Research Methods

Aims & Hypotheses

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The aim states the purpose of the investigation and is driven by a theory. The aim is a broad starting point that gets narrowed down into the hypothesis.

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A hypothesis (plural hypotheses) is a precise, testable statement of what the researchers predict will be the outcome of the study. Hypotheses must always include the DV and both levels of IV.

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An experimental hypothesis predicts what change(s) will take place in the dependent variable when the independent variable is manipulated.

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The null hypothesis states that there is no relationship between the two variables being studied e.g. There will be no difference in the number of words recall between the music and no music condition.

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A directional hypothesis (one-tailed) that states the direction of the difference or relationship (negative or positive correlation). This is used when previous research findings are available to help make the prediction e.g. Ppts in the no music condition will recall less words compared to the music condition.

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A non-directional (two tailed) states that there will be a difference between the two groups/conditions but it does not state where the difference will occur. This is used when there are no previous research findings available to help make the prediction e.g. There will be a difference in the number of words recall between the music and no music condition.

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Variables and controls

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The IV is the variable that is manipulated and changed between the conditions.

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The DV is the data that is collected.

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Operationalisation is a clear identification/definition of the observable actions/behaviours to be recorded which enables the behaviour under review to be measured objectively.

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A control condition does not involve exposure to the treatment or manipulation of the IV.

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An experimental condition does involve exposure to the treatment or manipulation of the IV.

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Extraneous variables

Situational extraneous variables are aspects of the environment might affect the participant's behavior e.g. noise, temperature, lighting, time of day

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Participant extraneous variables are any characteristic of a participant's that could affect the DV when it is not intended to e.g. IQ, mood, age, gender

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Demand characteristics are when participants detect cues from the environment which makes them guess the aim of the study and they change their behaviour as a result.

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Investigator effects are where a researcher (consciously or unconsciously) acts in a way to support their prediction and therefore affects the DV.

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Order effects are when when participants' responses in the are affected by the order of conditions to which they were exposed i.e. fatigue effects or practice effects.

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Participant reactivity is when participants alter their behaviour because they know they are part of a study and this can threaten the internal validity of the results.

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Extraneous variables are variables other than the IV which could affect the DV and should be controlled.

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Confounding variables are variables which have affected the DV and have threatened the validity of the results.

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Controlling variables

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Random allocation is when each participant has an equal chance of being allocated to either condition. All experiments should use random allocation apart from quasi-experiments which cannot.

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Counterbalancing is a way to control for order effects. Half of the participants do condition A then B and the other half do B then A. It means that any order effects will be spread out equally across both conditions.

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Randomisation is used in the presentation of trials in an experiment to enable to stimuli to be presented in a random manner so the order of presentation does not have any effect on the DV e.g. words presented in a list.

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Standardisation is the process in which procedures used in research are kept exactly the same apart for the IV.

 

Single blind study is when the participants are deliberately kept ignorant of either the group to which they have been assigned or key information in order to reduce demand characteristics.

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Double blind study is when the participants and the researcher are deliberately kept ignorant of either the group to which the participants belong or key information in order to reduce demand characteristics and investigator effects.

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Type of experiments

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Lab experiments

A laboratory experiment is an experiment conducted under highly controlled conditions and the IV is deliberately manipulated by the researcher. Participants will typically know they are in the experiment.

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Strengths

• High control – high internal validity

• Standardised procedure – reliable methodology

 

Limitations

• Low ecological validity

• Low mundane realism

• Chances of demand characteristics

 

Field experiments

A field experiment is an experiment conducted in a natural environment but the IV is deliberately manipulated by the researcher. Participants typically will not know they are in the experiment.

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Strengths

• High ecological validity

• High mundane realism

• Less chance of demand characteristics

 

Limitations

• Extraneous variables – questionable internal validity

• Hard to replicate to check reliability of the findings

 

Natural experiments

A natural experiment is an experiment conducted in a natural environment and the IV is naturally occurring e.g. introduction of the internet to a remote community or a natural disaster

Strengths

• High ecological validity

• Allows research to be carried out that would not normally be ethically viable

 

Limitations

• Confounding variables do not allow for causality to be established

• Cannot be replicated to check reliability of the findings

 

Quasi experiments

A quasi experiment is an experiment conducted in a lab or natural environment. The IV is a naturally occurring characteristic of the participant e.g. autism, OCD etc. Random allocation is not possible and therefore it is not a ‘true experiment’.

