Psychology AS research methods

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The IV and the DV
The researcher will manipulate the independent variable in order to investigate whether there is a change in the dependent variable.
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Lab experiment
These are conducted under controlled conditions, in which the researcher deliberately changes something (IV) to see the effect of this on something else (DV).
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Strengths of lab experiments
The researcher can manipulate the IV and DV carefully. It can be repeated therefore, it becomes more reliable.
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Weaknesses of lab experiments
If p know they are being judged, may show demand characteristics. Some p may try to guess what is expected and behave differently.
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Field experiment
These are in natural conditions, in which the researcher deliberately changes something (IV) to see the effect of this on something else (DV).
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Strengths of field experiments
There is higher control over the IV. As study is in a natural setting, it has high ecological validity.
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Weaknesses of field experiments
There is less control over the extraneous variables. Random allocation of p to experimental and control conditions is difficult.
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Natural experiment
These are in natural conditions, in which the researcher measures the effect of something which is naturally occurring (IV) to see the effect of this on something else (DV).
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Strengths of natural experiments
People will behave more natural as they do not know they are being watched or in an experiment.
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Weaknesses of natural experiments
Findings can be difficult to read. Observed differences in behaviour between groups may be because of the individual differences not because of the IV.
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These look at the relationships between 2 variables that are already occurring. A correlation can either be positive or negative and will be checked by a correlation co efficient between -1 and 1.
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Strengths of correlations
No experimental manipulation - the research is analysing data which already exists. Can see a direct link between variables - when a link is found, research can be conducted.
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Limitations of correlations
Cause and effect cannot be established. Is one of the variables a moderating factors rather than a direct cause?
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These observe behaviours. The behaviours that the researcher is interested in need to be operationalised so that the observer knows what to look out for and measure. These can be counted up to produce a score.
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How can behaviours be measured?
Behaviours can be defined by producing a behavioural checklist so that the researcher knows exactly what to look out for.
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Naturalistic observation
The researcher observes naturally occurring behaviour (CCTV).
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Controlled observation
The researcher observes and records behaviours that are the subject on the controlled variables (inviting someone and watching them).
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Participant observation
The researcher participants in the research procedure in order to observe target behaviours (pretending to be a p).
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Non participant observation
The researcher observes target behaviours from a distance and is not present during the research produce (hiding).
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Disclosed observation
Participants are informed that they are participating and will be observed (truthful).
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Undisclosed observation
Participants are not informed that they are participating and are not aware that they are being observed (hiding and CCVT).
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Structured observation
Target behaviours are identified prior to research commencing, which are measured during a specified time period using a checklist (when, how and who is control down to the time).
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These allow the researcher to collect qualitative data through asking p questions and recording their responses. The more structured, the easier responses are to compare and analyse.
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These collect data from p using a variety of written questions which can be open, closed or used with a rating scale.
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Open questions, closed questions and rating scales
Open questions - produce qualitative data, closed questions - produce quantitative data, rating scales - produce quantitative data.
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Case studies
These focus on 1 person in loads of detail. They check research/how someone develops overtime. This approach is described as idiographic as it focuses on the uniqueness of the individual.
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Null hypothesis
Predicts that there will be no difference or relationship between variables e.g. there will be no difference in recall scores out of 10 between the mnemonic and control conditions.
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Non directional hypothesis
Predicts that there will be no difference or relationship between variables e.g. there will be a difference in recall scores out of 10 between the mnemonic and control conditions.
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Directional hypothesis
Predicts what the difference or relationship between variables will be e.g. the mnemonic group will recall higher scores out of 100 than the control group..
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Independent groups design
Different p are used in each experimental condition, so that person A's performance in compared with person B from another condition.
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Strengths of independent groups
Can be used when a repeated measures design is inappropriate. There are no order effects.
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Weaknesses of independent groups
You need more p than you do with a repeated measures design.
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Repeated measures design
The same p are used in each experimental condition and the results for each p are compared against each condition, so person A's performance under one circumstance would be compared with their own performance in another circumstance.
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Strengths of repeated measures
You only need 50% of p to get the amount of results you want because you are doing the experiment twice so it will add up. You also have no individual differences.
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Weaknesses of repeated measures
P may guess the purpose of the study and may influence them to alter their behaviour. There are order effects and demand characteristics.
