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Test your knowledge and understanding of the different types of data with this A Level Psychology revision quiz.

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Research Methods - Demand Characteristics, Investigator Effects and Pilot Studies

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Demand Characteristics, Investigator Effects and Pilot Studies are the topics for this A Level Psychology revision quiz in our series on Research Methods.

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Research Methods - Descriptive Statistics

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Descriptive Statistics are the focus on this A Level Psychology revision quiz which forms part of our series on research methods.

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Variables are the subject of this A Level Psychology revision quiz in our series of quizzes on research methods.

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This revision quiz on research methods for A Level Psychology explores the topic of sampling.

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This A Level Psychology revision quiz in our series on research methods looks at the Experimental Method.

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The A Level Psychology revision quiz is on Research Ethics.

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Invasion of Personal Space Psychology Experiment

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Peer Review and false data newspaper article

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Peer Review and false data newspaper article

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Economic implications of psychological theory and research

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Economic implications of psychological theory and research

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Correlational Analysis

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Evaluation of Observational Techniques from Tutor2u

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Evaluation of Observational Techniques from Tutor2u

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Here is a summary of some of the key strengths and limitations of a variety of observational techniques.

Natural observations

STRENGTHSHigh ecological validity as the researcher records naturally occurring behaviour in a natural environment, without any outside interference from the researcher. LIMITATIONS Cannot be replicated to check reliability, as the researcher is not in control of variables.

Controlled observations

STRENGTHS Low ecological validity as the researcher records behaviours in an artificial (manipulated) environment, with potential outside interference from the researcher.
LIMITATIONS
Can be replicated to check reliability, as the researcher is in control of variables and therefore can repeat the method as they wish

Covert observations

STRENGTHSInvestigator effects are unlikely meaning that participants' behaviour will be genuine. LIMITATIONS Less ethical as participants are not aware they are taking part and cannot give fully informed consent

Overt observations

STRENGTHSIt is possible to inform participants in advance and obtain informed consent. LIMITATIONS Behaviour can be distorted through investigator effects in which the participant changes their behaviour through social desirability bias

Participant observation

The researcher can obtain in-depth data as they are in close proximity to the participants and so are unlikely to overlook or miss any behaviours.
LIMITATIONS
The researchers' presence might influence the participants' behaviour due to evaluation apprehension,

Non-participant observation
STRENGTHS
Investigator effects and evaluation apprehension are less likely as the researcher is not visible.

LIMITATIONS
Due to a lack of proximity the researcher might overlook or miss behaviours of interest.

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Observational Techniques - Strengths and Limitations

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Here is a summary of some of the key strengths and limitations of a variety of observational techniques.

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Observational techniques involve observing actual behaviours which are subsequently scored.

A key challenge that is encountered by the researcher though is deciding what to look for and how to decide what constitutes a particular behaviour.

The behaviours that the researcher is interested in need to be clearly defined (operationalised) so that the observer knows what to look out for and measure; eventually these can be counted up to produce a score.

There are many types of observations, such as naturalistic and controlled observation; covert and overt observation; participant and non-participant which all have their strengths and weaknesses.

Psychologists attempt to overcome the ambiguity of observing their chosen behaviours by clearly defining (operationalising) these, which usually involves producing a behaviour checklist or behaviour categories, so that the researcher knows exactly what to look out for.

For example, if a researcher was interested in measuring aggression through an observation the checklist might include predetermined behaviours such as punching, kicking, pushing and biting. Each time a participant displayed any of the listed behaviours this would be counted producing a running tally for each behaviour identified.

Time vs Event Sampling
There are occasions in which it might be useful for the researcher to gather an insight into whether there are behavioural trends that occur over particular time periods.

Under such circumstances researchers can use time sampling in which behaviours are noted within prescribed intervals.

For instance a researcher might tally co-operative classroom behaviours (operationalised as instances of students putting their hand up to contribute and attempting to help their peers) over 5 minute intervals during a lesson. Each 5 minute interval could then be compared to identify when most co-operative behaviours occur.

In contrast event sampling would simply tally all co-operative behaviour over the full 1 hour lesson to gather an overall impression of the amount of co-operative behaviour

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Observational techniques involve observing actual behaviours which are subsequently scored.