 

See the previous types of experiments for strengths and limitation depending on where the study is carried out.

 

Experimental design

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Independent groups design is when participants only take part in one condition.  

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Strengths

• Less chance of demand characteristics affecting the DV

• Order effects are eliminated

 

Limitations

• Participant EV are a threat to internal validity of the results

• More costly and time consuming as more participants are needed

 

Repeated measures design is when participants take part in both conditions.

 

Strengths

• Participant extraneous variables are reduced

• Less costly and time consuming as fewer participants are needed

 

Limitations

• Increased chance of demand characteristics affecting the DV

• Order effects are a threat to internal validity

 

Matched pairs design is when participants only take part in one condition but they are matched on a key characteristic with another participant. Random allocation will be used to allocate one of the pairs and the other participant will go into the other condition.

 

Strengths

• Participant extraneous variables are controlled for

• Less costly and time consuming as fewer participants are needed compared to independent groups design

• Order effects are eliminated

• Demand characteristics are reduced

 

Limitations

• Participants can never truly be matched – there will always be some differences

• It can be time consuming to match participants

 

Sampling methods

The target population is the group of people the researcher wants to study. They cannot study everyone so they have to select a sample.

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A sample is a small group of people who represent the target population and who are studied.

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It is important the sample is representative of the target population.

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Random sampling

This is a sampling technique in which every member of the target population has an equal chance of being chosen.

 

How to do it 

1 You need a sampling frame which is a complete list of all members of the target population is obtained

2 All of the names on the list are assigned a number

3 The sample is selected randomly for example, a computer-based randomiser or picking names from a hat

 

Advantages

• There is no bias with this method. Every person in the target population has an equal chance of being selected. Therefore the sample is more likely to be (but not definitely) representative.

 

Disadvantages

• Impractical: It takes more time and effort than other sampling methods because you need to obtain a list of all the members of the target population, identify the sample and then contact the people identified and ask if they will take part and not all members may wish to take part.

• Not completely representative: unbiased selection does not guarantee an unbiased sample, for example, the random selection may only end up generating an all female sample, making the sample unrepresentative and therefore not generalisable.

 

Opportunity sampling

A technique that involves recruiting anyone who happens to be available at the time of your study.

 

How to do it

The researcher will go somewhere where they are likely to find their target population and ask people to take part.

 

Advantages

• Simple, quick and easy and cheap as you are just using the first participants that you find.

• Useful for naturalistic experiments as the researcher has no control over who is being studied.

 

Disadvantages

• Unrepresentative: the sample is likely to be biased by excluding certain types of participants which means that we cannot confidently generalise the findings e.g. an opportunity sample collected in town during the day on a week day would not include those who are at work or college

 

Volunteer sampling

This is when people actively volunteer to be in a study by responding to a request which has been advertised by the researcher (they are self-selecting). The researcher may then select only those who are suitable for the study.

 

How to do it

Participants self-select by responding to an advert.

 

Advantages

• Most convenient and economical way method to gather a wide range of people with particular requirements for a study compared to a random sample as they have already agreed to participate.

• Can reach a wide audience, especially online.

 

Disadvantages

• Sampling bias - particular people (with higher levels of motivation and who have more time) are more likely to volunteer so may be harder to generalise. What is it that has made them decide to take part? This may lead to a bias as they may all display similar characteristics.

 

Systematic sampling

 

Systematic sampling involves selecting names from the sampling frame at regular intervals. For example, selecting every fifth name in a sampling frame.  

 

How to do it

• A sampling frame is produced, which is a list of people in the target population organised into, for example, alphabetical order.

• A sampling system is nominated (e.g every 3rd, 6th or 8th person etc).

• The researcher then works through the sampling frame until the sample is complete.

 

Advantages

• Simple to conduct (still need a sampling frame) 

• The population will be evenly sampled using an objective system, therefore reduces researcher bias increasing the chances of a representative sample.

 

Disadvantages

• Not truly unbiased/random because not all people have an equal chance of being selected therefore representativeness is not guaranteed.

