Chisquare Goodness of Fit Test or Single population proportion Test"

In GOFShiny: Interactive Document for Working with Goodness of Fit Analysis

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 "))}  

       }




   } )

GOFShiny documentation built on July 31, 2019, 5:09 p.m.