2025-04-29

Introduction

This is a simple Shiny app that predicts the fuel efficiency (MPG) of a car based on its weight.

Application Functionality

  • Input: Car weight (slider)
  • Output: Predicted MPG
  • Dataset: mtcars
  • Model: Simple linear regression (MPG ~ Weight)

title: “Interactive Car Analysis - MPG Dataset” author: “Leão Pereira” date: “2025-04-29” output: ioslides_presentation —

1. Introduction

This presentation explores car performance using the mpg dataset.
We combine interactive charts and map-based visuals to better understand fuel efficiency trends.

2. Fuel Efficiency by Class

3. Engine Displacement vs Fuel Efficiency

4. Map of Manufacturers (Sample Locations)

5. Conclusion

  • SUV and pickup classes tend to have lower highway MPG.
  • Engine displacement is inversely correlated with fuel economy.
  • Visual tools enhance exploration of performance patterns.
  • Mapping manufacturers can support strategic decisions.

Thank you!

The Model

library(dplyr)
model <- lm(mpg ~ wt, data = mtcars)
summary(model)
## 
## Call:
## lm(formula = mpg ~ wt, data = mtcars)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.5432 -2.3647 -0.1252  1.4096  6.8727 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  37.2851     1.8776  19.858  < 2e-16 ***
## wt           -5.3445     0.5591  -9.559 1.29e-10 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.046 on 30 degrees of freedom
## Multiple R-squared:  0.7528, Adjusted R-squared:  0.7446 
## F-statistic: 91.38 on 1 and 30 DF,  p-value: 1.294e-10