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A level Psychology > Research Methods > Flashcards

Research Methods Flashcards

1
Q

What are the 4 types of experiments

A

Lab
Field
Natural
Quasi

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2
Q

Describe lab experiments (how controlled in the IV, is random allocation allowed,)

A

Highly controlled IV manipulation and extraneous variables are also controlled
Allows random allocation

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3
Q

Describe field experiments (how controlled in the IV, setting, extraneous variable control)

A

Controlled manipulation of the IV
In a natural setting
Some control over extraneous variables

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4
Q

Describe natural experiments (IV manipulation, random allocation?, and eg )

A

Naturally existing event
No manipulation over the IV
No random allocation
eg. students who grew up in an orphanage vs a nuclear family

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5
Q

Describe quasi experiments (IV manipulation, how the IV is selected, setting)

A

No Iv manipulation as IV is a naturally occurring condition (eg. age and gender)
Simply a difference between people who exist
Natural setting

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6
Q

Define internal validity

A

If controlled variables affect the results

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7
Q

Define external/ecological validity

A

Can it be generalised to the public

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8
Q

Define mundane realism

A

Does it happen often in day to day life

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9
Q

Define confounding variables

A

A variable caused by a confederate (eg intelligence levels)

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10
Q

Describe the positive (2) and negative (2) features of a lab experiment

A

Good internal validity
Easily replicable

Low external validity
Low mundane realism

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11
Q

Describe the positive (4) and negative (2) features of a field experiment

A

Good to see natural behaviour
Less demand characteristics
High external validity
High mundane realism

Low internal validity
Less control over confounding variables

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12
Q

Describe the positive (2) and negative (2) features of natural and quasi experiments

A

High external validity
High mundane realism

Hard to deduce cause and effect (rls between IV and DV)
Low internal validity
Confounding variables

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13
Q

What are extraneous variables

A

Variables besides the IV which can affect the DV if not controlled- reducing the internal validity

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14
Q

Explain investigator effects

A

When a researcher unintentionally or unconsciously influences the outcome of any research they are conducting eg. leading questions

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15
Q

Explain confounding variables

A

A type of extraneous variable

These are variables that change systematically within the IV (different characteristics within groups- eg. if group A was a group of mathematicians in our class maths experiment)

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16
Q

Explain demand characteristics

A

When participants figure out the aim of a study and change their behaviour accordingly

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17
Q

In what two ways can we control research issues

A

Random allocation and Standardisation

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18
Q

Explain random allocation, its effects and an example

A

The use of chance methods when deciding the experimental groups

This can reduce participant/confounding variables

Eg. random name generator

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19
Q

Explain standardisation, its effects and an example

A

Using the exact same procedures for all participants, excluding the IV

This can reduce investigator effects

Eg. same instructions, same people reading, same environment

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20
Q

What are repeated measures and how are they controlled

A

All participants receive all/both levels of the IV and the performance of the DV is recorded each time

This is controlled by counterbalancing: If there are two groups then…
Group 1 undergoes condition A then B
Group 2 undergoes condition B then A

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21
Q

Evaluate the positives and negatives of repeated measures

A

Ps:
Reduces individual differences and confounding variables

Ns:
Order effects (boredom and practise effects)
Demand characteristics (may be linked to practise effects)

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22
Q

What are independent measures and how are they controlled

A

PPTs are placed in separate groups and each only does one level of the IV and then the performance of both groups are analysed

To control this, we use random allocation so all PPT variables are distributed evenly

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23
Q

Evaluate the positives and negatives of independent measures

A

Ps:
Less demand characteristics
Less order effects

Ns:
Individual differences/ confounding variables
Requires more ppts to end up with the same amount of data as repeated measures- more time consuming

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24
Q

What are matched pairs and how are they controlled

A

In matched pairs, two groups of PPTs are matched on key characteristics which are believed to affect performance on the DV (characteristics must be relevant to the study). One member of the pair is allocated to group A the other to group B

This is controlled by restricting the number of variables to match on to make it easier, and conducting a pilot study to consider key variables when matching.

