Research Methods Flashcards

1
Q

Operationalise meaning

A

Ensuring that variables are in a form that can easily be tested

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2
Q

Standardised procedures

A

A set of procedures that are the same for all participants in order to be able to repeat the study

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3
Q

Repeated measures limitations

A

ORDER EFFECT —>
Practice effect - do better on the second test
Boredom effect - do worse on the second test due to boredom

GUESS CAUSE- on the second test participants may guess the purpose of experiment, change behaviour

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4
Q

Repeated measures dealing with limitations

A

PRACTICE EFFECT - use two different tests - though the two tests must be equivalent

ORDER EFFECTS - counterbalancing (reversing the order)
GEUSS THE AIM- cover story about aim used

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5
Q

Independent groups limitations

A

Participant variables - act as a confounding variables

Need more participants

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6
Q

Independent groups dealing with

A

Randomly allocate participants to deal with personal differences

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7
Q

Matched pairs issues

A

Time consuming

Cannot control all participant variables as only match on variables KNOWN to be relevant

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8
Q

Matched pairs dealing with

A

Restrict no. Of variables to match

Conduct a pilot study to identify all key variables

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9
Q

Lab experiment limitations

A

IV/DV may be operationalised in a way that doesn’t represent every day experiences( lacks mundane realism) - leads to low ecological validity

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10
Q

Field experiment strengths

A

Participants likely to be unaware - no demand characteristics

In natural environment -> more relaxed

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11
Q

Natural experiment

A

When it is not possible (ethically or practically) to deliberately manipulate an IV - it varies ‘naturally’

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12
Q

Quasi experiment

A

IV is too naturally occurring. Has not been made to vary by anyone however, it simply exists (gender)

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13
Q

Quasi experiment STRENGTHS and WEAKNESSES

A

STRENGTHS - allows comparisons between types of ppl

WEAKNESSES - participants may be aware of being studied - demand characteristics/reduced internal validity

  • dependant variable may be artificial task-reduces mundane realism
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14
Q

Investigator effects

A

Any cues from an investigator that might encourage behaviours in the participant and which lead to the fulfilment of the investigators expectations

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15
Q

SONGLE BLIND DESIGN
DOUBLE BLIND DESIGN
EXPERIEMENTAL REALISM

A

SBD- participant not aware of aims and/or conditions they will receive - stops them seeking cues

DBD- participant and experimenter blind to aims/hypothesis. Less likely to give or receive cues

ER- task sufficiently engaging that participant only pays attention to task

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16
Q

Stratified sample

A

Subgroups within a population are identified. Participants are obtained from each group in accordance to their groups proportion in the population

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17
Q

Systematic sampling

A

Using a predetermined system to select participants such as the nth. Person in a phone book.

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18
Q

Opportunity sampling STRENGTHS AND WEAKNESSES

A

STRENGTHS - easy and quick

LIMITS - inevitably bias as sample drawn from a small proportion of population

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19
Q

Random sampling Strengths and weaknesses

A

STRENGTHS - unbiased - equal chance of selection

WEAKNESSES - time consuming - need every member of population included

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20
Q

Stratified sampling strengths and weaknesses

A

Strengths - most representative as is proportional as randomly selected

Weaknesses- very time consuming to identify subgroups and randomly select

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21
Q

Systematic sampling STRENGTHS WEAKNESSES

A

STRENGTHS- unbiased

Weaknesses- no truly unbiased/random unless you start by selecting a number using a random method and then do this method afterwards

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22
Q

Volunteer sampling STRENGTHS WEAKNESSES

A

STRENGTHS- give access to variety of participants making sample more representative and less biased

WEAKNESSES- biased as participants may be more motivated and/or with extra time on their hands. Leads to volunteer bias

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23
Q

Ethical issues

A

Informed consent
Deception (cannot deliberately give false information)
Right to withdraw
Protection from physical and psychological harm
Confidentiality
Privacy

24
Q

Dealing with ethical issues

A

Ethical guidelines (BPS ethical guidelines)
Cost benefit analysis
Ethics committees
Punishment (barred from psychological practice)

25
Q

Naturalistic observation

A

Situation where everything has been left as it normally is - researcher does not interphere

26
Q

Controlled observation

A

Some variables in environment are regulated - participants more likely to know they are being studied

27
Q

Overt observation

A

Aware of observation

28
Q

Covert observation

A

Not aware of observation

29
Q

Non participant observation

A

Observer merely watching

30
Q

Participant observations

A

Observer participating

31
Q

Unstructured observations

A

Researcher records all relevant behaviour- no system

ISSUE - too much to record, most behaviour caught would be most eye catching (may not be relevant)