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Experimental Design with The Simpsons

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BPS Ethical Guidelines

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Sampling with The Simpsons

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Sampling Exam Questions

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Experimental Design Exam Questions

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Reliability is a measure of whether something stays the same, i.e. is consistent. The results of psychological investigations are said to be reliable if they are similar each time they are carried out using the same design, procedures and measurements.

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Ethics are a key part of psychological investigation, as researchers have the responsibility to ensure that their practice is morally correct; ill practice could lead to banning from further practice as a psychologist.

There are a number of important issues that researchers should be mindful of when undertaking investigations, with regards to the selection and subsequent treatment of their participants:

Confidentiality

Participants should remain anonymous so that data cannot be identified as theirs (e.g. their names should be withheld when data is reported).

Informed consent

Participants must be briefed on objectives of the investigation and what will be required of them should they take part. In turn they must accept these conditions to proceed, and be put under no pressure to do so.

Deception

Generally, participants should not be misled during an investigation. However, sometimes participants need to be unaware of the true aims of an investigation - or even that they are participating in a study - to yield results that are considered valid (i.e. the data is a true reflection of what was supposed to be measured). This emphasises the need for participants to be debriefed at end of the study.

Debriefing

When a study ends, participants should be told the true motivations behind the investigation, and given the opportunity to clarify any misunderstandings with the researchers. It is also essential to ensure that the participants leave having not suffered long-lasting negative physical or mental effects, particularly where deception (see above) was utilised for the purposes of the experiment. Having checked that participants are in a positive state of health, they should also be notified of relevant services such as counseling to seek, if partaking in the study presents negative effects.

Right to withdraw

As part of their briefing prior to giving consent to partake, participants must be informed that they can leave the study at any point if they wish, and are under no obligation to disclose a reason why if they do.

Protection of participants

It is the responsibility of the researcher to ensure that participants are not caused any long-term physical or mental damage. For instance, it may be that participants are temporarily caused distress, although research will be pre-approved by an ethics committee to ensure this is sufficiently minimized, and researchers are expected to take participants through a detailed debriefing (see debriefing).

Working with animals

If non-human animals are to be used in an investigation, researchers can only use species that are considered scientifically suitable according to ethical guidelines. Procedures that could cause physical or mental harm should be avoided where possible, and it is encouraged that investigations take place in their natural environment. Animals must be properly cared for if the study requires them to kept captive.

There are some instances where it is deemed that the costs do not override the benefits of conducting some research. However, it should be appreciated that these ethical guidelines should always be carefully considered when scrutinising whether a study is ethically acceptable to be carried out.

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Ethical Issues of Psychological Investigation

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Ethics are a key part of psychological investigation, as researchers have the responsibility to ensure that their practice is morally correct; ill practice could lead to banning from further practice as a psychologist.There are a number of important issues that researchers should be mindful of when undertaking investigations, with regards to the selection and subsequent treatment of their participants:

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Validity refers to whether a measure actually measures what it claims to be measuring. Some key types of validity are explored below.

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An independent variable (IV) is a variable that is manipulated by a researcher to investigate whether it consequently brings change in another variable. This other variable, which is measured and predicted to be dependent upon the IV, is therefore named the dependent variable (DV).

For example, in an experiment examining the effect of fatigue on short term memory, there are two groups 'fatigued' and 'non-fatigued'. The fatigued group run for 10 minutes without stopping prior to being tested. Both groups are given a list of words to recall immediately after reading the list.

The independent variable in this example would be fatigued/non-fatigued as it has been manipulated by the experimenter.

The dependent variable would be the number of words recalled off the list because that is how the participants' performance is measured.

IVs and DVs only occur in experiments, as a cause and effect is predicted between the two (i.e. that changes in the IV will directly lead to changes in the DV).

IVs and DVs do not feature in correlation studies, as correlation studies look for a relationship between co-variables, cause and effect is therefore not established as the variables are predicted to change in response to each other.

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An independent variable (IV) is a variable that is manipulated by a researcher to investigate whether it consequently brings change in another variable. This other variable, which is measured and predicted to be dependent upon the IV, is therefore named the dependent variable (DV).

