y))
colnames(res) <- c('Media', 'Varianza', 'Número obs')
res
}, align='c', bordered = TRUE)
output$appPlot <- renderPlot({
inFile <- input$file1
if(is.null(inFile))
dt <- read.table('means_data.txt', header=T, sep='\t')
else dt <- read.csv(inFile$datapath, header=input$header,
sep=input$sep)
y <- na.omit(dt[, input$variable]) # Para sacar los NA de la variable
par(mfrow=c(1, 2), bg='gray98')
hist(y, col='deepskyblue3', freq=F, las=1,
xlab=as.character(input$variable),
main='Histograma y densidad', ylab='Densidad')
lines(density(y), lwd=4, col='firebrick3')
qqnorm(y, las=1, main='QQplot', xlab='Cuantiles teóricos N(0, 1)',
pch=19, col='deepskyblue3',
ylab=as.character(input$variable))
qqline(y)
shapi <- shapiro.test(x=y)
legend('topleft', bty='n', col='red', text.col='deepskyblue3',
legend=paste('Valor P=', round(shapi$p.value, 2)))
})
output$resul1 <- renderText({
inFile <- input$file1
if(is.null(inFile))
dt <- read.table('means_data.txt', header=T, sep='\t')
else dt <- read.csv(inFile$datapath, header=input$header,
sep=input$sep)
y <- na.omit(dt[, input$variable]) # Para sacar los NA de la variable
ph <- t.test(x=y, alternative=input$h0, mu=input$mu0,
conf.level=input$alfa)
paste0('El estadístico de prueba es to=', round(ph$statistic, 2),
' con un valor-P de ', round(ph$p.value, 4), '.')
})
output$resul2 <- renderText({
inFile <- input$file1
if(is.null(inFile))
dt <- read.table('means_data.txt', header=T, sep='\t')
else dt <- read.csv(inFile$datapath, header=input$header,
sep=input$sep)
y <- na.omit(dt[, input$variable]) # Para sacar los NA de la variable
ph <- t.test(x=y, alternative=input$h0, mu=input$mu0,
conf.level=input$alfa)
intervalo <- paste("(", round(ph$conf.int[1], digits=4), ", ",
round(ph$conf.int[2], digits=4), ").", sep='')
paste0('El intervalo de confianza del ', 100*input$alfa,
'% para la media poblacional es ', intervalo)
})
})
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