Created on: June 19, 2025

This presentation pitches a Shiny app that predicts a car’s miles per gallon (mpg) based on its weight using the mtcars dataset. It’s designed for easy use by novices, with interactive features and clear documentation.

Purpose: Predict mpg using a simple linear regression model.

Dataset: mtcars (built-in R dataset with 32 cars).

Features: Slider input for weight, reactive mpg prediction.

Link: https://yuemin2025.shinyapps.io/mpg_prediction/

Step 1: Open the app at the provided link.

Step 2: Adjust the “Weight” slider (1.5–5.5 thousand lbs).

Step 3: View the predicted mpg, which updates instantly.

No R knowledge needed—just slide and explore!

knitr::opts_chunk$set(echo = FALSE)
library(plotly)

## Loading required package: ggplot2

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

This scatter plot with a regression line shows the relationship modeled by the app.

Offers a simple, interactive tool for car efficiency predictions.

Code on GitHub: https://github.com/Yuemin2025/Developing_Data_Products

App on Shinyapps.io: https://yuemin2025.shinyapps.io/mpg_prediction/