Relationship between variables and MPG

mtcars dataset

SwhGo_oN
Part2 - Reproducible Pitch Presentation

Deployed App

Part0: Regression Models Course Project

URL: http://swhgoon.github.io/devdataprod-cp/part0_regmods-mtcars.html
Difference of the MPG between automatic and manual transmissions is focused in Part0.

Part1: Shiny Application

URL: https://swhgoon.shinyapps.io/part1_devdataprod-shiny/
A shiny-App shows the relationship between variables and miles per gallon (MPG).

Part2: Reproducible Pitch Presentation

URL: http://swhgoon.github.io/devdataprod-cp/part2_devdataprod-slidify

Get all SourceCode @Github:

git clone https://github.com/swhgoon/devdataprod-cp.git

mtcars dataset - Description

Motor Trend Car Road Tests

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

Henderson and Velleman (1981), Building multiple regression models interactively. Biometrics, 37, 391–411.

library(datasets)
head(mtcars, 3)

##                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

mtcars dataset - Format

A data frame with 32 observations on 11 variables.

Index	Field	Detail
[, 1]	mpg	Miles/(US) gallon
[, 2]	cyl	Number of cylinders
[, 3]	disp	Displacement (cu.in.)
[, 4]	hp	Gross horsepower
[, 5]	drat	Rear axle ratio
[, 6]	wt	Weight (lb/1000)
[, 7]	qsec	1/4 mile time
[, 8]	vs	V/S
[, 9]	am	Transmission (0 = automatic, 1 = manual)
[,10]	gear	Number of forward gears
[,11]	carb	Number of carburetors

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)
    })  })