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A confounding variable is a variable which has an unintentional effect on the dependent variable. When carrying out experiments we attempt to control extraneous variables, however there is always the possibility that one of these variables is not controlled and if this effects the dependent variable in a systematic way we call this a confounding variable.
An extraneous variable is a variable which could effect the dependent variable but which is controlled so that it does not become a confounding variable.
A laboratory is any environment where variables can be well controlled. Such environments are usually artificial but do not have to resemble a science lab at school. Control groups are often used in experiments. This is a group which does not receive the manipulation of the independent variable and can be used for comparison with the experimental group or groups.
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ExperimentalAn experiment is a research method used by psychologists which involves the manipulation of variables in order to discover cause and effect. It differs from non-experimental methods in that it involves the deliberate manipulation of one variable, while trying to keep all other variables constant.
There are three main types of experiment - laboratory experiments, field experiments and quasi (natural) experiments.
A laboratory experiment is an experiment conducted under highly controlled conditions.
The variable which is being manipulated by the researcher is called the independent variable and the dependent variable is the change in behaviour measured by the researcher.
All other variables which might affect the results and therefore give us a false set of results are called confounding variables (also referred to as random variables).
By changing one variable (the independent variable) while measuring another (the dependent variable) while we control all others, as far as possible, then the experimental method allows us to draw conclusions with far more certainty than any non-experimental method. If the independent variable is the only thing that is changed then it must be responsible for any change in the dependent variable.
Laboratory experiments allow for precise control of variables. The purpose of control is to enable the experimenter to isolate the one key variable which has been selected (the independent variable), in order to observe its effect on some other variable (the dependent variable); control is intended to allow us to conclude that it is the independent variable, and nothing else, which is influencing the dependent variable.
However, it must also be noted that it is not always be possible to completely control all variables. There may be other variables at work which the experimenter is unaware of.
It is argued that laboratory experiments allow us to make statements about cause and effect, because unlike non-experimental methods they involve the deliberate manipulation of one variable, while trying to keep all other variables constant. Sometimes the independent variable is thought of as the cause and the dependent variable as the effect.
Furthermore, experiments can usually be easily replicated. The experimental method consists of standardised procedures and measures which allow it to be easily repeated.
However laboratory experiments are not always typical of real life situations. These types of experiments are often conducted in strange and contrived environments in which people are asked to perform unusual or even bizarre tasks. The artificiality of the situation, together with the 'unnatural' things that the participants may be asked to do, jointly produces a distortion of behaviour. Therefore, it should be difficult to generalise findings from experiments because they are not usually ecologically valid (true to real life).
A further difficulty with the experimental method is demand characteristics. Demand characteristics are all the cues which convey to the participant the purpose of the experiment. If a participant knows they are in an experiment they may seek cues about how they think they are expected to behave.
Another problem with the experimental method concerns ethics. For example, experiments nearly always involve deceiving participants to some extent and it is important to recognise that there are very many areas of human life which cannot be studied using the experimental method because it would be simply too unethical to do so.
A field experiment is an experiment that is conducted in ?the field ?. That is, in a real world situation. In field experiments the participants are not usually aware that that they are participating in an experiment.
The independent variable is still manipulated unlike in natural experiments. Field experiments are usually high in ecological validity and may avoid demand characteristics as the participants are unaware of the experiment. However, in field experiments it is much harder to control confounding variables and they are usually time consuming and expensive to conduct.
In field experiments it is not usually possible to gain informed consent from the participants and it is difficult to debrief the participants.
Quasi or natural experiments
A quasi experiment is where the independent variable is not manipulated by the researcher but occurs naturally. These experiments are often called natural experiments.
In a true experiment participants are allocated to the conditions of an experiment, usually through random assignment, however this is not always possible for practical or ethical reasons.
In a quasi experiment the researcher takes advantage of pre-existing conditions such as age, sex or an event that the researcher has no control over such as a participants? occupation.
A strength of quasi experiments is that participants are often unaware that they are taking part in an investigation and they may not be as artificial as laboratory experiments.
However, it is argued that with quasi experiments it is harder to establish causal relationships because the independent variable is not being directly manipulated by the researcher.
It is worth noting that quasi experiments are very common in psychology because ethically and practically they are the only design that can be used.
An important procedure to be aware of when researchers carry out experiments is experimental design.
An experimental design is a set of procedures used to control the influence of participant variables so that we can investigate the possible effects of the independent variable on the dependent variable.
There are three basic experimental designs - independent measures design, repeated measures design and matched pairs design.
An independent measures design consists of using different participants for each condition of the experiment. If two groups in an experiment consist of different individuals then this is an independent measures design.
This type of design has an advantage resulting from the different participants used in each condition - there is no problem with order effects
The most serious disadvantage of independent measures designs is the potential for error resulting from individual differences between the groups of participants taking part in the different conditions. Also an independent groups design may represent an uneconomic use of those participants, since twice as many participants are needed to obtain the same amount of data as would be required in a two-condition repeated measures design.
A repeated measures design consists of testing the same individuals on two or more conditions.
The key advantage of the repeated measures design is that individual differences between participants are removed as a potential confounding variable. Also the repeated measures design requires fewer participants, since data for all conditions derive from the same group of participants.
The design also has its disadvantages. The range of potential uses is smaller than for the independent groups design. For example, it is not always possible to test the same participants twice.
There is also a potential disadvantage resulting from order effects, although these order effects can be minimised. Order effects occur when people behave differently because of the order in which the conditions are performed. For example, the participant?s performance may be enhanced because of a practice effect, or performance may be reduced because of a boredom or fatigue effect.
Order effects act as a confounding variable but can be reduced by using counterbalancing. If there are two conditions in an experiment the first participant can do the first condition first and the second condition second. The second participant can do the second condition first and the first condition second and so on. Therefore any order effects should be randomised.
A matched pairs design consists of using different participants for each condition of the experiment but participant variables are controlled by matching pairs of variables on a key variable.
In order to get the pairing precise enough, it is common to get one group of participants together and then look round for partners for everyone. Participants can be matched on variables which are considered to be relevant to the experiment in question. For example, pairs of participants might be matched for their scores from intelligence or personality tests.
Although this design combines the key benefits of both an independent and repeated measures design, achieving matched pairs of participants is a difficult and time consuming task which may be too costly to undertake. Successful use of a matched pairs design is heavily dependent on the use of reliable and valid procedures for pre-testing participants to obtain matched the pairs.