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Presence of demand characteristics in a study suggest that there is a high risk that participants will change their natural behaviour in line with their interpretation of the aims of a stud y, in turn affecting how they respond in any tasks they are set.

Participants may, for example, try to please the researcher by doing what they have guessed is expected of them.

Alternatively, they may deliberately try to skew the results in one way or other, such as attempting to do the opposite of what they think is expected (i.e. the 'screw you' effect).

A repeated measures study design is more likely to present the problem of demand characteristics, as participants will be take part in all conditions of the experiment, which could give them enough information to consider the 'real' purpose of the study. Independent groups and matched pairs designs are generally at lower risk, as participants will not perform more than one condition of the experiment, so will be less likely to look into the study's aims. Observational studies are also generally less likely to present demand characteristics, as participants might not know that they are taking part in a study.

Hawthorne Effect

The Hawthorne effect is present when the increased attention given by the researchers is a confounding variable in a study. Evaluation apprehension (i.e. the modulation of arousal and thus performance through participants knowing they are being appraised by others), may lead to a participant trying harder than they usually would do, thus distorting the results collected.

Detecting this effect requires information about similar activities carried out when the participants did not know they were under investigation.

Social Desirability Bias

This bias in participants' behaviour occurs when they note aspects of the study that have to do with particular social norms or expectations, and in turn present themselves in what they deem a socially acceptable fashion.

For example, when asked if they have ever stolen anything, participants may lie in order to avoid presenting themselves in a bad light, consequently leading to gathering inaccurate data.

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Presence of demand characteristics in a study suggest that there is a high risk that participants will change their natural behaviour in line with their interpretation of the aims of a study, in turn affecting how they respond in any tasks they are set.

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Extraneous variables are unwanted factors in a study that, if not accounted for, could negatively affect (i.e. confound) the data subsequently collected.

Such factors potentially prevent researchers from finding a direct causal effect between the manipulated independent variables (IVs) and measured dependent variables (DVs) set out in an investigation.

For researchers to be confident that change in the IV will solely affect change in the DV, potential confounds need to be identified and controlled/eliminated; poor control will lead to results with lower reliability.

There are three key considerations to take when controlling extraneous variables:

Participant variables - minimizing differences between participants (e.g. their stage of development such as age, or ability such as IQ).

Researcher variables - factors such as researcher behaviour, appearance or gender could affect participant responses, so should be made consistent throughout the experiment.

Situational variables - control of the setting where the experiment takes place, such as keeping light, sound and temperature levels consistent.

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Extraneous variables are unwanted factors in a study that, if not accounted for, could negatively affect (i.e. confound) the data subsequently collected.

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Observations of events or behaviour in our surroundings provoke questions as to why they occur. In turn, one or multiple theories might attempt to explain a phenomenon, and investigations are consequently conducted to test them. One observation could be that athletes tend to perform better when they have a training partner, and a theory might propose that this is because athletes are more motivated with peers around them.

The aim of an investigation, driven by a theory to explain a given observation, states the intent of the study in general terms. Continuing the above example, the consequent aim might be "to investigate the effect of having a training partner on athletes' motivation levels".

The theory attempting to explain an observation will help to inform hypotheses - predictions of an investigation's outcome that make specific reference to the independent variables (IVs) manipulated and dependent variables (DVs) measured by the researchers.

There are two types of hypothesis:
H₁ - The Research Hypothesis
This predicts a statistically significant effect of an IV on a DV (i.e. an experiment), or a significant relationship between variables (i.e. a correlation study), e.g.

In an experiment: "Athletes who have a training partner are likely to score higher on a questionnaire measuring motivation levels than athletes who train alone."

In a correlation study: 'There will be a significant positive correlation between athletes' motivation questionnaire scores and the number of partners athletes train with."

The research hypothesis will be directional (one-tailed) if theory or existing evidence argues a particular 'direction' of the predicted results, as demonstrated in the two hypothesis examples above.

Non-directional (two-tailed) research hypotheses do not predict a direction, so here would simply predict "a significant difference" between questionnaire scores in athletes who train alone and with a training partner (in an experiment), or "a significant relationship" between questionnaire scores and number of training partners (in a correlation study).
H₀ - The Null Hypothesis
This predicts that a statistically significant effect or relationship will not be found, e.g.

