Differential privacy manages the release of accurate statistics while protecting individual privacy by introducing a controlled amount of noise to the data or analysis results. This noise blurs the influence of any specific data point, preventing the inference of individual information while maintaining the overall accuracy and utility of the statistical results. The level of noise is carefully calibrated to strike a balance between data utility and privacy protection. While the altered data may not be exact, it typically reflects accurate population-level trends and insights. This approach allows for the dissemination of useful statistical information for research and policy-making without compromising