Analysis of Cars data

See the Regression Models Course Project

• URL: https://github.com/prabeeti/Developing-Data-Products
• All the data that have been use for this presentation and also for the creation of Shiny application and deploy it on Rstudio’s servers.

Shiny Application and Reproducible Pitch

This assignment has two parts. First, I have created a Shiny application and deploy it on Rstudio’s servers. This is a task for the data science coursera course about developing data products for week 4. As part of this, I have created a shiny app and deployed it on the shiny server. The link is https://prabeeti.shinyapps.io/DevelopingDataProducts_Week4Project/.

Overview

The shiny app plots graph against miles per gallon (mpg) for different variables like Displacement,Gross Horsepower,Rear axle ratio,Weigh,Number of forward gears,Number of carburetors, number of cylinders from the mtcars dataset. ## Details of Motor Trend Car Road Tests Datasets The data was extracted from the 1974 Motor Trend US magazine, and comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973-74 models).Source is Henderson and Velleman (1981), Building multiple regression models interactively. Biometrics, 37, 391-411.

library(datasets)
head(mtcars,5)

##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2

mtcars Dataset - Format

A data frame with 32 observations on 11 variables.

Analysis - Main Code

  formulaTextPoint <- reactive({
    paste("mpg ~", "as.integer(", input$variable, ")")  })
  
  fit <- reactive({
    lm(as.formula(formulaTextPoint()), data=mpgData)  })
  ...
  output$fit <- renderPrint({
    summary(fit()) })
  
  output$mpgPlot <- renderPlot({
    with(mpgData, {
      plot(as.formula(formulaTextPoint()))
      abline(fit(), col=2)
    })  })