Cautions about Correlation and Regression Section 4.2

Reminders Correlation and regression describe only linear relationships Correlation and LSRL are not resistant

Extrapolation The use of a regression line for prediction far outside the domain of values of the explanatory variable x that you used to obtain the line or curve Predictions are often not accurate

Lurking Variable A variable that is not among the explanatory or response variables in a study and yet may influence the interpretation of relationships among those variables

Using Averaged Data Averaged data smooths out the variation of individual observations

Explaining Association Common Response Confounding

Confounding When the variables effects on a response variable cannot be distinguished from each other Can be explanatory or lurking variables

Remember: Even when direct causation is present, it is rarely a complete explanation of an association between two variables Very strong association between two variables is not by itself good evidence that there is a cause-and-effect link between the variables

Establishing Causation The only method for determining causation is to conduct a carefully designed experiment

Practice Problems pg. 238 #4.38-4.49