Control of Variables

Extraneous variables?

variables (other than the IV) that could affect the DV, unless they are controlled. They are nuisance variables that we need to think about before conducting a study.

What do extraneous variables become if they are not controlled?

cofounding variables

Cofounding variables?

any variable other than the IV, that may have affected the DV so we cannot be sure of the true source of changes to the DV. Cofounding variables vary systematically with the IV.

Example of a cofounding variable?

personality

Participant variables?

natural and significant differences between participants that might unfairly influence the results

3 examples of Participant variables?

age, ethnicity and gender

Environmental variables?

any aspect of the research environment or situation (other than the IV) that might unfairly influence the results

3 examples of environmental variables?

time of day, temperature and noise levels

Demand characteristics?

any cues in the study that reveal the aims of the study to the participants, potentially affecting their behaviour

The 3 demand characteristics?

expectancy effect, screw-you effect and social desirability bias

Expectancy effect?

where a participant works out the aim of the study and changes their behaviour in a way they think suits the hypothesis

Screw-you effect?

the participant works out the aim of the study and changes their behaviour to purposefully damage the study

Social desirability bias?

participant changes their answers to appear more socially acceptable/fit in with societal norms

When is Social desirability bias most common?

when using self-report techniques

Investigator effects?

any effect of the investigator’s behaviour (unconscious and conscious) on the research outcome/participant behaviours

3 examples of investigator effects?

body language and tone of voice of the experimenter, use of leading questions to get certain answers and the selection of certain participants who the investigator thinks will give the ‘right’ results

Randomisation?

the use of chance to minimise the effects of bias when designing an experiment

Example of Randomisation?

randomising the order of conditions in a repeated measure design

Standardisation?

keeping the procedure and instructions exactly the same for each participant

Example of standardisation?

getting the researcher to read from a script