PredictionAssignment4

Please find my App at https://zhangyinning.shinyapps.io/Prediction/. For this Shiny App, I use the dataset of cars, which comes from the dataset library. I generate a linear regression model and created an interactive plot to predict the result. The code for Server.R covers the following parts:

• Built the regression model
• Assign the input and the predicted result to Output
• Create the plot

Create the regression model:

library(shiny)
   model1 <- lm(dist ~ speed, data=cars)
   model1pred <- reactive({
    speedInput <- input$sliderSpeed
    predict(model1, newdata = data.frame(speed = speedInput))
   })

Create the plot.

  renderPlot({
          speedInput <- input$sliderSpeed
          plot(cars$speed, cars$dist, xlab = "Speed", ylab = "Stopping Distance", bty = "n", pch = 16, xlim = c(0, 30), ylim = c(0, 150))
          abline(model1, col = "red", lwd = 2)
          legend(25, 250, "Linear Model Prediction", pch = 16, col = "red", bty = "n", cex=1.2)
          points(speedInput, model1pred(), col = "red", pch =16, cex = 2)
})

<!–html_preserve–>

<!–/html_preserve–>

The ui file get the input of speed which is used to predict Stopping Distance. Also, it shows the plot and the predicted result. Here is the code for the input Sidebar

       sliderInput("sliderSpeed",
                   "Driving Speed",
                   min = 4,
                   max = 25,
                   value = 20)

<!–html_preserve–>

<!–/html_preserve–>