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knitr::opts_chunk$set(echo = TRUE) library(rhandsontable)
inputPanel( sliderInput("los", label = "Enter the level of significance:", min = 0.01, max = 0.1, value = 0.05, step = 0.01), selectInput("Tail", label = " For Single Proportion testChoose among less(lower tail),greater(upper tail),two.sided(Two tail)", choices = c("less","greater","two.sided"), selected = "two.sided") ) mainPanel( rHandsontableOutput("testdata"), verbatimTextOutput("MD"), h6("", tags$img(src ="K.JPG", height= 400, width=400)) ) output$testdata<- renderRHandsontable({ ds = data.frame(observed_frequency = c(540,480,40,140), proportion =c(0.48,0.38,0.04,0.10)) rhandsontable(data.frame(ds)) }) output$MD<-renderPrint({ test_data = data.frame(hot_to_r(input$testdata)) attach(test_data) res <- chisq.test(observed_frequency,p = proportion ) test_data$expected_frequency = res$expected cat(sprintf("\nThe expected frequencies are as follows\n")) cat(sprintf("%f",test_data$expected_frequency)) cat(sprintf("\nThe results of the test(two-sided) are as follows\n")) print(res) if(input$Tail == "two.sided") { if(res$p.value < input$los) {cat(sprintf("There is enough evidence to reject NULL hypothesis of Goodness of Fit"))} else {cat(sprintf("There is not enough evidence to reject NULL hypothesis of Goodness of Fit"))} } else { cat(sprintf("\nThe p-value for one-sided test is %f\n",(res$p.value/2))) if((res$p.value/2)< input$los) {cat(sprintf("There is enough evidence to reject NULL hypothesis "))} else {cat(sprintf("There is not enough evidence to reject NULL hypothesis "))} } } )
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