Understanding how personality traits and demographics influence mental health is complex. This project tackles the challenge by analyzing data through cleaning, visuals, and advanced techniques, aiming to unravel these intricate connections for more targeted interventions.
This repository contains the code and results for a comprehensive analysis of the impact of personality traits and demographic factors on mental health outcomes. The project utilizes data cleaning, visualization, machine learning models, and statistical analyses to unravel complex relationships within mental health data.
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Notebook File: Team 10 - FP_FA23-DSCI 6002.ipynb
- This Jupyter Notebook file contains the code and step-by-step analysis of the project.
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SPSS Results Screenshots:
Screenshots of the SPSS results from the one-way ANOVA analyses: -
DASS Data CSV File: data.csv
- The dataset used for the analysis, including demographic information and DASS scores.
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Presentation: Team 10 Pitch Deck.pptx
- A presentation summarizing the key findings and insights of the analysis.
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PDF Report: Team 10 Mental Health Dynamics Analysis.pdf
- A detailed report providing an overview of the project, methodologies, results, and conclusions.
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Yash Malhotra - Project Guide
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Amjad Ali Kudsi - Team Leader, Data Analysis & Modeling
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Parin Patel - Storytelling & Data Visualization
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Karthik Vinnakota - Data Analysis
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Ramya Chava - Data Exploration
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Notebook Execution:
- Open the Jupyter Notebook file for a detailed walkthrough of the analysis.
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SPSS Results:
- Refer to the png files for screenshots of the SPSS results.
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Dataset:
- Access the dataset in for exploring the raw data.
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Presentation:
- Review the project's main findings and insights in the presentation.
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PDF Report:
- Delve into the detailed report for a comprehensive understanding of the project.
Feel free to explore each section according to your interests. If you have any questions or suggestions, please contact the team members.
Thank you for exploring our project!