Fuel Economy Explorer

A simple Shiny application for exploring how vehicle characteristics relate to fuel economy.

Fuel economy depends on several vehicle characteristics.

The app lets a user change:

• vehicle weight
• horsepower
• transmission type

and immediately see a predicted MPG value.

The application fits a linear regression model to the built-in mtcars dataset.

data(mtcars)
model <- lm(mpg ~ wt + hp + am, data = mtcars)
round(summary(model)$r.squared, 3)

[1] 0.84

The displayed R expression is evaluated when the presentation is rendered.

The user selects values with Shiny widgets.

The server then:

1. reads the selected inputs,
2. creates a new observation,
3. predicts MPG with predict(),
4. displays the result reactively,
5. places the prediction on a comparison plot.

example_vehicle <- data.frame(wt = 3.0, hp = 150, am = 0)
round(predict(model, newdata = example_vehicle), 1)

   1 
19.7 

• Simple enough for a novice user.
• Gives immediate reactive feedback.
• Demonstrates prediction with a real R dataset.
• Makes the effect of user-selected inputs easy to explore.
• Includes on-site documentation in the Shiny interface.

Deploy the app to shinyapps.io and publish this 5-slide presentation to RPubs.