Research Methods Flashcards

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1
Q

Independent variable

A

Variable that’s changed by researcher or naturally

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2
Q

Dependent variable

A

Variable measured by researcher - effect caused by change in Independent Variable

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3
Q

Laboratory experiment

A

> Highly controlled environments

>Eg: Milgram’s experiment on obedience.

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4
Q

Laboratory experiment: CONS

A

> Lack generalisability - lab environment = artificial + not like everyday life - behaviour can’t be generalised (low external validity)
Participants aware they’re being tested - demand characteristics
Tasks might not represent real-life experience

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5
Q

Laboratory experiment: PROS

A

> High control over extraneous variables (ensure change in IV caused effect on DV)
Demonstrates cause + effect (high internal validity).
Replication more possible - high level of control
Important to check results are valid

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6
Q

Field experiment

A

> Natural/everyday setting
Researcher manipulates IV + records effect on DV
Eg: Holfing’s hospital study on obedience.

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7
Q

Field experiment: CONS

A

> Less control over extraneous variables - cause + effect = harder to establish + replication = often not possible
Ethical issues - don’t know they are being studied = no informed consent

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8
Q

Field experiment: PROS

A

> Higher mundane realism than lab - more natural

>Produce more valid + authentic behaviour (high external validity)

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9
Q

Natural experiment

A

> Pre-existing independent variable

>IV not brought about by researcher - would happen even if researcher wasn’t there

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10
Q

Natural experiment: CONS

A

> Naturally occurring event might happen rarely - reduced opportunities for research
Less scope for generalising findings
Participants not randomly allocated - researcher = less sure that IV affects DV.

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11
Q

Natural experiment: PROS

A

> Allows research to take place that might not be ethical otherwise.
High external validity - study of real-life issues + problems as they happen

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12
Q

Quasi experiment

A

> Almost an experiment but not quite
IV based on existing difference between people (e.g. age or gender)
No-one manipulates IV - just exists

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13
Q

Quasi experiments: CONS

A

> Cannot randomly allocate participants to conditions - may be confounding variables.

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14
Q

Quasi experiments: PROS

A

> Controlled conditions - same strengths as lab study

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15
Q

Experimental method: Aims

A

> Broader or less precise than hypothesis

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16
Q

Experimental method: Hypothesis

A

> Testable + predictive statement generated from theory

>Either predicted difference between IV + DV (experimental hypothesis) or predicted relationship between variables

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17
Q

Experimental method: Operationalising hypotheses

A

> Hypothesis should be operationalised

>Variables + how they will be measured must be clear

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18
Q

The alternate (experimental) hypothesis

A

> States expected effect of IV on outcome = statistically significant.

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19
Q

The null hypothesis

A

> States that there is no effect in a study.

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20
Q

Directional (one tailed) hypothesis

A

> Direction of predicted difference
E.g. teenagers will sleep for more hours/week than adults ages 20-40
Predicts nature of effect of IV on DV

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21
Q

Non-directional (two tailed) hypothesis

A

> Predicts difference between 2 conditions where direction difference will be
E.g. significant difference between teenagers + adults aged 20-40 in no. of hours they sleep/week
Predicts IV will have effect on DV but direction isn’t specified.

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22
Q

Design of experiments: Independent

A

> Different participants used in each condition
Each condition includes different group of participants
Random allocation - ensures each participant has equal chance of being assigned

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23
Q

Design of experiments: Independent PROS

A

> Avoids order effects (practice or fatigue) as people participate in one condition only.

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24
Q

Design of experiments: Independent CONS

A

> More people needed than with repeated measures

>Differences between participants in groups

25
Q

Design of experiments: Repeated measures PROS

A

> Fewer people needed - take part in all conditions.

>Same participants = participant variables reduced.

26
Q

Design of experiments: Repeated measures CONS

A

> Order effects - order of conditions having effect on participants’ behaviour
Performance in 2nd condition may be better - participants know what to do
Performance might be worse in 2nd condition - tired
Can be controlled using counter balancing.
Counterbalances order of conditions for participants - alternating order that participants do conditions

27
Q

Design of experiments: Matched pairs

A

Each condition uses different but similar participants. An effort is made to watch the participants in each condition are terms of any important characteristics which might affect the results. One member of each matched pair must be randomly assigned to the experimental group and the other to the control group.

