README.md

Probability Perception Experiment Application

Welcome to the Probability Perception Experiment Application! This application is based on the paper titled "A Discrete Adjustment Experiment on Reporting Probabilities" by Kathryn Blackmond Laskey, Paul R. Wilson, and Steven F. Lehrer.

Introduction

This application aims to simulate the discrete adjustment experiment described in the paper, allowing users to participate in a study of probability perception and reporting. Participants will be presented with scenarios and asked to provide their probability estimates for certain events.

Project Structure

• frontend: Contains the frontend React.js application.
• backend: Contains the backend Node.js application built with Express.js.
• add .env file with the with paramenters DB_HOST, DB_DATABASE, DB_USER, and DB_PASSWORD. Also, add NO_OF_ROUND to set number of rounds for experiment.

Prerequisites

Before running this application, ensure you have the following installed:

• Node.js (https://nodejs.org)
• MongoDB (https://www.mongodb.com)
• npm (Node Package Manager)

Installation

1. Clone the repository: git clone https://github.com/ameya-shahu/probability-perception-exp-app.git
2. Navigate to the project directory: cd probability-perception-exp-app
3. Install dependencies for both frontend and backend:

   # dependencies for backend server
   npm install
   
   # dependencies for frontend
   cd ./frontend
   npm install
   

4. Start MongoDB service: mongod
5. Start the backend server:

   npm start
   

6. Start the frontend development server:

   cd ./frontend
   npm start
   

7. Access the application at http://localhost:3000 in your web browser.

Usage

• Participants can access the application through the provided URL and participate in the probability perception experiment.
• The backend server handles the logic and data management required for the experiment.
• Participants' responses are recorded and can be analyzed as per the experiment's requirements.

License

This project is licensed under the MIT License.

Acknowledgements

Special thanks to the authors of the paper "A Discrete Adjustment Experiment on Reporting Probabilities" for providing the inspiration and framework for this application.

---