PSTAT5A: Understanding Data

A comprehensive course website for PSTAT5A (Understanding Data) at UCSB, featuring interactive lectures, labs, worksheets, and resources built with Quarto.

📚 Course Overview

PSTAT5A is an introductory statistics course that covers:

• Descriptive Statistics: Data visualization, measures of central tendency and variability
• Probability Foundations: Basic probability concepts, conditional probability, and Bayes' theorem
• Random Variables: Discrete and continuous distributions
• Statistical Inference: Confidence intervals and hypothesis testing
• Linear Regression: Basic regression analysis and modeling

🚀 Features

• Interactive Lectures: Reveal.js presentations with embedded Python code execution
• Jupyter Notebooks: Hands-on labs with real data analysis
• Worksheets: Practice problems with solutions
• Responsive Design: Mobile-friendly interface
• Search Functionality: Easy navigation through course materials
• Modern UI: Clean, professional design with smooth animations
• Tabbed Schedule: Organized weekly content with filtering options
• Real-time Code Execution: Live Python code examples in lectures
• Mathematical Typesetting: Beautiful math rendering with KaTeX
• Cross-platform: Works on Windows, macOS, and Linux

🛠️ Technology Stack

• Quarto: Scientific and technical publishing system
• Python: Data analysis and statistical computing
• Reveal.js: Interactive slide presentations
• Jupyter: Interactive computing and data science
• KaTeX: Fast math typesetting
• Bootstrap: Responsive CSS framework

🎯 What You'll Learn

This course provides a comprehensive introduction to statistics and data analysis, covering:

📊 Descriptive Statistics

• Data visualization and exploration
• Measures of central tendency and variability
• Understanding data distributions

🎲 Probability Foundations

• Basic probability concepts and rules
• Conditional probability and independence
• Bayes' theorem and applications

📈 Statistical Inference

• Sampling methods and strategies
• Confidence intervals for means and proportions
• Hypothesis testing fundamentals

🔍 Data Analysis

• Linear regression basics
• Model interpretation and validation
• Real-world applications

📚 Course Content

Week 1: Introduction & Descriptive Statistics

• Introduction to statistics and data analysis
• Descriptive statistics fundamentals
• Data visualization techniques

Week 2: Probability Foundations

• Basic probability concepts
• Conditional probability
• Bayes' theorem

Week 3: Conditional Probability, Counting & Random Variables

• Advanced probability topics
• Counting principles
• Introduction to random variables

Week 4: Random Variables & Distributions

• Continuous random variables
• Probability distributions
• Sampling and confidence intervals

Week 5: Inference & Statistical Modeling

• Sampling strategies
• Confidence intervals
• Hypothesis testing

Week 6: Hypothesis Testing, Regression & Course Wrap-Up

• Advanced hypothesis testing
• Linear regression basics
• Course review and applications

🚀 Quick Start

Want to get up and running quickly? Here's the fastest way:

# Clone the repository
git clone https://github.com/yourusername/PSTAT5A.git
cd PSTAT5A/web/PSTAT5A

# Install dependencies
pip install -r requirements.txt

# Start the development server
quarto preview

Then open your browser to http://localhost:4292/ and you're ready to go!

🛠️ Getting Started

Prerequisites

• Quarto (latest version)
• Python (3.8 or higher)
• Jupyter (for interactive notebooks)

Installation

1. Clone the repository

   git clone https://github.com/yourusername/PSTAT5A.git
   cd PSTAT5A/web/PSTAT5A

2. Install Python dependencies

   pip install -r requirements.txt

3. Install Quarto (if not already installed)

   # macOS
   brew install quarto
   
   # Windows
   # Download from https://quarto.org/docs/get-started/
   
   # Linux
   # Follow instructions at https://quarto.org/docs/get-started/

Development

1. Start the development server

   quarto preview

2. Build the website

   quarto render

3. View the site Open your browser and navigate to http://localhost:4292/

📖 Usage

For Students

• Navigate the Schedule: Use the tabbed interface to browse weekly content
• Interactive Lectures: Click through slides and run code examples
• Download Materials: Access labs, worksheets, and solutions
• Practice Problems: Work through exercises with step-by-step solutions
• Real-time Code: Execute Python code directly in the browser

🤝 Contributing

We welcome contributions! Please feel free to:

1. Report bugs by opening an issue
2. Suggest improvements through discussions
3. Submit pull requests for fixes and enhancements
4. Share feedback on course materials

Contributing Guidelines

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

The MIT License is a permissive license that allows for:

• Commercial use: You can use this software for commercial purposes
• Modification: You can modify the software
• Distribution: You can distribute the software
• Private use: You can use and modify the software without distributing it

👨‍🏫 Instructor

Narjes Mathlouthi
Department of Statistics and Applied Probability
University of California, Santa Barbara

🌐 Deployment

Local Development

quarto preview

Production Build

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Hosting Options

• GitHub Pages: Free hosting for public repositories
• Netlify: Easy deployment with drag-and-drop
• Vercel: Fast deployment with automatic builds
• University Servers: Host on your institution's web servers

GitHub Pages Setup

1. Enable GitHub Pages in your repository settings
2. Set source to /docs folder
3. Your site will be available at https://yourusername.github.io/PSTAT5A/

📞 Contact

• Email: [email protected]
• Course Website: https//pstat5a.com

📈 Project Status

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