Correlation and Regression - Errors and Pitfalls

Correlation and regression are important tools for empirical research to establish, justify and describe relations between characteristics. The concepts stem from a specific historical background and were intended to imitate causal connections for empirical research in wider areas than physics. While in physics the rank of causality has been changed drastically by entrenching theoretical physics models with genuine - randomness, the search for causal relations in soft sciences is still an ideal. The methods are applied by scientists from other disciplines than mathematics and statistics who have to interpret them from a “wider perspective”. However, misunderstandings and misinterpretations about the concepts involved are also wide-spread even among statisticians. Common errors and pitfalls with regression and correlation are dealt with to enhance the concepts.