research methods and statistics Flashcards

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1
Q

what are the two categories self-report can be split into?

A

interview and questionnaire

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2
Q

what is self-report research method?

A

asking paticipants about topic personally for their own report

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3
Q

self-report strengths

A

researchers can obtain participant’s beliefs, emotions and experiences that they could not observe. high validity, more representative of behaviour being measured

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4
Q

self-report weaknesses

A

social desirability bias so pps could lie to give researchers what the pps think they want, lacks validity. data often not generalisable so not representative of full population, not reliable

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5
Q

structured interview

A

pre-set q’s with fixed responses-high reliability but q’s might not be asked in the same way causing lack of consistency

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6
Q

semi-structured interview

A

pre set q’s but no fixed responses- high reliability but open to interpreter bias

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7
Q

unstructured interview

A

no fixed questions or answers- high validity but open to social desirability bias

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8
Q

questionnaires

A

often contains several items to draw information from pps

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9
Q

pilot study

A

small-scale preliminary version of study, primary of questionnaires

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10
Q

pilot study reasons

A

check question clarity, check sample method for representativity, check questions are universally understandable, no leading questions, check questions aren’t upsetting to pps, ensure format has enough room

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11
Q

open-ended questions

A

invite pps to describe and explain providing qualitative data

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12
Q

closed questions

A

provide pps with a limited choice of answers to collect quantitative data

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13
Q

likert scales

A

pps given a scale of several options and must pick the option they agree with most, not just a rating scale but still quantitative data but not reliable as numbers can be interpreted differently

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14
Q

rating scales

A

allow pps to express preferences using numbers but not reliable as numbers can be interpreted differently

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15
Q

experiments

A

manipulation of variables to create ways to measure factors affecting behaviours

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16
Q

laboratory experiment

A

-manipulated iv and measured dv
-controlled variables
-artificial enviro/task
-allocation of pps to groups

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17
Q

field experiment

A

-manipulated iv and measured dv
-controlled variables
-natural enviro/task
-allocation of pps to groups

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18
Q

natural experiment

A

-natural iv and measured dv
-no control of variables
-natural enviro/task
-no allocation of pps to groups

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19
Q

quasi experiment

A

-natural iv and measured dv
-controlled variables
-artificial enviro/task
-no allocation of pps to groups

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20
Q

independent measures

A

variable being manipulated

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21
Q

dependent measures

A

variable being measured for results

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22
Q

operationalising variables

A

defining in very specific terms the variables being tested so that the iv is definitely the cause of the effect (dv)

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23
Q

independent measures design

A

pps only take part in one condition of the experiment

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24
Q

repeated measures design

A

pps take part in all conditions

25
Q

factors affecting repeated measures design

A

task order interferes with pps performance due to practice from previous tasks or fatigue

26
Q

correlation

A

measures relationship between variables

27
Q

positive correlation

A

as one variable increases, so does the other

28
Q

negative correlation

A

as one variable increases, the other decreases

29
Q

zero correlation

A

no relationship between variables

30
Q

example one-tailed hypothesis

A

there will be significantly more of variable a observed than variable b

31
Q

example two-tailed hypothesis

A

there will be a significant relationship between variable a and variable b

32
Q

example null hypothesis

A

there will be no significant relationship between variable a and variable b and any relationships observed with be up to chance

33
Q

strengths of correlation

A

-can be used in place of experimental manipulation that would otherwise be unethical or impossible
-when only one variable is known, the other variable score can be predicted

34
Q

weaknesses of correlation

A

-cannot predict cause and effect
-relationship may be affected by extraneous variables

35
Q

observation

A

process of watching and recording pps behaviours

36
Q

overt observations

A

pps know they are being watched

37
Q

covert observations

A

pps don’t know they are being observed during the research

38
Q

participant observation

A

researcher is involved and participating in the research

39
Q

non-participant observation

A

researcher is not part of activity or group or behaviour being observed

40
Q

structured observation

A

some variables controlled by the researcher and usually carried out in lab conditions

41
Q

naturalistic observation

A

pps watched in their natural environment and behaviour recorded as it happens without manipulation

42
Q

observation behaviour sampling techniques

A

researcher must decide intervals at which behaviours will be recorded and what specific behaviours will be recorded which can yield qual and quant data

43
Q

observation time sampling

A

recording set behaviour at set time intervals

44
Q

observation event sampling

A

recording every instance of specific behaviour every time it happens rather than at specified instances

45
Q

content analysis

A

allows analyzing of written communication such as lengthy texts which can be broken down into manageable units of data so it can be converted into qualitative or quantitative data

46
Q

content analysis strengths

A

reductionist as it converts complex text into numbers and standardised so more reliable

47
Q

content analysis weaknesses

A

open to researcher bias so they might only utilise data that aligns with hypothesis and qualitative data can be interpreted differently

48
Q

case study

A

studies singular pps or small groups looking at unique characteristics and behaviours

49
Q

case study strengths

A

allow in depth investigation and triangulation of various data forms and allow unique, one-off situations so pps can be better protected from harm

50
Q

case study weaknesses

A

only generalisable to specific individuals and often effected by desirability bias

51
Q

longitudinal research

A

investigation of the same group of pps behaviours on numerous occasions over an extended period of time

52
Q

longitudinal research strengths

A

ind diff removed as confounding variable is measured so high validity. good way of showing how ind behaviours develop over time

53
Q

longitudinal research weaknesses

A

pps often drop out of the research over time making data less consistent. open to interpreter bias as relationships can form over the long periods

54
Q

cross sectional research

A

collection of a variety of types of pps at a single moment in time to compare development amongst different ppl. often used to assess cultural or background

55
Q

cross sectional research strengths

A

take into account a wide range of diff pps at one moment in time so high pop val. easier to control variables due to being carried out in a single moment in time so more valid

56
Q

cross sectional research weaknesses

A

affected by ind diff in the diff groups of ppl. difficult to replicate due to wide range of pps so low reliability

57
Q

meta analysis

A

a review of secondary data, not a study itself

58
Q

meta analysis strengths

A

allows many different sources to be used so more holistic. does not create ethical issues so doesn’t harm pps because there are none directly

59
Q

meta analysis weaknesses

A

open to researcher bias as they could just only use the studies that support their hypothesis. no direct control over how previous research was conducted