What are the Challenges in Interpreting Aggregate Results?
Interpreting aggregate results comes with several challenges:
1. Confounding Variables: These are variables that may affect the outcome and need to be controlled for accurate interpretation. 2. Bias: Different types of biases such as selection bias, information bias, and recall bias can distort the results. 3. Causality vs. Correlation: Distinguishing between causal relationships and mere associations is often challenging. 4. Data Quality: The reliability of aggregate results is heavily dependent on the quality of data collected.
