Variables in Psychology

- The independent variable is the variable that is controlled and manipulated by the experimenter.

For example, in an experiment on the impact of sleep deprivation on test performance, sleep deprivation would be the independent variable.

- The dependent variable is the variable that is measured by the experimenter.

In our previous example, the scores on the test performance measure would be the dependent variable.

Impact of sleep deprivation on test performance -

Independent = Sleep deprivation.

Dependent = Scores on the performance test.

Extraneous variables also play a role. This type of variable may have an impact on the relationship between the independent and dependent variables.

For example, in the effects of sleep deprivation on test performance, other factors such as age, gender and academic background may have an impact on the results.

In such cases, the experimenter will note the values of these extraneous variables so this impact on the results can be controlled for.

There are 2 types of extraneous variables:

- Participant Variables

- Situational Variables

Participant Variables -

These extraneous variables are related to individual characteristics of each participant that may impact how he or she responds.

These factors can include background differences, mood, anxiety, intelligence, awareness and other characteristics that are unique to each person.

Situational Variables -

These extraneous variables are related to things in the environment that may impact how each participant responds.

For example, if a participant is taking a test in a chilly room, the temperature would be considered an extraneous variable.

Some participants may not be affected by the cold, but others might be distracted or annoyed by the temperature of the room.

In many cases, extraneous variables are controlled for by the experimenter.

In the case of participant variables, the experiment might select participants that are the same in background and temperament to ensure that these factors do not interfere with the results.

If, however, a variable cannot be controlled for, it becomes what is known as a confounding variable.

This type of variable can have an impact on the dependent variable, which can make it difficult to determine if the results are due to the influence of the independent variable, the confounding variable or an interaction of the two.

Confounding variable examples - Weather or a dog bark in the distance.

(things that aren't controlled by the independent variable)