If a researcher wanted to investigate differences in memory between 2, 10, and 16

Research methods in Psychology

Although you might not think about it immediately, how you conduct psychological research is at least as important (in fact more important) than subject of the research you conduct. Here is a quick introduction to some of the key ideas in psychological research.

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:

There will be no difference in the reaction time taken to press a button upon seeing a green square on the computer screen (measured in milliseconds) before consumption of three units of alcohol and after consumption of three units of alcohol.  Any difference in results is due to chance alone.

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.

If a researcher wanted to investigate differences in memory between 2, 10, and 16

Creating aims and hypotheses allows Psychology to follow the SCIENTIFIC METHOD. This is one of the key things that differentiates Psychology from common sense explanations of behaviour (see the 'Psychology vs common sense' section below)

  • Variable: any factor that can change or vary
  • Independent variable : the variable that is manipulated by the experimenter (the variable that the experimenter is interested in as to whether or not it has an effect or cause change in the research participants behaviour)
  • Dependant variable: the dependant variable is what changes as a result of manipulating the IV, it is the result
  • A hypothesis should show how the IV will affect the DV.

Extraneous and confounding variables

An extraneous variable is a variable other than the IV that might affect the DV if it is not controlled

Extraneous variables must be carefully and systematically controlled so they don’t vary across any of the experimental conditions or, indeed, between participants.  When designing an experiment, researchers should consider three main areas where extraneous variables may arise:-

  • Participant variables: participants’ age, intelligence, personality and so on should be controlled
  • Situational variables:  the experimental setting and surrounding environment must be controlled.  This may even include the temperature or noise effects.
  • Experimenter variables:  the personality, appearance and conduct of the researcher.  Any change in these across conditions might affect the results.  For example, would a female experimenter have recorded lower levels of obedience in Milgram’s obedience to authority studies?


If extraneous variables are not controlled, then can become... confounding variables.


If a researcher wanted to investigate differences in memory between 2, 10, and 16

If a researcher wanted to investigate differences in memory between 2, 10, and 16

Confounding Variables - variables that do actually have an effect on the DV. A confounding variable could be an extraneous variable that has not been controlled. 

If the IV is the only thing that is changed then it must be responsible for any change in the DV.

(N.B. - if we fail to identify & control for an extraneous variable, and we only notice afterwards that it has affected our results, then it becomes known as a confounding variable. 

EXAMPLE:
  if researchers wished to investigate the effect of background music (condition 1) or silence (condition2) on homework performance using two classes, they’d have to control a number of possible extraneous variables.  These might include age, homework difficulty and so on.  If these were all successfully controlled, then the results would probably be worthwhile.  However, if the researchers discovered that those in condition 1 were considerably brighter than those in condition 2, and then intelligence would be acting as a confounding variable.  The researcher could no longer be sure whether any differences in homework performance were due to the presence of the music or due to intelligence levels.  Results would be confounded and worthless.


Populations and sampling

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.

If a researcher wanted to investigate differences in memory between 2, 10, and 16

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.



Identify the target populations.

Identify the target population in the following

1)    Research into the effectiveness of the use of cognitive therapy for people scared of heights.

2)   An investigation into play habits in one year old infants

3)   A study into whether cat owners believe advertising claims


Sampling methods and their evaluations...

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.

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.

If a researcher wanted to investigate differences in memory between 2, 10, and 16

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.  

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


 Weakness

  • 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’ 

Types of experiment in Psychology

Laboratory Experiments

If a researcher wanted to investigate differences in memory between 2, 10, and 16

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.



Field Experiments

If a researcher wanted to investigate differences in memory between 2, 10, and 16
Field experiments take place in 'the field'... not in a field

Sometimes it is possible to carry out experiments in a more natural setting, i.e. in ‘the field ’.  A famous example of this is the series of studies carried out by Piliavin et al (1969) in which they arranged for a person to collapse on an underground train and waited to see how long it was before the person was helped.  

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.



Quasi Experiments

If a researcher wanted to investigate differences in memory between 2, 10, and 16
Comparing men and women's performance on this task would be a quasi experiment as we cannot choose who is in each group in the experiment.

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.




Think like a Psychologist - evaluating types of experiment

If a researcher wanted to investigate differences in memory between 2, 10, and 16

Evaluating the different types of experiment is very straightforward, as soon as you understand that THE ADVANTAGES OF ONE DESIGN ARE THE DISADVANTAGES OF THE OTHER. If you understand this then you actually don't have to revise as much information, as you can reuse the same ideas in a number of different places!

For example, a lab experiment will try to tightly control variables in an artificial setting. This means that it is less likely that any confounding variables will affect the results (so cause and effect relationships can be discovered between the IV and DV), but is also means that the situation will have very low ecological validity. This means that the situation does not resemble real life, so there is a danger that the behaviour produced by participants will not be realistic as a result. If this is the case, then we cannot generalise the results of the experiment to real life behaviour (in effect the results of our experiment are worthless as they don't tell us anything about the real world). 

A field experiment will be the opposite. It will have

high ecological validity as it occurs in a natural setting, but the poor control of extraneous variables makes it much more likely that they could affect the DV and confound the results. 

A quasi experiment has the obvious drawback that the researcher is

not properly in control of the variables involved, so again there is the possibility for the results to be confounded. 

Want another example of a place where you can save yourself work by just understanding that the strengths and weaknesses of different ideas will be related...? Look at the evaluations of the experimental designs section below, or of the sampling methods above! The same patterns occur...

