Shiny App: Stopping Distance of Cars

• In this assignment we use “cars” dataset.
• This dataset contains data about different car speeds and the corresponding stopping distances
• In this assignment we apply linear model to the cars data
• We then allow user to select a speed
• Based on the speed we predict the stopping distance

• In the User Interface code, we allow the user to select speed through sliderinput

sliderInput("speed",
            "Enter Speed of car:",
            min = 4,
            max = 25,
            value = 15)

• In the server code, we apply linear model to the cars data
• We then use the speed given by the user and predict the stopping distance based on the LM

data("cars", package = "datasets")
linearmodel <- lm(dist ~ cars$speed, data = cars)
linearmodel

Call:
lm(formula = dist ~ cars$speed, data = cars)

Coefficients:
(Intercept)   cars$speed  
    -17.579        3.932  

coef_intercept <- coef(linearmodel)[1]
coef_speed <- coef(linearmodel)[2]
output$distance <- renderText({
    coef_intercept+ coef_speed*input$speed
})

• In the Main panel we display the estimated stopping distance
• We also plot the cars data ( stopping distance vs speed)
• We highlight the points that correspond to the user given speed.
• We then show the regression line based on linear model
• the estimated stopping distance is actually the value derived from this regression line