https://github.com/stefagnone/-employee-salary-analysis-and-insights

Predictive analysis of employee salary determinants for an anonymized dataset, highlighting key factors influencing salary and providing insights for salary policy improvements.
https://github.com/stefagnone/-employee-salary-analysis-and-insights

business-intelligence data-analysis data-science employee-salary-analysis excel gender-pay-gap predictive-insights regression-modeling spss statistical-analysis

Last synced: 10 days ago
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Predictive analysis of employee salary determinants for an anonymized dataset, highlighting key factors influencing salary and providing insights for salary policy improvements.

• Host: GitHub
• URL: https://github.com/stefagnone/-employee-salary-analysis-and-insights
• Owner: stefagnone
• Created: 2024-11-14T17:50:22.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-12-05T11:34:38.000Z (3 months ago)
• Last Synced: 2024-12-19T01:13:23.987Z (2 months ago)
• Topics: business-intelligence, data-analysis, data-science, employee-salary-analysis, excel, gender-pay-gap, predictive-insights, regression-modeling, spss, statistical-analysis
• Homepage:
• Size: 1.76 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## Project Overview

In this project, I performed an in-depth analysis on a dataset representing anonymized employee data to identify factors influencing salary. This blind analysis, conducted for an auditing client, required inferring data labels, understanding industry implications, and predicting salary determinants.

The analysis focused on:

- Renaming columns based on inferred data meanings.

- Conducting descriptive, correlation, and regression analyses to understand salary impact factors.

- Providing actionable recommendations for salary policy improvement.

This project showcases skills in statistical analysis, data interpretation, and executive reporting for real-world business insights.

## Technologies Used

- **SPSS**: Statistical analysis and regression modeling

- **Excel**: Data cleaning, organization, and descriptive statistics

- **Microsoft PowerPoint**: Presentation and executive summary visualization

- **Microsoft Word**: Executive report creation

## Repository Structure

- `Data/`: Contains the dataset file (`Salaries.csv`).

- `Analysis/`: Final report and presentation slides:

    - `Executive Report - Stefano Compagnone.pdf`: A 1-page report summarizing findings.

    - `Individual assignment final (Stefano Compagnone).pptx`: Presentation slides with insights and recommendations.

## Key Insights

- **Gender Pay Gap**: Women earn approximately $2,000 less than men, underlining a gender disparity in salary policy.

- **Education Impact**: Each additional year of education increases salary by approximately $502.

- **Entry Salary Influence**: Initial salary has a strong positive correlation with current salary, indicating salary growth for long-term employees.

- **Position Level**: Higher-level positions are associated with significant salary increases, supporting a structured career progression within the company.

## Instructions

1. Clone this repository.

2. Review the `Data/` folder for the dataset (`Salaries.csv`).

3. Open `Executive Report - Stefano Compagnone.pdf` for a summary of findings.

4. Refer to `Individual assignment final (Stefano Compagnone).pptx` for an in-depth presentation.

## Contact

Connect with me on [LinkedIn](https://www.linkedin.com/in/stefano-compagnone98/) for more information or explore my other projects on GitHub.