Employee-Satisfaction-Analysis-Using-R

Employee Satisfaction Analysis Using R

This project analyzes employee satisfaction and workplace dynamics using statistical techniques in R. The analysis examines factors that influence employee job satisfaction across 3,025 survey responses from a fictional company.

📊 View the Live Report

The full analysis report is available on GitHub Pages: View Employee Satisfaction Analysis Report

Project Overview

This analysis explores relationships between various workplace factors and employee satisfaction using:

• Chi-squared tests for association between categorical variables
• One-way and Two-way ANOVA for comparing means across groups
• Multiple Linear Regression to model predictors of job satisfaction

Dataset

The dataset uses a synthetically made employee survey available on Kaggle.

Sample size: 3,025 employee responses

Key Variables Analyzed

• Demographics: Gender, Age, Job Level, Experience, Department
• Workplace Factors: Work-Life Balance, Work Environment, Work Load, Stress
• Well-being: Sleep Hours, Training Hours Per Year
• Outcome: Job Satisfaction

Required R Packages

Install the required packages before running the analysis:

install.packages(c("readxl", "dplyr", "ggplot2", "corrplot", "knitr", "gridExtra"))

How to Run

1. Clone this repository
2. Open R or RStudio
3. Install required packages (see above)
4. Open Project_Alexandre_Saliba.Rmd in RStudio
5. Ensure employee_survey.xlsx is in the same directory
6. Click “Knit” to generate the HTML report, or run chunks individually

Key Findings

• Stress and Job Satisfaction: Strong statistical association found between stress levels and job satisfaction
• Work Environment: Significant predictor of job satisfaction in regression analysis
• Demographics: Age and experience show positive correlation with training hours received
• Sleep Hours: No significant differences found across gender groups
• Work Load & Environment: No significant interaction effect on stress levels

Statistical Tests Performed

1. Chi-Squared Tests:
   • Job Level vs Stress
   • Stress vs Job Satisfaction
2. ANOVA Tests:
   • One-way ANOVA: Sleep Hours across Gender groups
   • Two-way ANOVA: Stress levels based on Work Load and Work Environment
3. Multiple Linear Regression:
   • Predictors of Job Satisfaction (Stress, Work-Life Balance, Work Environment, Training Hours, Gender)

Project Structure

.
├── Project_Alexandre_Saliba.Rmd    # Main analysis file
├── Project_Alexandre_Saliba.html  # Generated HTML report
├── employee_survey.xlsx            # Dataset
├── README.md                       # This file
└── .gitignore                      # Git ignore file

Author

Alexandre Saliba

License

This project is for educational and portfolio purposes.