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25
Evaluate the positives and negatives of matched pairs
Ps: Less demand characteristics Less order effects Ns: Individual differences still exist even when matched Time consuming
26
Name how can we control demand characteristics
Single blind procedures
27
Explain single blind procedures and their effects (mention ethics)
In a single-blind study, patients do not know which study group they are in (for example whether they are taking the experimental drug or a placebo) Reducing any information that might create expectation Helps reduce demand characteristics Ppts should be debriefed at the end and given the chance to withdraw
28
How can we control investigator effects
Double blind procedure
29
Explain double blind procedures
In a double-blind study, neither the patients nor the researchers/doctors know which study group the patients are in. There is usually a third party conducting the study
30
What is a correlation
A correlation is a relationship between co-variables that have to be continuous
31
How are correlations different from experiments
They have no IV or DV, therefore no cause of effect relationship
32
Name and explain the three types of correlation
Positive correlation- both variables increase together Negative correlation- as one variable increases, the other decreases No correlation- no relationship between the two variables
33
What are the values for a perfect positive correlation and a perfect negative correlation
1 and -1
34
Explain the fact that correlation does not equal causation
Correlations are being criticised for not creating a cause and effect relationship so it is hard to know which covariable causes what
35
Explain the third variable effect
A third variable can affect the correlation and negatively affect the results
36
What are the advantages if correlations (2)
Useful as a preliminary research method to allow researchers to identify a link Can be used to research topics that are sensitive or would otherwise be unethical
37
What are the 4 principles of BPS (British Psychological Society)
Respect Competence Responsibility Integrity
38
What are the measures of central tendency
Averages that tell us about the central value for a set of data (mean, median, mode)
39
What are the measures of dispersion
They are base don the spread of scores and how far they differ from each other (range and standard deviation)
40
What is standard deviation and what does it show
Standard deviation shows the amount of variation in a data set (around the mean value). The larger the standard deviation, the greater the dispersion of data. It shows the consistency of data
41
What is a normal distribution
A symmetrical spread of data that forms a bell shaped pattern. The mean, median and mode are all located at the highest peak. The tails of the curve which extend outwards never meet the x axis (0) as there can always be more extreme results
42
What is a skewed distribution
A spread of frequency data that is not symmetrical, the data clusters to one end. They may derive from psychological scales rather than measurable scales
43
What are the two variants of a skewed distribution
Positive skew: Frequency distribution in which the long tail is on the positive (right) side of the peak and most of the distribution is concentrated on the left Negative skew: Frequency distribution in which the long tail is on the negative (left) side of the peak and most of the distribution is concentrated on the right
44
Evaluate quantitative data
S: analysis and comparison is easier; more objective and less open to bias L: more narrow in meaning and detail so it may not represent real life
45
Evaluate qualitative data
S: greater external validity due to greater meaningful insight from participants L: difficult to analyse; cannot be categorised statistically to recognise patterns and comparisons
46
Evaluate primary data
S: Authentic and may specifically target the info that the investigator requires L: Open to researcher bias; takes time and effort
47
Evaluate secondary data
S: Inexpensive and easily accessed L: Variation in quality and accuracy of data challenges validity
48
Evaluate meta-analysis
S: Larger, more varied sample of results resulting in greater generalisability and validity L: publication bias-> the researcher may exclude findings that go against there hypothesis
49
What is the purpose of an observation
To capture spontaneous and unexpected behaviour which might differ from what people say they would do
50
Name and explain the different types of observations and their evaluations
Natural vs Controlled: Natural- uncontrolled environment, natural response, high ecological validity, low internal validity Controlled- controlled environment, high internal validity, low ecological validity Covert vs Overt: Covert- participants are unaware, natural behaviour, ethical issues Overt- participants are aware, no ethical issues, demand characteristics Participant vs Non-participant: Participant- researcher takes part, special insight, overt (if not overt then ethical issues) Non-participant- researcher does not take part, more objective,