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Matched pairs design
Different p are used in each experimental condition but the people are matched on relevant variables, so person A's is compared with person B from another condition but researchers check to make sure that person A and B have similar abilities.
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Strengths of matched pairs
It controls some individual differences between p. Can also be used when a repeated measures design is used and it minimises individual differences.
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Weaknesses of matched pairs
It is difficult to match the p exactly the same. You'll need more p to ensure they are matched with someone of the same variable. It is challenging and time consuming.
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Pilot studies
These are small scale studies conducted before the start of main data collection, to check if research methods work, so that any problems with he method can be addressed. Can be used with behavioural checklists.
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Control of extraneous variables
These are variables that interfere with the researcher's ability to assess what they intend to. They lower the internal validity of research as it prevents the researcher from measuring what they set out to.
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Refers to whether research is consistent over time; if finding are meaningful and not due to chance, the same results should be replicated at a later point.
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Inter observer reliability
Assessed to check whether 2 observer's rating, of the same event are consistent. The 2 sets of scores can be correlated and a co efficient of +0.8 is expected.
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Internal validity
Refers to whether the researcher is measuring what they have set out to measure. Does the DV really reflect the IV?
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Population and ecological validity
Population - whether the research can be generalised to other groups of people, ecological - whether the research can be generalised from the research setting to other real life settings.
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Psychologists have to follow certain standards produced by the BPS, to ensure that p are protected.
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Protection from harm
Researchers have to prevent p from experiencing any harm, physical or emotional, that exceeds undue risk.
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Right to withdraw
At the start of the research, p should be given the right to leave the research if they wish to, or to withdraw their data.
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P have a right not to be deceived or have information withheld from them.
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P should be given consent to show that they agree to participate, ideally this should be fully informed consent, which means at the time of consent, they understand what the research involves and why it is being done. Parental consent for
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P data or personal information should not be identified by name or organisation.
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Dealing with ethical issues
These aim to prevent ethical issues from occurring, they are also ways to deal with them.
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At the end of research, the researcher should have time with the p to explain what they have done and why, offer reassurance and answer and queries. It is designed to restore the p to their original psychological state.
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Prior general consent
The researcher advises p that sometimes not all information is given prior to research, to check if p are comfortable participating.
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Presumptive consent
The researcher asks a sample of p if they would be happy to participate in the absence of being fully informed. If p agree that they will still participate, the researcher assumes others would be and will conduct the research without full consent.
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Refers to the techniques used in the selection of participants that will be used in research.
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Random sample
All potential p will have an equal chance of being selected. This could be by using a random number generator or picking names "out of a hat".
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Opportunity sample
Researchers ask individuals that they are in contact with to participate in research.
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Volunteer sample
Researchers advertise their research asking for p to come forward. This could be through a newspaper advert.
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Demand characteristics
These occur when p try to make sense of the research and so change their behaviour. This can distort results as p may display the screw you effect. P try to present themselves in a positive light aka social desirability bias.
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Investigator effects
occur when the presence of the investigator themselves affects the outcome of the research.
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Bar charts
Shows the frequency of data for separate variables.
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Shows the frequency of data for continuous variables.
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Show a correlation between 2 variables, producing a positive or negative correlation.
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Central tendency
Mean - add scores and divide by number, median - place data into a rank and locate middle number, mode - most frequency value.
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Measures of dispersion
These show how variable or spread out a set of data is; whether values are highly similar or dissimilar.
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The lowest value is subtracted from the highest value.
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Standard deviation
Once the mean score is calculated, the difference between each particular value and the mean is identified, and used to calculate the overall amount of difference between scores.
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Content analysis
Used to convert qualitative data into quantitative data.
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How is content analysis achieved?
It is achieved by identifying a theme which is relevant to qualitative data; once the theme has been found, the number of times it occurs in the data can be counted, allowed the researcher to spot trends in responses.
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Lab experiment


These are conducted under controlled conditions, in which the researcher deliberately changes something (IV) to see the effect of this on something else (DV).

Card 3


Strengths of lab experiments


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Weaknesses of lab experiments


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Card 5


Field experiment


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