2.5

These flashcards cover key concepts related to regression analysis, residual analysis, and the implications of correlation in statistical studies.

Regression

A statistical method used to determine the relationship between variables, particularly how one variable affects another.

Residuals

The difference between an observed value and the value predicted by the regression line.

Residual Plot

A scatterplot of the regression residuals against the explanatory variable, used to assess the fit of a regression line.

Outlier

An observation that lies outside the overall pattern of the other observations in a data set.

Influential Observation

An observation that has a significant impact on the result of a statistical analysis when removed.

Lurking Variable

A variable that is not included among the explanatory or response variables in a study but may still influence the interpretation of relationships.

Correlation

A statistical measure that describes the extent to which two variables change in relation to each other.

Association Does Not Imply Causation

The principle that correlation between two variables does not necessarily mean that one causes the other.

Least-Squares Residuals

The differences between observed and predicted values in regression analysis that are minimized in the least-squares method.

Explanatory Variable

The variable that is manipulated or considered in a study to examine its effect on the response variable.