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An experiment focuses on two specific variables: the independent variable and the dependent variable. The idea is that the manipulation of the I.V will cause the response measured of the D.V. However within every experiment there are thousands of other variables that are constantly changing. For example all participants entering an experiment have different backgrounds, heights, weights, personalities etc.. Furthermore the conditions of the experiment are constantly changing such as the lighting, temperature, weather changes, and people getting tired or bored and so on. All these extra variables are called extraneous variables, which cannot be avoided and therefore it is important that the researcher doesn’t let these turn into confounding variables. If an extraneous variable turns into a confounding variable then it can undermine the internal validity of an experiment and potentially cause a type 1 error.

For an extraneous variable to turn into a confounding variable it must influence the dependent variable. If the extraneous variable is totally unrelated to the dependent variable then it is not a threat. For example everyone knows Milgram’s obedience study, in this experiment participants would all be wearing different types of shoes (trainers, sandals, heels, flats, etc) however it is unlikely that the type of shoe one is wearing has any influence on participants obedience levels. Therefore it was not necessary to control participants shoe variable. Secondly a confounding variable must vary systematically with the independent variable. If the variable changes randomly with no relation to the independent variable then it is not a threat.

 To control an extraneous variable the researcher needs to firstly identify those variables that are most likely to influence the dependent variable. This is done based on the researcher’s common sense, simple logical reasoning and past experience. For example it is obvious that a loud busy room can cause distractions that lower performance opposed to a quiet room, therefore by using a quiet room you are stopping the extraneous variable of noise from becoming a confounding variable. Furthermore once identifying an extraneous variable they can be controlled by either holding a variable constant or matching values across treatment conditions. The extraneous variables can be hold constant by creating a standardized environment and procedure so that all variables are the same in each condition and therefore cannot be confounding. By matching the values across treatment conditions you are ensuring that the variable does not vary across the treatment conditions, for example participants are assigned so that the average age is the same for all different treatment conditions.

 If the extraneous variable is not controlled then it can turn into a confounding variable which means the conclusion reached in an experiment may not be correct. For example, an experiment measuring group interaction on a playing field came to the conclusion that boys are more sociable than girls however when the girls were on the playing field the weather was rainy which may have caused them to be cold and not feel very sociable. Therefore the weather is the confounding variable and has lead the researcher to come to a false conclusion.

 In conclusion it is extremely important when conducting research to stop extraneous variables from turning into confounding variables. Although it is hard to hold all other variables apart from the I.V constant there are ways around stopping most extraneous variables from becoming confounding.

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