In an experiment: "There will be no significant difference in motivation questionnaire scores between athletes who train with and without a training partner."

In a correlation study: "There will be no significant relationship between motivation questionnaire scores and the number of partners athletes train with."

When the investigation concludes, analysis of results will suggest that either the research hypothesis or null hypothesis can be retained, with the other rejected. Ultimately this will either provide evidence to support of refute the theory driving a hypothesis, and may lead to further research in the field.

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Observations of events or behaviour in our surroundings provoke questions as to why they occur. In turn, one or multiple theories might attempt to explain a phenomenon, and investigations are consequently conducted to test them.

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Experimental design describes the way participants are allocated to experimental groups of an investigation. Types of design include Repeated Measures, Independent Groups, and Matched Pairs designs.

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A population is an entire group with specified characteristics. The target group/population is the desired population subgroup to be studied, and therefore want research findings to generalise to. A target group is usually too large to study in its entirety, so sampling methods are used to choose a representative sample from the target group.

A representative sample is a subset of the target group with a similar distribution of relevant characteristics, in turn allowing us to generalise from the sample to the target group with some justification. An unrepresentative sample is one that does not reflect the distribution of characteristics of the target group, cannot be generalised to the target population, and is therefore biased.

There are a number of different sampling methods. Let's take a look at each briefly.

Random sampling

This method gives every member of the target group an equal chance of being selected for the sample (e.g. by assigning a number to each member, and then selecting from the pool at using a random number generator).

Strengths

It is widely accepted that since each member has the same probability of being selected, there is a reasonable chance of achieving a representative sample.

Weaknesses

Small minority groups within your target group may distort results, even with a random sampling technique.

It can be impractical (or not possible) to use a completely random technique, e.g. the target group may be too large to assign numbers to.

Systematic sampling

A systematic method is chosen for selecting from a target group, e.g. every fourth person in a list could be used in the sample. It differs from random sampling in that it does not give an equal chance of selection to each individual in the target group.

Strengths

Assuming the list order has been randomised, this method offers an unbiased chance of gaining a representative sample.

Weaknesses

If the list has been assembled in any other way, bias may be present. For example if every fourth person in the list was male, you would have only males in your sample.

Stratified Sampling

Here the sampler divides or 'stratifies' the target group into sections, each showing a key characteristic which should be present in the final sample. Then each of those sections is sampled individually. The sample thus created should contain members from each key characteristic in a proportion representative of the target population.

Strengths

It avoids the problem of misrepresentation sometimes caused by purely random sampling.

Weaknesses

It takes more time and resources to plan.

Care must be taken to ensure each key characteristic present in the population is selected across strata, otherwise this will design a biased sample.

Opportunity Sampling

Participants who are both accessible and willing to take part are targeted, e.g. employees from a conveniently located employer near the laboratory could be selected for the sample group.

Strengths

This method is easy and inexpensive to carry out.

Weaknesses

The consequent sample may not be representative as it could be subject to bias (e.g. the conveniently located employer may undertake a selection process for job applicants, making it likely that employees possess certain similar characteristics that are unrepresentative of the wider target group).

Volunteer Sampling

Here the sample consists of people who have volunteered to be in the study.

Strengths

This often achieves a large sample size through reaching a wide audience, for example with online advertisements.

Weaknesses

Those who respond to the call for volunteers may all display similar characteristics (such as being more trusting or cooperative than those who did not apply) thus increasing the chances of yielding an unrepresentative sample.

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A population is an entire group with specified characteristics. The target group/population is the desired population subgroup to be studied, and therefore want research findings to generalise to. A target group is usually too large to study in its entirety, so sampling methods are used to choose a representative sample from the target group.

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Explaining a Quasi-Experiment

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Quasi-Experiment in Psychology | Definition & Examples - Lesson | Study.com

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Learn the definition of quasi-experiment in psychology. Understand quasi-experimental designs and quasi-independent variables through real research…

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Example of lack of replication

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Reliability and validity class presentation

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What is it?

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Exam-style questions

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Psychology Review Article
Extraneous and Confounding Variables