This presentation describes the MPG Predictor Shiny App, which estimates miles per gallon based on engine cylinders and horsepower.

We use the built-in mtcars dataset.

##       mpg             cyl              hp       
##  Min.   :10.40   Min.   :4.000   Min.   : 52.0  
##  1st Qu.:15.43   1st Qu.:4.000   1st Qu.: 96.5  
##  Median :19.20   Median :6.000   Median :123.0  
##  Mean   :20.09   Mean   :6.188   Mean   :146.7  
##  3rd Qu.:22.80   3rd Qu.:8.000   3rd Qu.:180.0  
##  Max.   :33.90   Max.   :8.000   Max.   :335.0

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

## 
## Call:
## lm(formula = mpg ~ cyl + hp, data = mtcars)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.4948 -2.4901 -0.1828  1.9777  7.2934 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 36.90833    2.19080  16.847  < 2e-16 ***
## cyl         -2.26469    0.57589  -3.933  0.00048 ***
## hp          -0.01912    0.01500  -1.275  0.21253    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.173 on 29 degrees of freedom
## Multiple R-squared:  0.7407, Adjusted R-squared:  0.7228 
## F-statistic: 41.42 on 2 and 29 DF,  p-value: 3.162e-09

Users pick:

• number of cylinders

• horsepower

The app returns predicted MPG.

The app is deployed here: https://sleepystitch.shinyapps.io/mpg_predict/

• Built in Shiny

• Uses reactive prediction

• Presentation created with RStudio Presenter

• Code + app available on Rpubs and Github