In statistics, common response refers to changes in both the explanatory and response variables that result from changes in another variable. The variable that triggers a common response is typically not part of the research design.
A variable refers to an entity that can take on a numerical value or a certain characteristic. Variables are classified based on their type and purpose. There are two kinds of variables according to type: quantitative variable and categorical variable. A quantitative variable is a numerical measurement of data that is used in mathematical calculations.
Examples of this type of variable include age, height, temperature and salary. A categorical variable is any variable that is non-numeric. Examples of categorical variables include gender, party affiliation, school attended and hair color. In some cases, researchers assign numerical values to categories for a more convenient way of manipulating data.
Statistical studies are often conducted to measure the effects of one variable against another. An explanatory variable, also known as an independent or predictor variable, directly influences the response variable, which is referred to as the dependent or predicted variable.
However, an observed relationship between the two variables may be the result of an extraneous variable, known as a lurking variable. A common response occurs when a lurking variable causes a change in both the explanatory and response variables. For example, a college student's entrance exam rank does not necessarily lead to high grades. These variables share a common response to learning habits and knowledge.