51
Name and explain the ways data can be summarised
Tables- include summary paragraph underneath explaining numbers and drawing conclusions Bar charts- can be used to display differences in mean value; used for discrete data (not continuous) Histograms- bars touch showing that the data is continuous rather than discrete Scattergrams-for correlations for example, they depict associations between co-variables and it does not matter which variable is on which axis Line graphs- like histograms, they represent continuous data and use points connected by lines to represent changes over time, for example
52
What are the differences between a structured observation and an unstructured observation
Structured- > for a large group > simplifies target behaviour > allows researchers to quantify observation > predetermined list of behaviours and sampling methods > use behavioural categories and sampling methods Unstructured- > for a small group > write down everything you see > data is rich in detail > used for small-scale observations with few participants > doesn't use behavioural categories and sampling methods
53
What are the two ways to record behaviour
Behavioural categories and Sampling methods
54
Name and explain the sampling methods
Through continuous recording the sampling methods are time and event sampling. Time sampling- recording a target behaviour in a small amount of participants (often 1) using a predetermined timeframe (e.g. every 30s) Time sampling uses behavioural categories (e.g. in a football match we may be interested in only one player so we record their behaviours according to the checklist every 30 seconds) Event sampling- counting the number of times a particular event occurs in a target group. (e.g. identifying the dissent at a football match would require counting the amount of times the players argue with the ref)
55
Explain behavioural categories
Similar to operationalisation, behavioural checklists are made to make the target behaviours more measurable for all researchers
56
Name the two self report techniques
Questionnaires and Interviews
57
What are open vs closed questions in a questionnaire
Open- attains qualitative data as participants are allowed to answer as they wish; there is no fixed range of answers Closed- may attain qualitative data in the form of "yes" or "no" or quantitative data in the form of numerical ratings
58
What are structures, semi-structured and unstructured interviews
Structured- standardised. made up of a set of predetermined questions that are all asked in the same order Semi-structured- an in-between of the two others; there is a list of predetermined questions but follow up questions are allowed, like a job interview Unstructured- no set questions. there is the aim for a specific topic of conversation but interaction tends to be free-flowing
59
Evaluate questionnaires
S: cost effective as they can be sent to a large sample group easily; can be completed without the researcher present; data provided is generally straightforward and easy to analyse (esp if questions are closed) L: self-report means the responses may not always be truthful (demand characteristics and social desirability bias); questionnaires often produce a response bias like acquiescence bias where a person will agree with items in a scale despite the content of the statement (the F-scale is an example of this)
60
Evaluate structured interviews
S: straightforward to replicate due to their standardised format L: data collected is not as rich as interviewers cannot deviate from the questions provided
61
Evaluate unstructured interviews
S: more flexibility and greater insight as a result; rapport can be established L: increased risk of investigator bias; analysis is more difficult
62
List and explain the three types of close ended questionnaires
Likert scale- statement of agreement on a topic usually varying from 1-5 Rating scale- statement of feeling on a particular topic Fixed choice options- list of possible options for a particular topic
63
How are questions asked in interviews (4)
Interviews will have a standardised interview schedule of the questions that should be asked to avoid investigator effects and make answers more comparable. Questions will be operationalised The interviewer will take notes of the answers or record the interview to rewatch it later Rapport will be established Ethical issues like confidentiality will be covered
64
What 4 things should be considered when creating interview questions
Overuse of jargon- using technical terms that are only recognisable to people within a specialised field Emotive language and leading questions- when a researcher's opinion is clear in the way the ask a question or when the respondent is guided towards an answer Double barrelled questions and double negatives- two questions in one or a double negative statement

A level Psychology (5 decks)

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