Research methods Flashcards

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1
Q

Nominal

A

Basic type of data, data into separate categories, counting frequency which behaviour occur in a category

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2
Q

Ordinal

A

Data is ordered in some way, it is meaningfully rank-able, 1st 2nd 3rd

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3
Q

Interval

A

Public units of measurements, interval between ranks are regular and has no true zero
e.g. temperature, g (mass)

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4
Q

Ratio

A

Similar to interval data, has a true zero point
e.g. weight, height, mph

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5
Q

IM/Nominal

A

Chi-squared

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6
Q

IM/Ordinal or higher

A

Mann-Whitney

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7
Q

RM/Nominal

A

Sign Test

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8
Q

RM/Ordinal or higher

A

Wilcoxon

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9
Q

Correlation

A

Spearman’s Rank

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10
Q

IM/Interval, Ratio (Parametric)

A

Unrelated T-test

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11
Q

RM/Interval, Ratio (Parametric)

A

Related T-test

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12
Q

Correlation (Parametric)

A

Pearsons

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13
Q

IV

A

Something which is being manipulated by the experimenter but can also naturally occur

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14
Q

DV

A

Something which is measured

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15
Q

Primary data

A

Getting your own data, answering the research questions
e.g. questionnaires, observations
+unbiased, controlled and up to date data

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16
Q

Secondary data

A

Pre-existing data, surveys, documents , articles
+cheaper, quicker, ethical

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17
Q

External reliability

A

Aspects that measure acts same way every time

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18
Q

Test-re-test reliability

A

Has measure done twice, should give similar responses, it can gain high correlation co-efficient

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19
Q

Inter rater reliability

A

Two or more raters consistently assessing or interpreting data from the PS

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20
Q

Internal reliability

A

Consistency measure within itself, should be same throughout

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21
Q

Internal validity

A

Truly measuring what it claims to
e.g. IV causes changes in the DV

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22
Q

Face validity

A

Whether on the surface or face it measures what it claims to

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23
Q

Construct validity

A

Whether your measure is consistently tapping into a construct which you think will exist

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24
Q

Criterion validity

A

Whether measure you are using is backed up by another measure of sae phenomena

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25
Q

Concurrent validity

A

Two measure which are agreeing with each other

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26
Q

External validity

A

Findings can be generalised outside the study

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27
Q

Population validity

A

Whether results from the sample can be generalised to target population

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28
Q

Ecological validity

A

Measure and results are generalisable to real world - measuring real life

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29
Q

Null hypothesis

A

No difference, no correlation between variables

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30
Q

Alternate hypothesis (one tailed)

A

Directional, specific
e.g. longer the hours revising, the more better the results

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31
Q

Alternate (two tailed)

A

There will be a difference between the correlations

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32
Q

Structured interviews

A

Structured questions, designed to give a specific answer - often closed questions

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33
Q

Semi structured interviews

A

Contain more open questions can gain a detailed response

34
Q

Unstructured interview

A

Now questions can be added in response to PS answers

35
Q

Simple/random sampling

A

e.g. pulling names out a hat,
+low bias, equal chance
- perfect list of people for sample frame

36
Q

Volunteer/self selecting sampling

A

Questionnaires/flyers sent by post
+ethically good
- only certain types may volunteer, bias

37
Q

Opportunity sampling

A

Takes whoever is available
e.g. researcher directly asks someone to participate
+good sized sample obtained fast
-using whoever is there at present time may mean only certain people feature in experiment

38
Q

Snowball sampling

A

Researcher identifies a person with characteristics they’re interested in then researcher ask people to introduce them to a similar person

39
Q

Stratified sampling

A

Split into groups - gender, race,
+all relevant groups in strata have some representation
-difficult to truly get a representative number for each group

40
Q

Repeated measures

A

PS do all conditions , fewer PS are needed , order effects such as fatigue and boredom affect results

41
Q

Independent measures

A

Sample is divided in groups and each group does one condition, participant characteristics may affect results , more PS needed

42
Q

Matched pairs

A

Not possible to match all PS characteristics , matching PS is time consuming, sample divided into groups matched for their characteristics each group only does one condition , order affects do not occur as PS do only one condition