28
Q

Design of experiments: Matched pairs PROS

A

> Reduces participant variables because the researcher has tried to pair up the participants so that
each condition has people with similar abilities and characteristics.
Avoids order effects, and so counterbalancing is not necessary.

29
Q

Design of experiments: Matched pairs CONS

A

> Very time-consuming trying to find closely matched pairs.
Impossible to match people exactly, unless identical twins
If one participant drops out you lose 2 PP’s data.

30
Q

Counterbalancing

A

Suppose we used a repeated measures design in which all of the participants first learned words in ‘loud noise’ and then learned it in ‘no noise’ You would expect the participants to show better learning in ‘no noise’ simply because of order effects, such as practice. However, a researcher can control for order effects using counterbalancing. The sample would split into two groups experimental (A) and control (B). For example, group 1 does ‘A’ then ‘B’, group 2 does ‘B’ then ‘A’ this is to eliminate order effects. Although order effects occur for each participant, because they occur equally in both groups, they balance each other out in the results.

31
Q

Participant variables

A

Individual differences between participants such as levels of intelligence, age, gender, social class, fitness etc. A researcher can do little to control these, but careful selection of participants can reduce these. Repeated measures designs eradicate participant variables, but lead to order effects. Matched pairs designs minimise participant variables, but even twins have some differences that could be significant.

32
Q

Target population

A

> The first thing you need to do is establish the target population
Target population – the group of people the researcher wants to look at.
Usually the target population will be too big to look at everyone, so this is when you need to obtain a sample
This should be a representative sample.

33
Q

Representative sample

A

One in which all characteristics of the target population are represented
If a sample is representative, then any results we obtain can be generalised to the rest of the target population.

34
Q

Sampling: Random sampling

A

> Every member of the target population has an equal chance of being selected
No experimenter bias
Might not be representative

35
Q

Sampling: Opportunity sampling

A

> Asking whoever is there at the time
Straightforward to use
Could be biased (but no more than any other sample)

36
Q

Sampling: Volunteer sampling

A

> (can be direct or indirect) people put themselves forward to participate in research
Easy to carry out
Type of person who volunteers for sample?

37
Q

Sampling: Systematic sampling

A

> When every nth member of the target population is selected. A ‘sampling frame’ is produced (list of all the people in the TP organised eg into alphabetical order). A sampling system is then nominated and the sampling frame is worked through.
Avoids researcher bias
Generally a representative sample so you can generalise

38
Q

Sampling: Stratified sampling

A

This is when the composition of the sample reflects the composition of the target population e.g. 20% 16 year olds, 60% 17 year olds and 20% 18 year olds. Once divided, participants are randomly chosen.
>Avoids researcher bias
>Produces representative sample
>Still can’t be wholly representative

39
Q

Ethics

A

The British Psychological Society has a code of ethics that all researchers must stick to when conducting psychological research. It is their professional duty to follow them, failure to do so may result in loss of reputation or career. Usually ethics committees in institutions and universities will use a cost-benefit approach to determine whether research proposals are ethically sound to go ahead.

40
Q

Ethics: Informed consent

A

> Whenever possible investigators should obtain the consent of participants. In practice this means it is not sufficient to simply get potential participants to say “Yes”.
They also need to know what it is that they are agreeing to.

41
Q

Ethics: Presumptive consent

A

> It is not always possible to gain informed consent. Where it is impossible for the researcher to ask the actual participants, a similar group of people can be asked how they would feel about taking part.
However, a problem with this method is that there might there be a mismatch between how people think they would feel/behave and how they actually feel and behave during a study?

42
Q

Ethics: Debrief

A

> After the research is over the participant should be able to discuss the procedure and the findings with the psychologist. They must be given a general idea of what the researcher was investigating and why, and their part in the research should be explained.
Participants must be told if they have been deceived and given reasons why.
They must be asked if they have any questions and those questions should be answered honestly and as fully as possible.

