Psychology - Research methods

0.0(0)
learnLearn
examPractice Test
spaced repetitionSpaced Repetition
heart puzzleMatch
flashcardsFlashcards
Card Sorting

1/176

flashcard set

Earn XP

Description and Tags

AQA A-level Research Methods

Study Analytics
Name
Mastery
Learn
Test
Matching
Spaced

No study sessions yet.

177 Terms

1
New cards

experiments

can identify an IV (change) and DV (measure)

2
New cards

types of experiment

  1. lab

  2. field

  3. quasi

  4. natural

3
New cards

how to identify lab experiments?

  • IV been manipulated by the researcher

  • takes place in an artificial place/is an artificial task

4
New cards

advantages of lab experiments

  1. high levels of control so more certain about cause + effect

  2. high internal validity

  3. easy to replicate as standardised procedure

5
New cards

disadvantages of lab experiments

  1. lacks ecological validity as cannot be applied to a range of real world situations

  2. lacks mundane realism

  3. chance of demand characteristics

6
New cards

how to identify field experiments?

  • IV been manipulated by research

  • isn’t an artificial task or in an artificial place

7
New cards

advantages of field experiments

  1. higher mundane realism

  2. reduced demand characteristics

  3. high external validity

8
New cards

disadvantages of field experiments

  1. lack of control over extraneous variables - causality is difficult and less precise

  2. ethical issues - no consent so might be invasion of privacy

9
New cards

how to identify quasi experiments?

  • IV not manipulated by researcher because it CAN’T be manipulated

10
New cards

advantages and disadvantages of quasi experiments

depends on setting taking place in e.g. if was artificial or natural setting

11
New cards

how to identify natural experiments?

  • IV not manipulated by researcher but it COULD be

12
New cards

advantages of natural experiments

  1. high external validity

  2. provide research opportunities that may not otherwise be possible for practical or ethical reasons

13
New cards

disadvantages of natural experiments

  1. rare

  2. hard to replicate

  3. lack of control

  4. participants cannot be randomly allocated to experimental conditions

14
New cards

aim of research

a general statement of the purpose of the research

15
New cards

hypothesis

a precise and testable statement about the assumed relationship between variables

  • MUST operationalise DV and give both conditions for the IV

16
New cards

directional hypothesis

“the (DV) in the (IV condition 1) is better/faster/bigger/less/fewer etc. than the (DV) in the (IV condition 2)”

17
New cards

undirectional hypothesis

“There is a difference between (IV condition 1) and (IV condition 2)”

18
New cards

hypothesis for correlation

“there is a positive/negative relationship/a relationship between (both co variables)”

19
New cards

null hypothesis

no relationship between 2 variables

20
New cards

random sampling

every member of the target population has an equal chance of being selected e.g. obtain all names of population, write on separate pieces of paper and draw the number required for the sample

21
New cards

adv of random sampling

least biased so representative of the target population

22
New cards

disadv of random sampling

still a chance it could produce a biased sample and is time consuming

23
New cards

systematic sampling

taking every nth person from a list of the population e,g, select every 10th person

24
New cards

adv of systematic sampling

unbiased method and it is likely to be representative (results = generalizable)

25
New cards

disadv of systematic sampling

by chance could generate a biased sample

26
New cards

stratified sampling

subgroups (or strata) identified within the population and then random samples are taken from each strata

  • must know the proportions of the strata and then calculate how many people necessary and then pull necessary number out of a hat

27
New cards

adv of stratified sampling

more representative as there is a proportional representation of subgroups

28
New cards

disadv of stratified sampling

time consuming

29
New cards

opportunity sampling

makes use of people readily available and willing to take part

30
New cards

adv of opportunity sampling

quick and easy as no actual selection process and is sometimes the only available possible method

31
New cards

disadv of opportunity sampling

inevitably biased as the sample is drawn from a small part of the population

32
New cards

volunteer sampling

people volunteer or put themselves forward for research in response to a newspaper or on an advertisement

33
New cards

adv of volunteer sampling

fairly quick and easy and can target specific participants who are required

34
New cards

disadv of volunteer sampling

not likely to be representative of a target population as volunteers tend to be a certain type of person e.g. confident

35
New cards

pilot study

small-scale trial run of a research design in order to find out if any aspects of the design do not work - can be adjusted preventing large amounts of time and money being wasted

36
New cards

pilot studies in observations

make sure the behavioral categories are suitable, observers are consistent in what they see and interpret behaviors in the same way and cannot be seen

37
New cards

pilot studies in questionnaires/interviews

questions can check to be clear, unambiguous, not misleading and not offensive

38
New cards

pilot studies in experiments

check experimental design is suitable, instructions are clear and check if demand characteristics could become a problem

39
New cards

independent group design

each group of participants completes one condition

40
New cards

adv of independent group design

less chance of demand characteristics and order effects as only complete one condition

41
New cards

disadv of independent group design

potential problem of participant variables as different people and twice as many participants needed (increases time and money spent)

42
New cards

how to deal with participant variables

random allocation

  1. names out of a hat

  2. evenly distributes participant characteristics across the conditions of the experiment used random techniques

  3. put names into hat, 1st into one, 2nd into the other until all assigned to a group

43
New cards

repeated measures design

one group of participants completes both (all) conditions of the experiment

44
New cards

adv of repeated measures design

no problem of participant variables as same people and less participants needed

45
New cards

disadv of repeated measures design

more chance of demand characteristics and order effects

46
New cards

how to deal with order effects?

counterbalancing

  1. participants split in half

  2. one half do condition 1 then 2

  3. other half do condition 2 then 1

47
New cards

matched pairs design

two groups of participants are matched to each other on relevant characteristics then one from each pair completes one condition

