Regressiopetäminen

Regressiopetäminen, a Finnish term, translates to "regression fraud" or "regression deception." It describes a scenario where the results of a regression analysis are intentionally misrepresented or manipulated to support a predetermined conclusion, rather than to accurately reflect the underlying data. This can occur in various fields, including academic research, business analytics, and policy-making.

The core of regressiopetäminen lies in distorting the findings of a statistical model, typically a regression model. This distortion can take many forms. For instance, researchers might selectively choose variables that produce a desired outcome, omit crucial confounding factors, or misinterpret the statistical significance of the results. Another common tactic is to cherry-pick data points that align with the intended narrative or to apply inappropriate statistical methods that inflate the perceived strength of a relationship.

The motivations behind regressiopetäminen can vary. It might be driven by a desire to publish findings, secure funding, promote a particular agenda, or protect an existing reputation. Regardless of the motive, the consequence is a misleading representation of reality, which can lead to flawed decision-making, erosion of trust in data-driven insights, and potentially harmful societal impacts. Identifying and preventing regressiopetäminen requires a critical approach to data analysis, transparency in methodology, and rigorous peer review processes.