Research Methods

What is an experiment?

An experiment is a research method used by psychologists which involves the manipulation of variables in order to discover cause and effect. (If other extraneous variables are controlled for) The independent variable is manipulated in order to cause a change in the dependent variable.The effect that the independent variable has on the dependent variable is investigated and measured.

Before researchers carry out an experiment they operationalise the variables and create hypotheses, a hypothesis a testable, predictive statement. 

When psychologists carry out experiments they use one of three basic experimental designs, these are independent, repeated or matched pairs desgin. Results are collected for the two conditions and compared to see if there is a significant difference.

There are three main types of experiment, laboratory, field and quasi. 

Variables

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.

The IV is a variable is a variable directly manipulated by the researcher. The DV is the variable that you think is affected by changes in the IV, the DV is the change in behaviour that is measured. The IV is thought of as the cause and the DV as the effect. The DV is dependent on the IV.

By changing one variable (the IV) while measuring another (the DV) while we control for others as much as possible, then the experimental method allows us to draw conclusions with far more certainity than any non-experimental method. If the IV is the only thing that is changed then it must be responsbile for any change in the DV, can establish cause and effect.

Extraneous variables is a variable which could effect the DV but which is controlled so that it does not become a confounding variable.An extraneous variable is any variable (other than the IV) that could affect what you are trying to measure. If these things are actually influencing the DV then they are called confounding variables. 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.

Operationalisation...

Before conducting a psychology experiement, it is essential to create firm operationalised definitions for both the independent variable and the depdenent variable.

Variables must be operationalised, this means describing the process by which the variable is measured. 

Operationalisation allows others to see exactly how you are going to define and measure your variables.

For example - ‘Memory is measured by the number of items correctly recalled from a list after 5 minutes’ is an operationalised variable. Similarly ‘aggression’ could be operationalised as the number of aggressive acts recorded in a 10 minute observation.

In the exam you can write this in brackets after the variable or you can writie it in sentences at the end of the question. 

Laboratory Experiments

A laboratory experiment is an experiment conducted under highly controlled conditions. - not necessarily a laboratory – and therefore accurate measurements are possible. Laboratory experiments are conducted in an artifical setting. 

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.

Strengths - experiments can be replicated, control the effects of confounding variables, possible to establish whether one variable actually causes change in another, scientific. 

Weaknesses - artificial so experiments might not measure real-life behaviour and be lacking in ecological validity, demand characterists meaning ppts may respond according to what they think is being investigated, ethics, experimenter bias.

Example - Loftus Weapon Focus

Field Experiments

In field experiments behaviour is measured in a natural environment (a school, a train, a street). A key variable is still altered so that its effect can be measured. Field experiements are done in everyday, real-life conditions. The experimenter still manipulates the IV, but in a natural setting so it is difficult to actually control extraneous variables. 

In field experiments the participants are not usually aware that that they are participating in an experiment.

Strengths - behavior in a field experiment is more likely to reflect life real because of its natural setting, i.e. higher ecological validity than a lab experiment, avoids demand characteristics if participants are not aware they are being studied.

Weaknesses - less control so confounding variables may be more likely in this environment, ethics in relation to participants who didn't agree to take part might experience distress and often cannot be debriefed, more difficult to replicate.

Example - Courtroom studies A2. 

Quasi Experiment

A quasi experiment (a natural experiment) is a study that measures variables that are not directly manipulated by the experimenter. They are not classed as really experiements hence 'quasi' experiments. The IV is not manipulated but is naturally occuring. 

The researcher takes advantage of pre-existing variables such as age, gender, occupation. 

Strengths - participants are often unaware that they are taking part in an investigation and they may not be as artificial as laboratory experiments so it avoids demand characterists, ethical as it is possible to study variables that would be unethical to manipulate. 

Weaknesses - you cannot randomly allocate participants to each condition so confounding variables may affect results, no control over the variables so it is difficult to say what is caused by what (harder to establish casual relationship), rare events - some groups of interest are hard to find, ethics because deception id often used which makes informed consent is difficult. 

Independent Measures

An independent measures design means there are different participants in each group. Participants are only in one condition. Different participants are used in each condition of the independent variable. This means that each condition of the experiment includes a different group of participants. This should be done by random allocation, which ensures that each participant has an equal chance of being assigned to one group or the other.

Independent measures involves using two separate groups of participants; one in each group.

Strengths- No order effects which means that no one gets better through practice (learning effect) or gets worse through being bored or tired (fatigue effect).

Weaknesses-More people are needed than with the repeated measures design as twice as many people are needed, participant vairables/individual differences there are differences between the people in each group which might affect the results so one group may just be better at the task or variations in age etc.

Repeated Measures

A repeated measures design is where the same participant takes part in both conditions of the independent variable. Each condition includes the same participants.They complete the task but under a different condition. 

Strengths- The same people do the test in both conditions so any differences between individuals shouldn't affect the results thus minimising participant variables, fewer partcicipants are needed to get the same amount of data so it is easier to obtain the sample. Weaknesses-There may be order effects as participants are performing more than one task then because they have had some practice or become bored or tired it means that one could be performed differently for a reason other than the IV. Order effects refer to the order of the conditions having an effect on the participants’ behaviour. 

The negative impact of order effects can be reduced by counterbalancing - varying the order in which participants take part. To combat order affects the research counter balances the order of the conditions for the participants.  Alternating the order in which participants perform in different conditions of an experiment.The sample is split in two groups experimental (A) and control (B).  For example, group 1 does ‘A’ then ‘B’, group 2 does ‘B’ then ‘A’ this is to eliminate order effects. 

Matched Pairs

A matched pairs design means that there are different participants in each condition, but they are matched on important variables such as age, sex, personality. In a matched pairs design there are two equal groups of participants, each participant is then matched with a similar participants in the other group, Both groups then take part in different conditions of the IV as with the independent measures design.

Some studies use control groups. These groups have not experienced any of the manipulations of the IV that an experimental group might have. In this case one participant would be randomly assigned to the experimental group and the participant they were matched with would go to the control group. This allows the reasearcher to make a direct comparision between them. 

Strengths-No order effects because there are different people in each condition, participant variables are minimised because important differences are minimised through matching. 

Weaknesses-Need twice as many people compared to the repeated measures design, there are issues with practicalities such as it is time-consuming and difficult to find participants who match. 

Aim: An aim is a statement of a study's purpose, research should state its aim beforehand so that it is clear what the study intends to investigate.

Hypotheses:Although the aim states the purpose of a study, it is not usually precise enough to test. What is needed are clear statements of what is actually being tested this is the hypothesis.

Research Hypothesis - The research hypothesis is proposed at the beginning of a piece of research and is often generated from a theory.

Null Hypothesis - The null hypothesis is what you are going to assume is true during the study. Any data you collect will either back this assumption up or it won't. If the data does not support your null hypothesis then you rejct it and accept your alternative hypothesis. Very often, the null hypothesis is a prediciton that there will be no relationship between key variables in a study - and any correlation is due to chance. No relationship or difference between two sets of data.

Experimental/Alternative Hypothesis - If data forces you to reject the null hypothesis then you accept this type of hypothesis instead. There is a relationship between the two variables being studied (one variable has an effect on the other).

One-tailed Hypothesis- A one-tailed directional hypothesis predects the nature of the effect of the IV on the DV. These hypotheses are often used when previous research findings suggest which way the results will go.

Two-tailed Hypothesis- A two-tailed non-directional hypothesis predicts that the IV will have an effect of the DV, but the direction of the effect is not specified.These hypotheses can be used when there is little previous research in the are under investigation, or when previous research findings are mixed or inconclusive.