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research methods- 2 Flashcards

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1
Q

theories are..

A

an explanation of a phenomena- constructed using evidence

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2
Q

what is hypothesis testing

A

the process in which theories are tested

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3
Q

what is a hypothesis

A

testable prediction of an element of a theory,
by using a theory to generate hypotheses, researchers can see if their theory is wrong

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4
Q

what is falsifiability and who came up with it

A

key feature of science developed by Karl popper stating that it must be at least theoretically possible to prove theories wrong, unfalsifiable theories are not scientific

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5
Q

what is replicability

A

when a different team can repeat the same experiment and receive the same results, variables have to be operationalised

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6
Q

what is the empirical method

A

collecting data through direct observation or experiments to test their ideas

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7
Q

what is the aim of an experiment

A

simple summary of what variables are being investigated, and setting up the purpose of the study

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8
Q

what is operationalisation

A

clearly defining the variables in such a a way other researchers can replicate the exact conditions and method of the study

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9
Q

what are confounding variables

A

type of ev that cause significant problems for the study’s internal validity, have a causal effect on the dv, researcher cannot tell if it was the iv or the cv that had the effect on the dv

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10
Q

strength- independent groups design

A

helps strengthen internal validity of the study- no order effects

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11
Q

limitation- independent groups deign

A

uncontrolled participant evs

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12
Q

strength- matched pairs design

A

controlled participant evs- no differences between conditions in participants

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13
Q

limitation- matched pairs

A

time consuming and expensive- matched pairs is harder to find than independent groups

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14
Q

strength- repeated measures design

A

no participant evs

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15
Q

limitation- repeated measure design

A

order effects

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16
Q

what is a lab exp

A

true exp- controlled conditions

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17
Q

what is a field exp

A

true exp- naturalistic conditions

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18
Q

what is a quasi exp

A

not a true exp- iv determined by pre-existing differences

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19
Q

what is a natural exp

A

not a true exp- iv determined by naturally occurring evet

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20
Q

strength and limitation of a lab exp

A

strength- high internal validity
limitation- low external validity- ecological validity

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21
Q

strength and limitation of a field exp

A

strength- high external validity- ecological validity
limitation- low internal validity- less controlled settings

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22
Q

strength and limitation of a quasi exp

A

strength- necessary- only way to study variables such as age or gender
limitation- low internal validity- impossible to randomly allocate- uncontrolled participant evs

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23
Q

strength and limitation of a natural exp

A

strength- high external validity- study of real life events
limitation- low internal validity- impossible to randomly allocate- uncontrolled participant evs

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24
Q

strength of unstructured interviews

A

flexibility- helps clarify answers, can ask follow up questions

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25
Q

limitation of unstructured interviews

A

hard to analyse- lots of qualitative data

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26
Q

strength of structured interviews

A

replicable- standardized format, more data can be collected easily

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27
Q

weakness of structured interviews

A

no follow up questions- miss out on potentially useful data

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28
Q

strength of open questions

A

high ecological validity- more natural responses from participants

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29
Q

weakness of open questions

A

harder to analyse- qualitative data

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30
Q

what is a likert scale

A

how satisfied are you with…

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31
Q

acquiescence bias

A

type of response bias in which people have a tendance to agree with statements

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32
Q

strength and limitation of qualitative data

A

strength- greater external validity
limitation- harder to analyse

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33
Q

strength and limitation of quantitative data

A

strength- more objective, less open to bias
limitation- narrower in scope of data, may fail to represent ‘real- life’

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34
Q

strength and limitation of primary data

A

strength- authentic data collected specifically for the purpose of a specific investigation
limitation- requires time and effort from researcher

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35
Q

strength and limitation of secondary data

A

strength- easily accessed, limited effort and time
limitation- may be variation in quality and accuracy of secondary data compared to primary- may not fit researchers specific needs

