Research methods in Psychology

Research methods in Psychology

You will need to know everything on this page and be able to recall and apply the information here to all the studies.

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Laboratory Experiments

These take place in either a lab or in a controlled environment setting, which is unnatural for the participants. They attempt to control all variables except the IV.
By changing one variable (the IV) while measuring another (the DV) 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 IV is the only thing that is changed then a cause and effect relationship can be found between the IV ad the DV.

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Field Experiments

Sometimes it is possible to carry out experiments in a more natural setting, i.e. in ‘the field ’. As with the laboratory experiment, the independent variable is still deliberately manipulated by the researcher.
However it is not possible to have such tight control over variables in the field, but it does have the advantage of being far less artificial than the laboratory.

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Quasi Experiments

Quasi experiments may take place in the lab or field. Like other experiments they have an IV but in this type of experiment the experimenter does not directly manipulate the IV.
Some IVs are not open to manipulation as some conditions are pre-decided by fixed characteristics. E.g. comparing men and women’s driving skills, they cannot be randomly allocated to be male or female. The IV is naturally occurring. Other examples of pre-existing variables might be age, IQ, position in the family and social background.

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Formulating research questions - aims and hypotheses

Aim – a general statement about the purpose of an investigation.
Experimental Hypothesis – a precise, testable statement about the expected outcome of the experiment.
A hypothesis must be:

    A clear statement
    A prediction
    Testable (all variables should be operationalised)
    Formulated at the beginning of the research process

Null Hypothesis - written alongside the main hypothesis in order to make the scientific prediction complete. A null hypothesis predicts that any differences or similarities between the sets of results in an experiment are due to chance alone.

An example of a null hypothesis:
Tomato plants show no difference in growth rates when planted in compost rather than soil.

Note that the variables are clearly operationalised (it is clear how we would measure them), a prediction is made and it could be easily tested.

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Sampling Methods

Definitions

    A sample is the group of people who take part in the investigation. The people who take part are referred to as “participants”.
    Sampling is the process of selecting participants from the population.
    The target population is the total group of individuals from which the sample might be drawn.
    Generalisability refers to the extent to which we can apply the findings of our research to the target population we are interested in.
Once we have our aim and hypothesis, we have to decide who we want to do our research on. Research will often only be relevant to certain groups of people (all females, or all teenagers, or people suffering from depression etc). We call the group of people we want to apply our research to the target population.

Ideally we would do out research of all of the members of the target population, but this is almost never possible due to the constraints of time, cost and logistics. Instead, psychologists take a selection of the target population called a sample.

Psychologists try not to use a biased sample -that is a sample that is not representative. Representative here means including members of each type of person in that population, usually in the correct proportion.

It is difficult to get a representative sample because there are problems in obtaining participants, even if you can get access to relevant people, you still have to choose who will be involved.

Four Sampling methods.

Opportunity sampling.

Is not really a true method of sampling because it means taking whoever is available. Researchers take whoever they can find to take part. The way participants are selected is not systematic or structured. Psychology students tend to use opportunity sampling as they have limited access to participants

Strengths.

It tends to be more ethical because the researcher can judge if the participant is likely to be upset by the study or is too busy to take part.

The researcher has more control over who is asked, so finding participants should be quick and efficient and costs less money, for example the researcher may use friends, family or colleagues.

Weaknesses.

The people who are available at the time may well not be representative of the target population as a whole, so the sample will be biased.

The researcher may have more control over who is chosen and choose certain people, leading to a biased sample.

Stratified sampling.

Stratified sampling involves classifying the population into categories and then choosing a sample which consists of participants from each category in the same proportions as they are in the population. For example, if you wanted to carry out a stratified sample of students from a sixth form college you might decide that important variables are sex, 1st or 2nd years, age, have a part-time job and so on. You could then identify how many participants there are in each of these categories and choose the same proportion of participants in these categories for your study.

Strengths.

Stratified sampling is an efficient way of ensuring that there is representation from each group. Random sampling would probably still provide some participants from each group, but the researcher cannot be sure of this and may therefore need a larger sample. Stratified sampling limits the numbers needed to obtain representation from each group.

Weaknesses.

However, stratified sampling can be very time consuming as the categories have to be identified and calculated. As with random sampling, if you do not have details of all the people in your target population you would struggle to conduct a stratified sample.

Random sampling.

Here every member of the target population has an equal chance of being selected. Everyone in the target population is available for selection each time a participant is picked out.

It could be done by drawing straws or pulling names from a hat. One popular method is to give each member of the target population a number and then to take numbers from a random number table.

Strengths.

There is no bias in the way that the participants are selected, everyone has an equal chance of being selected. Therefore the sample is likely to be representative of the target population.

Weaknesses.

Random sampling can be very time consuming and is often impossible to carry out, particularly when you have a large target population, of say all students. For example if you do not have the names of all the people in your target population you would struggle to conduct a random sample.

Other issues people may not be available on the day, or they simply do not wish to take part in the study so there could be bias.

Systematic Sampling.

Made up of participants chosen mathematically. This is done by taking every nth person in the sampling frame.

Strengths.

It avoids bias as, once the researcher has decided what number they are going to use for selection, they have no control over who is selected.

The law of probability says that the researcher will normally get a representative sample. For example, what is the chance that every fifth person is a male if the list of people is 50% male and 50% female?

Fairly simple procedure

Weaknesses.

There is a chance, although unlikely, of a ‘freak’ sample which would not be representative.

It is not as objective as random sampling, because the researcher may decide on how people are listed before selection and on what number to use for the ‘system’