48
New cards

adv of matched pairs design

less problem of participant variables as similar people and less chance of demand characteristics and order effects as one condition only

49
New cards

disadv of matched pairs design

time consuming to match participants and may not be entirely successful (unless identical twins)

50
New cards

behavioural categories

used as a ‘checklist’ as the behaviour is observed in an observation - impossible to analyse a whole stream of behaviour and needs to operationalise behaviour (tally chart)

51
New cards

time sampling (observation)

observations made at regular time intervals (e.g. every 10 mins for an hour) and record any behaviour occurring (good if one participant and want a comprehensive idea of their behaviour)

52
New cards

event sampling (observation)

observation lasts for a certain length of time and includes the whole time so don’t miss any behaviours - use of categories and tally behaviour

53
New cards

closed questions

choice of pre-determined answers e.g. yes, no, strongly agree etc (always include these options)

54
New cards

adv of closed questions

easier to analyse and represent in a graph

55
New cards

disadv of closed questions

not always representative as may not be one of the options etc.

56
New cards

open questions

allows the respondent to answer in their own words

57
New cards

adv of open questions

more descriptive and involve the collection of qualitative data and often quantified using content analysis

58
New cards

disadv of open questions

difficult to analyse due to range of results so time-consuming

59
New cards

design of interviews

  1. how will it be recorded?

  2. interviewer effects may impact outcome so must consider characteristics

60
New cards

operationalisation

making variables measurable

61
New cards

extraneous variables

unwanted variables that could affect DV so must be controlled (may confound/confuse the results)

62
New cards

examples of extraneous variables

  1. participant variables (IQ, age etc.)

  2. environmental variables (distraction, noise etc.)

  3. experimenter variables

63
New cards

confounding variables

uncontrolled extraneous variables that confuse the results by affecting the DV

64
New cards

standardisation

controlling the extraneous variables - same room, same experimenter, same instructions

65
New cards

randomisation

present all conditions muddled up so the order occurs by chance

66
New cards

participant effects

if know they are being studied they may behave differently due to social desirability bias

67
New cards

demand characteristics

participants try to figure out the aim of the study and act accordingly so may be too cooperative etc.

68
New cards

single blind procedure

participants are not fully informed of the true nature of the research

69
New cards

investigator effects

influencers may influence the participants e.g. leading questions

70
New cards

double blind procedure

participants and investigator unaware of the research aim

71
New cards

informed consent (ethical issues)

participant must be told sufficient details so make their own choice (may cause participant variables = cause deception where incorrect details given or information withheld)

72
New cards

how to deal with informed consent

  1. presumptive consent - gained from similar group of people

  2. prior general consent - agree to be deceived without knowing how

  3. retrospective consent - asking participants after they have participated (ONLY if confident yes)

  4. debriefing - occurs after the study and involves giving all relevant details including aim of study

73
New cards

protection from harm (ethical issues)

protected from physical and psychological harm e.g. anxiety, lowered self-esteem - leave in same state they arrived in

74
New cards

how to deal with protection from harm

debriefing - occurs after the study and may include support/counselling as required if participant are harmed

75
New cards

right to withdraw (ethical issues)

should be able to leave the study at any time even if agreed to continue

76
New cards

how to deal with the right to withdraw

state this option at the start and remind them during the study - be paid for their contribution even if they drop out

77
New cards

confidentiality (ethical issues)

all data should be protected and kept confidential and must agree if information published

78
New cards

how to deal with confidentiality

numbers or pretend names used

79
New cards

privacy (ethical issues)

should not be observed if unaware

80
New cards

how to deal with privacy

only occur in public places where a participant could expect to be observed anyway

81
New cards

quantitative data

numerical, lacks detail, from experiments, correlations, observations which use categories and closed questions

82
New cards

qualitative data

non-numerical, rich in detail and occurs through descriptions of behaviours or attitudes e.g. open questions on interview or case studies

83
New cards

mean

adding all the numbers in a set of data and dividing by the size of the sample

84
New cards

median

worked out by first putting all scores in order of size, starting with smallest

85
New cards

mode

score that occurs most often

86
New cards

adv of mean

  1. every bit of data is used in its calculation (sensitive measure) and most accurate

  2. measure of central tendency that should be used with interval data

87
New cards

disadv of mean

  1. distorted by extreme scores (outliers)

88
New cards

adv of medians

  1. not distorted by extreme scores (outliers)

  2. measure of central tendency with ordinal data

89
New cards

disadv of medians

  1. not a sensitive measure as does not include all scores

90
New cards

adv of mode

  1. data is collected in categories (nominal data) so a mean would not make sense

91
New cards

disadv of mode

  1. can be two modes - bimodal or no modal valuerang

92
New cards

measures of dispersion

measure of the (variability) spread of scores

93
New cards

range

subtracting the lowest value from the highest value (smaller = more reliable)

94
New cards

standard deviation

measure of the spread of a set of scores from the mean (larger = larger spread of scores)

95
New cards

adv of range

simple to calculate

96
New cards

disadv of range

distorted by extreme values

97
New cards

adv of standard deviation

sensitive measure as every score is used

98
New cards

disadv of standard deviation

more complicated to calculate as requires a formula

99
New cards

correlational data

ranges from -1.0 to +1.0 (correlation coefficient) - the closer to 0 = weaker the correlation (0.1-0.3 = weak, 0.4-0.6 = moderate, 0.7-0.9 = strong with 1 and -1 being perfect)

100
New cards

scattergrams

display correlationdal data as there is no IV or DV (just co-variables) - cannot establish cause and effect - positive correlation = as one goes up, the other goes up with negative = as one goes up, the other goes down