32
Q

Structured observations

A

Observational techniques are objective and rigorous

Two types: behavioural categories, sampling procedures

33
Q

Behavioural catagories

A

Breaking down actions into specific observation groups (I.e different facial expressions)

34
Q

Sampling procedures

A

EVENT SAMPLING - counting no. Of times certain behaviour occurs

TIME SAMPLING - recording behaviours in a given time frame

35
Q

STRENGTHS WEAKNESSES questionnaires

A

STRENGTHS- can be distributed to large no. Cheaply and quickly
- more willing to give personal information that in an interview (less self conscious

LIMITATIONS- biased towards ppl who can read/write and have time

36
Q

Structured interview

A

Pre determined questions

Questioned in real time

37
Q

Unstructured interview

A

New questions are developed over the course of the interview

Interview begins with general aims

38
Q

Structured interview STRENGTHS WEAKNESSES

A

STRENGTHS- easily repeated - answers from different ppl can be compared
Easier to analyse that unstructured, as answers more predictable

WEAKNESSES- interviewers expectations may influence the answers the interviewees gives
- compatibility may be difficult if interviewer behaved differently

39
Q

Unstructured intervention STRENGTHS WEAKNESSES

A

STRENGTHS - more detailed information obtained

LIMITATIONS- interviewers require more skill to develop questions on the spot - these ppl are more expensive
- questions may lack objectivity than the predetermined as they have no time to reflect on what to say

40
Q

Questionnaire construction

A
  • clarity
  • bias
  • analysis (closed questions)
  • filler questions (distraction)
  • sequencing (easy to hard questions)
  • pilot study
41
Q

Correlations

STRENGTHS WEAKNESSES

A

STRENGTHS- investigate trends in data. If correlation significant, further investigation justified
-easily repeated

WEAKNESSES- cannot assume causal conclusions, only correlations conclusions
- intervening variables may be the cause for the trend in data, and connect the co variables that are studies

42
Q

Content analysis

A

Observational study where behaviour is observed indirectly in written/verbal material such as interviews, conversations, books, dairies or TV programmes

43
Q

Meta analysis STRENGTHS WEAKNESSES

A

STRENGTHS- reviewing results from multiple studies increase validity of conclusions drawn
-often a group of studies on a similar topic have different results. Can reach an overall conclusion using MA

LIMITATIONS - research designs may vary between studies, so the studies are no longer truly comparable

44
Q

Content analysis STRENGTHS WEAKNESSES

A

STRENGTHS- based in observations - high ecological validity
- when sources can be accessed by others, findings can be replicated

WEAKNESSES- observer bias reduces objectivity/validity because different observers may interpret observations differently

45
Q

Case study WEAKNESSES STRENGTHS

A

STRENGTHS - rich in-depth data
- useful in researching human behaviour that is rare

WEAKNESSES- difficult to generalise from individual cases

  • often use recollection of past event - may be unreliable data
  • case studies are only identified after an event has occurred - cannot be sure changes were not already present
46
Q

Measures of central tendency

A

Mean median mode

47
Q

Measures of dispersion

A

Range standard deviation

48
Q

Nominal data

A

Data in separate categories (I.e fave footie teams)

49
Q

Ordinal data

A

Data ordered in a specific way. Intervals between data not the same. (I.e orders in how much they like their fave footie teams)

50
Q

Interval data

A

Data measured using units of equal intervals ( I.e counting no. Of correct answers)

51
Q

Standard deviation

A

Measure of the average distance between each data item above and below the mean, ignoring plus or minus values

52
Q

Standard deviation STRENGTHS WEAKNESSES

A

STRENGTHS - is a precise measure of dispersion because it takes all the exact values into account

WEAKNESSES- may hide some characteristics of the data set

53
Q

Histogram

A

Areas within the bar chart must be proportional to the frequencies represented. No gaps between bars

54
Q

Quantitive v qualitative data

A

Quantitive - how much or how long, how many etc. (Numbers)

Qualitative - Can’t be counted but can be put into categories then counted . What ppl think/feel (words)

55
Q

Primary v secondary data

A

Primary - data observed/collected from first hand experience . Can be collected using an experiment

secondary - information that was collected for a purpose other than the current one (I.e data collected for a different study, government statistics)

56
Q

One tailed v two tailed

A

One tailed- directional hypothesis - know which direction experiment going

Two tailed - non directional hypothesis - experiment goes in both ways