Experimental designs

As well as the type of experiment that you conduct, there are a number of ways that experiments can be designed. What we mean by this is the way that the experiment puts people into groups. The three main examples of this are below:

Independent groups (or 'independent measures')

If a researcher wanted to investigate differences in memory between 2, 10, and 16
Different people in each condition

Two independent (separate) groups of participants.

E.G. one group studies in silence and does a memory task and the other group studies with music and then does the same memory task


Advantages:
Eliminates order effects

Disadvantages:
Individual differences could confound the results.  What if you had the world memory champion in one group! Solution: use very large groups.  If you had 1,000 in each group, just by chance the groups might contain broadly similar people.


Repeated measures

If a researcher wanted to investigate differences in memory between 2, 10, and 16
The same people do each condition

Each participant takes part in both conditions of the experiment.  E.G. each participant learns in silence and with music and does the memory task after each.

Advantages:
The same people in each group, so no need to control for individual differences like age etc.  Because of this you don’t have to use as many participants so it is cheaper and faster


Disadvantages:
Order effects: people may get better or worse because of practice or fatigue (possible confounding variables).  Solution is to counterbalance the order in which they do the task. ½ of the group eat have silence first and music second, the other ½ do music first and silence second.


Matched pairs

If a researcher wanted to investigate differences in memory between 2, 10, and 16
Here participants have been matched for age (e.g. as age might affect memory, we make sure that our two groups contain similar ages). In a memory study, we might also match for IQ and so on...

Like an independent groups design but you carefully match members of each group. If you have a 23yr old rugby player in one group you need one in the other group.  If you have a female with an IQ of 150 you need one in the other group and so on...


Advantages:
Matching is a control for individual differences.  Also there are no order effects.

Disadvantages:
Matching is extremely difficult.  Even if you use identical twins they may still have different abilities and may have had different experiences.  It you don’t use twins (more likely) you can never be sure to match everything about the pairs of people you use.


Non-experimental methods

Experiments are not the only way that psychologists can investigate behaviour. There are many other non-experimental methods which are widely used in the subject, such as correlation studies, content analyses, observational studies, case studies, questionnaires and interviews. Bandura et al (1961), Piliavin et al (1969) and Rosenhan (1973) are all good examples of observational studies from the CIE course.

Observational studies

If a researcher wanted to investigate differences in memory between 2, 10, and 16

One of the simplest research methods, this simply involves observing and recording the behaviour that occurs. However, in order to make the process more scientific, a number of checks are often put in place...

INTER-OBSERVER RELIABILITY: the extent to which there is agreement between two or more observers involved in observations of behaviour. A good study should have at least 80% agreement between observers.

For a recap on the meaning of the term 'reliability' in Psychology, see here.

Observation studies can be participant observations, where the researcher joins the group being studied, or non-participant observations, where the researcher stays apart and observes from a distance.


Correlations

If a researcher wanted to investigate differences in memory between 2, 10, and 16

Sometimes psychologists are interested in whether there is a relationship between two factors or variables, e.g. is there a relationship between how extrovert you are and how good at maths you are. In a case like this we might use a correlation.

In a correlation study the experimenter does not make any attempt to manipulate variables (so there is no IV or DV), he simply measures two things (e.g. maths scores and extroversion) and then compares them for a relationship (e.g. does it seem to be that as maths scores increase, so do extroversion scores).

The difference between an experiment and a correlation:

Experiment

  • Shows cause and effect
  • Extraneous variables are controlled


Correlation

  • Does not show cause and effect
  • No control of extraneous variables


Case studies

If a researcher wanted to investigate differences in memory between 2, 10, and 16
The case study of Phineas Gage is one of the most famous in Psychology

A case study involves a detailed investigation of a single individual or small group of individuals. Example of the type of research that would lend itself to a case study are investigations into the effects of a stroke on later personality and behaviour, studying the effects of severe deprivation and the possibilities for recovery and so on.

Case studies often involve the use of interviews with the individual and family, friends, medical professionals etc. They may continue for many years and for this reason are
often expensive and time consuming. However, they may lead to the way to future research, as they will collect extremely in-depth data.

Freud's case study of Little Hans and Thigpen and Cleckley's report of 'The three faces of Eve' are both examples from the CIE specification of a case study.



Applying your understanding to a real study - The Marshmallow Test

First watch the video to the left, then open the document below. In the summary of the experiment table of the document, fill in the gaps in the description of the study with the appropriate answers, based on what we’ve done in the last few lessons.

If a researcher wanted to investigate differences in memory between 2, 10, and 16


TIPS!
When evaluating an experiment, think of the positives and negatives of the ways that the experiment is designed. For example, what are the pros and cons of the sampling method used? What about the experimental design? All of these problems will affect the study as well.

Want more practice...? Firefly is your place

Log into the JIS Firefly page and find the 'Research methods' section in the 'Psychology' pages ('Humanities' section) for lots more resources and practice opportunities. 

At what point did researchers begin to consider the implications of attachment styles in adulthood?

Although Bowlby was primarily focused on understanding the nature of the infant-caregiver relationship, he believed that attachment characterized human experience from "the cradle to the grave." It was not until the mid-1980's, however, that researchers began to take seriously the possibility that attachment processes ...

Which if the following is a major problem with arriving at a conclusive scientific answer to the nature nurture debate?

Which of the following is a major problem with arriving at a conclusive scientific answer to the nature-nurture debate? Humans cannot easily be randomly assigned to different genetic and environmental conditions.

Which of the following best describes the purpose of institutional review boards?

The purpose of IRB review is to assure, both in advance and by periodic review, that appropriate steps are taken to protect the rights and welfare of humans participating as subjects in the research.