Omitted variables are factors that influence both the dependent and independent variables but are not included in the analysis. Their absence can lead to an overestimation or underestimation of the relationship between the variables of interest. For instance, if we are studying the impact of air pollution on lung disease and omit variables like smoking and occupational exposure, the results may be misleading.
