In statistics, a collider can affect the relationship between variables, leading to false impressions. For example, controlling for a collider can change the true effect of one variable on another.
Berkson's Paradox shows how relationships between variables can change when selecting samples based on certain traits, leading to counterintuitive results.
The impact of weighting test scores in selection processes can alter the relationship between test scores and outcomes. Higher weighting can sometimes lead to negative correlations, despite the underlying positive relationship.