Data Analytics Guide

• Correlation: A statistical measure that describes the extent to which two variables tend to change together. It indicates a relationship but not necessarily a cause-and-effect link. • Control Group: In formal experiments, a group that does not receive the treatment or intervention being studied, used as a baseline for comparison. • Ethical Limitations: Constraints on analytics related to moral principles and standards, ensuring that data use and algorithms do not violate societal values or lead to unfair outcomes. • Feedback Loop: A system where outputs are returned as inputs to influence future actions, allowing for continuous improvement of models or processes based on results. • Legal Limitations: Constraints on analytics imposed by laws and regulations, particularly concerning data privacy, collection, usage, and individuals' rights over their data. • Outliers: Data points that significantly differ from other observations, potentially indicating errors or unusual events. • Practical Limitations: Constraints on analytics arising from real-world factors such as data quality, the complexity of situations, and the skill of the analysts. • Statistical Significance: A determination by a statistical test that an observed effect is unlikely to have occurred by chance, suggesting a real relationship or difference. • Transparency (in AI): The ability to understand how an AI system works, how it makes decisions, and the data it uses, especially important for accountability and bias detection.