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36
Q

outline controlled observations

A

carried out in a controlled setting, uses a standardized procedure

37
Q

one strength and limitation of controlled observations

A

strength- high internal validity
limitation- low external validity

38
Q

outline naturalistic observations

A

takes place in conditions where behaviour would naturally occur- aspects of environment will vary

39
Q

one strength and limitation of naturalistic observations

A

strength- high ecological validity
limitation- low internal validity- lacks control

40
Q

what are covert observations

A

participants is observed without their knowledge or consent

41
Q

strength and limitation of covert observations

A

strength- high ecological validity
limitation- ethical issues- informed consent

42
Q

what are overt observations

A

behaviour is observed with their knowledge and consent

43
Q

strength and limitation of overt observations

A

strength- ethics- obtain informed consent
limitation- low ecological validity

44
Q

what is a participant observation

A

the researcher becomes a member of the group whose behaviour is being observed

45
Q

strength and limitation of participant observations

A

strength- collect rich data- can experience the situation as the participants experience it
limitation- loss of objectivity- can compromise validity

46
Q

what is a non- participant observation

A

the researcher remains outside of the group whose behaviour is being observed

47
Q

strength and limitation of non- participant observation

A

strength- remain objective- improves validity
limitation- may miss nuances in participants’ behaviour

48
Q

what is a paradigm

A

set of shared assumptions and agreed methods for a scientific discipline

49
Q

what is a paradigm shift

A

researchers switch to a new paradigm with a whole new set of shared assumptions and methods- e.g. behaviourist to cognitive

50
Q

what is content analysis

A

studies behaviour indirectly through their communications- diaries, transcribed phone conversations
- analysing qualitative data using quantitative techniques

51
Q

what are coding categories- content analysis

A

specific types of communication the coders will look for

52
Q

how to conduct content analysis

A

identify coding categories- repeatedly look through data and tally instances of categories- can then be charted

53
Q

what is thematic analysis

A

studies behaviour indirectly through their communications- diaries, transcribed phone conversations
- qualitative data analysed qualitatively, by identifying themes within the data

54
Q

how to conduct thematic analysis

A

Familiarisation with the data –immerses themselves in the data by intensely reading
- identify ideas that reoccur in the data
-group the ideas together into themes, broad categories that are important
- write a report of their findings including direct quotes

55
Q

strength of content and thematic analysis- ecological validity

A

used to analyse qualitative data from real-life communications
-This means research findings from content/thematic analysis may be more generalisable

56
Q

limitation of thematic analysis- subjectivity

A

researchers have to analyse the data to identify the themes within it
-requires a significant degree of interpretation, which can result in observer-bias
-subjective and therefore unscientific.

57
Q

limitation of content analysis- surface level analysis

A

can only access the manifest content within communication data- (I.e., evident/obvious) on the surface
- relies only on counting instances of types of communication, can describe what the data appears to show, but may easily miss the latent content- deeper meanings that are hidden below the surface

58
Q

strength of thematic analysis- latent content

A

requires the researcher to interpret the data so they can go beyond just describing the communications and instead explain what they meant to communicate
- thematic analysis is good at accessing the latent content of communication data, meaning it can detect the hidden meanings below the surface

59
Q

strength of content analysis- scientific credibility, replicability

A

easily replicable as once the researcher has generated their coding categories and specified the data they have analysed, another team of researchers can easily re-analyse the data with the same coding categories, and so determine if the results are replicable

60
Q

what is the abstract of a scientific report

A

-first section of a scientific report- provides an overview of the report,
allows other researchers to quickly scan and decide if it is appropriate for their research
- contains summary of the aims, hypothesis, method, results and conclusions
-about 150-200 words.