43
Q

Naturalistic observations

A

Allowing to observe natural behaviour

44
Q

Controlled observations

A

Controls all factors which may alter behaviour

45
Q

Participant observation

A

Observers part of or pretending to be part of group they’re observing

46
Q

Non- participant observation

A

Observer not part of group being studied

47
Q

Unstructured observation

A

Observer records/report behaviour gain a lot of data

48
Q

Structured observation

A

Observers structured observation to meet the aim

49
Q

Covert observation

A

Participants unaware they are being observed

50
Q

Overt observation

A

Participants aware they’re are being observed

51
Q

Field experiment

A

Natural, everyday setting - researcher manipulates IV records affect DV

52
Q

Lab experiment

A

High controlled environment, manipulates IV records effect on DV

53
Q

Natural experiment

A

Naturally occurring IV, researcher records affect on DV- takes advantage of pre existing IV

54
Q

Quasi experiment

A

Naturally occurring IV

55
Q

Deception

A

Deliberately misleading a PS withholding information, false info given

56
Q

Informed consent

A

PS not under pressure to participate

57
Q

Debrief

A

Make PS fully aware of what has actually happened , offer sources for wellbeing

58
Q

Confidentiality

A

PS info in held confidential not publicised

59
Q

Right to withdraw

A

PS can leave experiment and withdrawal at any time

60
Q

Protection from harm

A

PS protected from being harmed from experiment

61
Q

Extraneous variable

A

Anything other then the IV which is not manipulated but has effect on the DV

62
Q

Confounding variable

A

Extraneous variable but has a negative impact on the results

63
Q

Social desirability bias /demand characteristics/social desirable responses

A

PS give untruthful answers (please and screw -U effects)
responses that PS think they ought to give even if they are not true

64
Q

Order effects

A

e.g. tiredness , fatigue, illness- positioning of Qs and tasks can have an influence on the outcome (loftus and palmer misleading Qs avoided this)

65
Q

Situational variables

A

Extraneous type- e.g. noise, light, temperature - environment of where the study is conducted

66
Q

Participant variables

A

Extraneous type- e.g. tiredness, age, gender personality , disabilities

67
Q

Experimental variables

A

Extraneous type- egg female researchers may gain different results from male researchers
- concern in appearance, personality of researcher
needs control

68
Q

Correlation co-efficient

A

Co-efficient of 0.00 means there is no relationship between variables - number between +1 and -1

69
Q

Mode

A

Most common, counting which occurs most frequently
+can be used with nominal data
-data can have several modes

70
Q

Mean

A

Average, add all numbers and divide by how many there are
+makes use of all numbers in the data
-only used with certain types of data-ratio/interval

71
Q

Median

A

Central value, arranging scores in order to find the midpoint
+not affected by extreme scores, can be used with ordinal data
-not as sensitive as mean
-not all values reflected

72
Q

Range

A

Measure of a spread of scores, difference between high-low (arrange in order first) +1 always
+easy to calculate shows extreme values
-affected by extreme values, does not take into account number of observations in the data set

73
Q

Standard deviation

A

Measure of a spread of data around the mean- higher value , more variation in scores
+gives more precise and sensitive measure of dispersion then the range
+all values taken into account
-more complicated to calculate then range-may hide some characteristics of the data

74
Q

Type 1 error

A

Made when were accept a hypothesis when in fact we should have rejected it- this can happen when level of significance is too low

75
Q

Type 2 error

A

When we reject a hypothesis when we should have rejected it-can happen if level of significance is too high

76
Q

Content analysis

A

Method by which you take qualitative data and analyse it in order to draw conclusions

77
Q

Bar chart

A

Used to represent ‘discrete’ data , in categories on x-axis
mean frequency on y-axis
columns do not touch and have equal width and spacing

78
Q

Frequency polygons

A

Can be sued as alternative to histogram
lines show where midpoints of each column on a histogram would reach
particularly useful for comparing two or more conditions simultaneously

79
Q

Histogram

A

Used to represent data on a continuous scale
columns touch because each one forms a single score on a related scale
e.g. time
scores(intervals)placed on x-axis
height of column shows frequency of values

80
Q

Scatter diagram (correlation)

A

Used for measuring the relationship between two variables
data from one variable is presented on the x-axis while other is presented on y-axis
we plot an ‘x’ on graph when two variables meet
pattern of plotted points reveals different types of correlation
e.g. positive, negative or no correlation

81
Q

Cross-sectional study

A

Type of observational study that analyses data collected from a population, at a specific time