What are extraneous variables?

Extraneous variables are all variables not related to the independent variable that could affect the results of an experiment. They can introduce noise or variability into the data, potentially leading to inaccurate conclusions about the relationship between the independent and dependent variables. Identifying and controlling for extraneous variables is crucial for establishing a clear causal relationship in psychological studies.

For instance, if researchers are studying the effects of a new teaching method on student performance (where the teaching method is the independent variable), factors such as students' prior knowledge, socio-economic status, or even environmental conditions like classroom lighting can act as extraneous variables. If these factors are not accounted for, they can skew the results, making it difficult to ascertain whether any changes in student performance were truly due to the teaching method itself.

The other options do not accurately define extraneous variables. The manipulation of variables is specifically related to independent variables, while controlled variables refer to those that are kept constant to prevent them from affecting the outcome. Additionally, variables that measure the dependent variable describe the outcomes being assessed and do not encapsulate the wider category of extraneous factors.