61
Q

what is the introduction of a scientific report

A

provide background information and a rationale for the current research
-contains a review of previous research relevant to the investigation + the aims and hypotheses of the study
- structured like a funnel, moving from the general conclusions of previous research to the specific aim and hypotheses of the study

62
Q

what is the method of a scientific report

A

detailed description of what the researcher did- needs to be detailed enough to allow replicability
should include- the design, participants/sampling
(detail about participants must be anonymised), materials, procedure and ethics

63
Q

what are the results of a scientific report

A

what they found in their investigation, includes;
- Descriptive statistics e.g. graphs
- Inferential statistics e.g. significance levels
- final outcome: which hypotheses were accepted or rejected
- if qualitative research; results section would involve description of the categories, themes and examples

64
Q

what is the discussion in a scientific report

A

the researcher interprets the results of the study and reflects on the investigation- includes;
- summary of the results – verbal summary
- Relationship to previous research – supported or challenged?
- Reflection on methodology –consider problems within their study
- Implications of research – discuss real-world implications of their research
- Suggestions for future research – lay out suggestions for future research

65
Q

what is the refence section of a scientific report

A

full details of any sources used when writing report
- name of the author(s), title of the source, date of publications, publisher
-It also provides an important check on plagiarism

66
Q

what are case studies

A

a detailed and intensive analysis of a single case; individuals, organisations, communities
- the case is not being studied because it is intended to be representative of a broader target population- it is studied to be the focus of interest in its own right

67
Q

limitation of case studies- external validity

A

case study research conducted on a single case- small sample size + unique
- generalising from case study research can be difficult- e.g. Freud’s psychodynamic theories- Little Hans
-however case study research is not intended to be generalized- purpose is to understand a single case in its own right
-criticism may be inappropriate

68
Q

strength of case studies- evaluating a theory

A

-Clive Wearing case study used to challenge validity of MSMs claim that there is only one LTM store.
- unique cases can be used to test hypotheses generated by a theory
-play an important role in challenging current thinking
-guides the way to the development of new theoretical ideas

69
Q

what are statistics and what are they used for

A

branch of mathematics used to analyse data
used by psychologists to aid hypothesis testing -analyse their data and determine if their hypotheses are supported

70
Q

presence of manipulation in correlational or experimental

A

experimental

71
Q

purpose of correlational study

A

establish whether two or more variables are associated in some way

72
Q

purpose of experimental study

A

establish a causal relationship

73
Q

what descriptive stats can be used in correlations and experimental

A

correlations- correlation coefficient
experimentals- measures of central tendency

74
Q

what is nominal data

A

simplest level of measurement
-assigning labels or names to identify and categorize objects or subjects, without any quantitative value or order

75
Q

what is ordinal data

A

categorizing data into discrete groups with a meaningful order or ranking among the categories
- intervals between categories are not uniform

76
Q

what is interval data

A

numerical scales with a consistent interval or distance between value

77
Q

what do descriptive statistics do

A

describe overall patterns in data
- can be used to make a judgement about; which condition (if any) did “better” and Whether there was a positive or negative correlation and its strength

78
Q

what do inferential stats do

A

assess whether the results could have occurred by chance

79
Q

what is a related design

A

repeated measures and matched pairs designs

80
Q

what is a non- related design

A

independent groups design

81
Q

what is a type 1 error

A

the researcher claimed they have found significant results when in reality the results are not significant

82
Q

what is reliability

A

how consistent the findings of the test are

83
Q

what is test- retest

A

requires the researcher test the same participant twice, with both these tests having consistent result

84
Q

what is inter-observer reliability

A

two different researchers conduct the test on the same participant, and their observations are consistent

85
Q

when does a test have validity

A

if it measures what it claims to measure

86
Q

acronym for statistical tests

A

carrots should come mashed with sweet un-roasted potatoes
-chi, sign, chi, mann, wilcoxon, spearmans, unrelated, related, pearsons

87
Q

how to find calculated value (sign test)

A

allocate
- plus if condition 1 is larger
-minus if condition 2 is larger
-equals (ignore in calculation) if equal
then count frequency of least common sign
written as S=

88
Q

how to calculate DF for contingency table-chi-squared

A

(columns-1)X(rows -1)

psych (13 decks)

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