 

Stratified sampling

For this method, participants are selected from different subgroups (strata) in the target population in proportion to the subgroup’s frequency in the population.

 

How to do it

• If a researcher wants to sample different age groups in a school, they first of all have to identify how many students are in each strata e.g. students aged 10-12, 13-15, 16-18

• They then need to work out the % of each strata that makes up the target population. If there are 1000 students in the school and 300 of them are 10-12 years, 500 of them are 13-15 years and 200 are 16-18 the frequency of the subgroups is 30%, 50% and 20%.

• The researcher then uses random sampling to select the sample. If the researcher wishes to have a sample of 50 participants, then 30% of the 50 should 10-12, 50% of the 50 should be 13-15 years and 20% should be 16-18 years which are selected at random from each strata.

 

Advantage

• Most representative than all sampling methods because there is an equal representation of subgroup, making generalisations of findings possible.

 

Disadvantage

• Knowledge of population characteristics required: stratified samples require a detailed knowledge of the population characteristics, which may not be available.

• Time consuming: dividing the population into stratums and then randomly selecting from each can take time and more admin time

 

Ethics

Remember the saying ‘Can Do Can’t Do With Participants’ to help you remember the ethical guidelines.

 

Consent: This means revealing the true aims of the study, or at least letting the participant know what is actually going to happen.

Participants must be aware of what they are needed to do as part of the study in order to give valid consent.

If the study involves children parental consent must be obtained.

 

Deception: This means deliberately misleading or with holding information. Deceiving participants must be kept to a minimum. Withholding details of the research to avoid influencing behaviour is acceptable, deliberately providing false information is not acceptable. If telling the truth will not have an effect on results participants must be informed.

 

Confidentiality: The communication of personal information from one person to another and the trust this will be protected. Psychologists need to be sure the information they publish will not allow their participants to be identified (keeping their identity secret may not be enough).

 

Debrief: If consent cannot be obtained (such as in a field experiment) participants must be fully debriefed afterwards. This involves telling the participant about the experiment and then giving them the option of withdrawing their information if they wish

 

Withdraw: Even after giving consent participants still have the right to leave the experiment at any point in time. The p’s must be made aware of this when they sign the consent form. 

 

Protection from harm: Participants should be no worse off when they leave an experiment as to when they arrived. Risk is considered acceptable if it is no greater than what would be experienced in everyday life.

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Validity and Reliability

Validity

Validity refers to the extent to which something is measuring what it is claiming to measure.

 

Internal validity refers to the extent to which a study establishes a cause-and-effect relationship between the IV and the DV.

 

External validity

Ecological validity refers to whether the data is generalisable to the real world.

Population validity refers to whether the data is generalisable to other groups of people.

Temporal validity refers to whether the data is generalisable to other time periods.

 

Test validities

Construct validity: This refers to the degree to which a test measures what it claims, or purports, to be measuring e.g. How effectively does a mood self-assessment for depression really measure the construct of ‘depression’? How effectively does an IQ test really measure ‘intelligence’?

 

Concurrent validity: This asks whether a measure is in agreement with a pre-existing measure that is validated to test for the same (or a very similar) concept. This is gauged by correlating measures against each other. For example, does a new test measuring intelligence, agree with an existing measure of intelligence e.g. Stanford-Binet Test?

 

Predictive validity: This is the degree to which a test accurately predicts a criterion that will occur in the future. For example, a diagnostic test of schizophrenia has low predictive validity as being diagnosed with sz can lead to very different outcomes. Some people continue to live ‘normal’ lives whilst others struggle with homelessness and drug abuse.

 

Face validity: A superficial form of validity where you apply a superficial and subjective assessment of whether or not your study or test measures what it is supposed to measure.

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Reliability

Reliability refers to the extent to which something is consistent.

 

Test-retest reliability: This measures test consistency; the reliability of a test measured over time. i.e. if a person completed the same test twice at different times, are the scores are the same?

If the results on the two tests achieve a correlation co-efficient of 0.8 or above, we can assume the test is reliable.

 

Inter rater/observer reliability is the degree of agreement among raters.

If there is high correlation (0.8+) between the observers/ raters, the measure is reliable.

