title: “MTCARS MPG Predictor” author: “Haider Ali” date: “2025-11-15” output: ioslides_presentation —

Introduction

This presentation describes my Shiny application created for the Developing Data Products course.

The app allows users to:

• Select predictor variables from the mtcars dataset
  
• Fit a linear regression model to predict MPG
  
• View model summary results
  
• Display predicted MPG for sample inputs
  
• Visualize a plot of Actual vs Fitted values

A deployed version of the app is available here:
[YOUR_SHINY_APP_LINK]

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About the Dataset

The application uses the built-in mtcars dataset.

Key dataset features:

• 32 cars
  
• Variables include mpg, wt, hp, cyl, disp, drat, gear, carb and more
  
• Ideal for demonstrating simple regression models
  
• Well-known dataset used in R examples

The goal of the app is to allow users to explore how different predictors influence fuel economy (MPG).

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How the App Works

The user interface includes:

• A checkbox menu for selecting predictor variables
  
• A button to run the selected model
  
• Display of the regression model output
  
• Predicted MPG for example input
  
• A plot showing Actual vs Fitted values

The server logic:

• Reactively builds a model using:
  mpg ~ selected_variables
  
• Calculates predicted MPG
  
• Renders model summary and visualization

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Screenshot of the App

Below is a placeholder image. Replace with a screenshot taken after deployment.

Shiny App Screenshot Placeholder

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Conclusion

This project demonstrates:

• How to build a Shiny app using ui.R and server.R
  
• How to deploy a Shiny app online
  
• How to build and publish a reproducible pitch presentation

To access the live app:
[YOUR_SHINY_APP_LINK]

Thank you for viewing!