A simple Shiny application that predicts car fuel efficiency using regression.

Fuel efficiency is an important factor when choosing a car. This app allows users to explore how different car features affect MPG.

The application uses the built-in mtcars dataset.

head(mtcars)

##                    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
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

A linear regression model is trained using cylinders, horsepower, and weight.

model <- lm(mpg ~ cyl + hp + wt, data = mtcars)
summary(model)

## 
## Call:
## lm(formula = mpg ~ cyl + hp + wt, data = mtcars)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.9290 -1.5598 -0.5311  1.1850  5.8986 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 38.75179    1.78686  21.687  < 2e-16 ***
## cyl         -0.94162    0.55092  -1.709 0.098480 .  
## hp          -0.01804    0.01188  -1.519 0.140015    
## wt          -3.16697    0.74058  -4.276 0.000199 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.512 on 28 degrees of freedom
## Multiple R-squared:  0.8431, Adjusted R-squared:  0.8263 
## F-statistic: 50.17 on 3 and 28 DF,  p-value: 2.184e-11

• Simple and interactive
  
• Demonstrates reactive programming
  
• Useful for quick MPG estimation