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Observations

A researcher will simply observe behaviour of a sample and look for patterns. Like all non-experimental methods, in an observation we cannot draw cause and effect relationships.

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Observations are used in psychological research in one of two ways, a method or a technique.

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Observations can be understood about by considering its four main features:

• The settings: Naturalistic v controlled

• The data: Structured v unstructured

• The participants: Overt v covert

• The observers: Participant v nonparticipant

 

Naturalistic observations

This refers to the observation of behaviour in its natural setting. The researcher makes no attempt to influence the behaviour of those being observed. It is often done where it would be unethical to carry out a lab experiment.

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Strength

• High levels of ecological validity as carried out in a natural setting

• P’s are less likely to be affected by demand characteristics as they are unaware they are being studied

 

Limitations

• Little control over EVs - hard to establish causality

• Replication is often not possible - cannot check reliability of the findings

 

Controlled observations

This refers to an observation taking place in a controlled setting, usually behind a one way mirror so they cannot be seen. 

 

Strength

• There is less risk of extraneous variables affecting the behaviour as it is in a controlled environment

 

Limitation

• The setting is artificial and therefore the results may lack ecological validity

 

Structured observations

An observation where the researcher creates a behavioural checklist before the observation in order to code the behaviour. Behaviour can be sampled using time or event sampling.

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Researchers will use a standardised behaviour checklist to record the frequency of those behaviours (collecting quantitative data). The target behaviour is split up into a set of behavioural categories (behaviour checklist) e.g. aggression may be categorised as punching, kicking, shouting etc.

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The behaviours should:

• Be observable (record explicit actions)

• Have no need for inferences to be made

• Cover all possible components behaviours

• Be mutually exclusive/ not overlap (not having to mark two categories at the same time)

 

A pilot study is a small scale study carried out before the actual research. It allows the researchers to practise using the behaviour checklist/ observation schedule. 

 

It is not always possible to watch and record every behaviour so researchers use a systematic method of sampling it. 

 

Event sampling

Counting each time a particular behaviour is observed.

Strength: Useful when the target behaviour or event happens infrequently and could be missed if time sampling was used. 

Limitation: However, if the situation is too busy and there is lots of the target behaviour occuring the researcher could not record it all

 

Time sampling

Recording behaviour at timed intervals

 Strength: The observer has time to record what they have seen.

Limitation: Some behaviours will be missed outside the intervals - observations may not be representative.

 

Strengths of structured observations

• The behavioural checklist (coding system) allows objective quantifiable data to be collected which can be statistically analysed

• Allows for more than one observer (due to checklist) which can increase the reliability (inter-observer reliability)

 

Limitations of structured observations

• The pre-existing behavioural categories can be restrictive and does not always explain why the behaviour is happening

 

Unstructured observations

The observer note down all the behaviours they can see in a qualitative form over a period of time. No behavioural checklist is used.

 

Strengths

• They can generate in-depth, rich qualitative data that can help explain why the behaviour has occurred

• Researchers are not limited by prior theoretically expectations

 

Limitations

• The observer can get drawn to eye catching behaviours that may not be representative of all behaviours occurring

• More subjective and less comparable across researchers

 

Overt observations

Participants are aware that their behaviour is being studied, the observer is obvious.

 

Strength

• It will better fulfil ethical guidelines (compared to covert)

 

Limitations

• Participants know they are being observed and therefore they may change their behaviour (participant reactivity)

 

Covert observations

Participants are unaware that their behaviour is being studied – the observed is covered.

 

Strength

• P’s do not know they are being observed and therefore their behaviour is more likely to be natural (higher validity)

 

Limitations

• It can break many ethical guidelines as deception is used it may cause the p’s some psychological harm

 

Participant observations

The observer becomes involved in the participant group and may not be known to other ppts.

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Strength

• Being part of the group can allow the researcher to get a deep understanding of the behaviours of the group (increasing validity).

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Limitations

• The presence of the researcher might influence the behaviour of the group.

• The researcher may lose objectivity as they are part of the group.

 

Non-participant observations

The observer is separate from the participant group that are being observed.

 

Strength

• Researchers observations are likely to be more objective as they are not influenced by the group

 

Limitations

• It is harder to produce qualitative data to understand the reasons for the behaviour

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