43
Q

Ethics: Protection of participants

A

> Researchers must ensure that those taking part in research will not be caused distress.
Must be protected from physical and mental harm.
Normally, the risk of harm must be no greater than in ordinary life
The researcher must also ensure that if vulnerable groups are to be used they must receive special care

44
Q

Ethics: Privacy

A

> Confidentiality is a legal right for participants and researchers should do everything possible to ensure anonymity by removing names and any identifying details. Under the data protection act, this is the right to have personal data protected.

45
Q

Ethics: Right to withdraw

A

> All participants should know that they can withdraw from a study at any time, and, perhaps more importantly, how to withdraw. They should not feel obligated to continue with their participation and should be aware that they can leave part way through the investigation If they wish. Their data will be removed too.

46
Q

Questionnaires

A

> List of pre-set questions,which are often written down
The questionnaires are the same for everyone who takes part in the questionnaire survey.
Questionnaires can consist of one, other or both closed and open questions

47
Q

Closed questions

A

Questions for which there is a set number of responses. There are often given in the form of multiple-choice answers or as a rating scale (i.e. strongly agree, agree, indifferent, disagree, strongly disagree)

48
Q

Open questions

A

When the respondent chooses their own answers. Such questions can often be answered in some depth

49
Q

Strengths of questionnaires

A

> They can be used to access people’s thoughts and feelings
All respondents are asked the same questions. This means it’s possible to compare answers and look for patterns and trends
Questionnaires are easy to administer to a large sample quickly. For example, they can be posted on an internet site, or given out to a group of people at the same time

50
Q

Weaknesses of questionnaires

A

> People may lie or exaggerate as there is often no one to check their responses. However, others argue that that we are more likely to get more truthful answers because there is no one there.
Respondents may misunderstand questions and therefore not give reliable answers. In addition, with some closed questions, they may not be able to give the response that they want. Therefore, they may end up missing out questions, or giving inaccurate responses.
Questionnaires also do not take individuals into account. By asking everyone the same questions, researchers cannot explore individual responses.

51
Q

Interviews

A

> Always carried out face to face. The psychologist asks direct questions to the interviewee. These questions are often open in order to get more in depth answers.
Two main types of interviews:
Structured interviews: questions are predetermined. Everyone who is interviewed is asked the same questions
Unstructured interviews: Do not have set questions. Instead the interviewer asks questions based on the interviewees’ answers. This means that the interview runs more like a conversation.

52
Q

Strengths of Interviews

A

Can be used to access people’s thoughts and feelings
The interviewee can double-check what they think the question means. The interviewer can also clarify their answers if they are not clear.

53
Q

Limitations of interviews

A

> People may lie or exaggerate as there is no way of checking the truth. Since the interviewer is there throughout the interview, interviewees may feel obliged to give socially desirable responses, rather than their real responses
They rely on people being able to explain their thoughts and feelings. Some people do not have the ability to do this as they cannot express themselves clearly. In addition, they may not have a good insight into themselves.

54
Q

Casual correlations

A

There is a cause and effect relationship e.g. the IV affects the DV.

55
Q

Non-casual correlations

A

There is a relationship between the two variables e.g. correlation

56
Q

Correlational design

A

Not so much a research method as a method of data analysis. Looks at relationship between two variables (Co –variables) – but not at cause and effect A does not necessarily cause B – But there is a relationship

57
Q

Correlation coefficient

A

This is the number that expresses the degree to which the two variables are related. Ranges from: + 1 (perfect positive correlation) to – 1 (perfect negative correlation). The closer the relationship to a perfect correlation, the stronger the relationship between the two variables. If there is no correlation, the result will be near zero (0.0)

58
Q

Strengths of correlational design

A

> There is little manipulation of variables. Measures are often taken of existing situations with few controls needed – which can make for a straightforward design. The two measures are taken and the scores tested to see if there is a relationship.
This is quite straightforward compared to some experiments, observations and surveys.
Correlations can show relationships that might not be expected, and so can be used to point towards new areas for research.

59
Q

Limitations of correlational design

A

> Relationship found without finding whether 2 variables are casually or chance related
Build scientific body of knowledge = claim cause + effect >E.g - correlation between smoking + risk of heart disease - not accepted by smokers, not claimed at the time
Other factors may cause hearts disease as well
Lack validity - 1+ variable has to be operationalised = unnatural