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Psychology A-level > Research methods > Flashcards

Research methods Flashcards

1
Q

main methods

A
  • experiments
  • observation
  • self-report
  • correlations
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2
Q

other methods

A
  • meta analysis
  • case studies
  • content analysis
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3
Q

introduction

experiments

A
  • main methods
  • allows mesurement of one variable or another
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4
Q

introduction

IV

A

change
(ndependant ppl can change)

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5
Q

DV

A

mesure

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6
Q

introduction

observation

A
  • aim is to watch the behaviour without manipulation
  • removes bias and increases validity as this is their natural behaviour
  • e.g. watching cctv cameras, two sided mirror
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7
Q

introduction

self- report

A
  • questionares
  • interviews
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8
Q

introduction

correlation

A

(most forgotten)
- rather than seeing jwo one variable affects the other we see if two variables are associated
- e.g. do students who study longer get better gradees
- scatter graph/gram used

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9
Q

meaning

reliable

A

consistencey

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10
Q

meaning

vaild

A

accuracy

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11
Q

direcrtional

A

when the direction of the difference has

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12
Q

non-directional

A

when the direction of the difference has

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13
Q

3 criteria for obseration

A

covert/overt
non/ppt
control/natural

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14
Q

natural

A

watching and recordng behaviour in setting where it would naturally occur e.g. nature documentary
+less demand characteristics and socai desirability
+ high ecological validity
- cant control extraneous variables
- hard to replicate, unreliable?

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15
Q

controlled

A

watching and recording behavir within a structured envroment where variables controled e.g. zimbardo
+ can control extraneous variables
+ easier to replicate, reliable
- demand ch, social d

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16
Q

overt

A

watching and recording when ppts know they are bieng watched e.g. cctv
+ less ethical issues
- higher chance of ppt reactvity

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17
Q

covert

A

observing and recorning without ppts nowledge e.g. hidden cameras, tea room trade
+high ecological validity
- ethical issues
- psychological harm, anxiety

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18
Q

ppt

A

when researcher disguses themselves into the group they are oserving e.g. jake perulta
+increased insight
+may increase validity
- subjectivity
- deception

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19
Q

non ppt

A

when researcher remains outside of the group they are watching e.g. invidulator
+more objective
- may miss out on valuable insgight

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20
Q

observational desgign

unstructured

A

when reseracher records everything they see
+qualitative
- hard o may attention to everything

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21
Q

Behavioural categories

A

when a target behaviour is broken into components that are observable and measurable and specific
e.g. leaving the room, laughing

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22
Q

practice behavioural categories

anger

A

shouting
clenched fists
arched eyebrows

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23
Q

practice behavioural categories

affection

A

smiling
hugging
holding hands

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24
Q

observational design

sampling methods

A

refers to how often data is recorded, not how ppts are selected

event
time

intervals in time sampling refer to the tine between observations not te

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25
Q

sampling method

event sampling

A

counting the number of times a particular event occours

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26
Q

sampling method

time sampling

A

recornig behaviour within a pre-established time frame e.g. every 30 seconds

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27
Q

Inter-oserver reliability

A

this is when 2 or more observers make consistent judgment about the data they recorded
1. carry out pilot study using behavioural categories
2. collect observed data from both observations (independantly)
3. check for a correlation between the two sets of data
4. is there’s a strong correlation theer is a high inter observer reliability

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28
Q

A03

structured

A

quantitative
numerical results, less detail, easy to compare

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29
Q

A03

non structured

A

qualitative data
more detail, observer bias

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30
Q

A03

behavioural categories

A

+structured, less open to interpretation
findings are more objective
- overlapping categories e.g. offensive language, sweraing
- dustbin categories
- missed out categories

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31
Q

A03

event sampling

A

+useful when the target behaviour is infrequent
- we may overlook other important information if we are too focued on one e.g. fixated on one child in play ground

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32
Q

A03

Time sampling

A

+less observations need to be made so less overwhelming, fresh eyes, qyicker analysis
- we may miss important events during the intervals so data doesnt have high internal validity

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33
Q

Pilot study

A
  • a small-scale trail run of the investigation
  • the study is initially conducted with a small sample to check that the procedure & materials are appropriate
  • this is also done with TV shows

+ gives us oppurtunity to improve the study
+ ensures that study runs smoothly
+ saves us time, money and effort

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34
Q

stats we use to describe trends/ patterns and differences in data

A
  • moCT: mean, median,mode
  • measures of dispersion: range, IQR
  • reading & interpreting graphs, tables, bar, line
  • graphical displays
  • dispersion
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35
Q

Distribution

A

the dpread of frequency data for a particular variable (how data is distributed)
types: normal/skewed (positively or negitively)

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36
Q

why look at distribution

A
  • tells us about the frequency data for a particular variable across a particular population
  • it can show differences across populations and is used to identify statistics infrequently
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37
Q

Distributions

what i need to know

A
  • definition of each type
  • how to draw a distribution using moct
  • interpreting distribution based on measures of centeral tendancies, may include describing how the distribution may be skewed, or comparing distributons from different data sets
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38
Q

Normal distribution

A

a symetrical spread of frequency that forms a bell-shaped curve. The mean, median and mode are all located at the highest part if teh curve
[see physical card]

39
Q

Skewed distribution

A

a spread of frequencey data that is not symmetrical, where data clusters to one end

40
Q

Explain why the psychologist did a pilot study

A

To test whereter ppts understand standerdised intructions, timing, so they can make adjustments before the real study to save time and money

41
Q

Discriptive statistics

A

the use of graphs, tables and summary statistics to analyse trends and sets of data
- measures of centeral tendancies
- measures of dispersion

42
Q

measures of centeral tendancies

A

the general term for any measure of the average value in a set of data

43
Q

measures of dispersion

A

how far scores vary and differ from one another (the spread of scores)

44
Q

the measures

A

CT- mean
- mode
- median

D- range
- standard deviation

45
Q

mean

A

the arithmetic average calculated by adding up all the values in a set of data and diving by the number of valuses there are

46
Q

median

A

the centeral value in a set of data when values are arranged from lowest to highest

47
Q

Experimental design

A
  • the different ways in which the testing of ppts can be organised in relation to experimental conditions
    e.g. independant groups, repeated measures, matched pair
48
Q

Independant groups

A

ppts are allocated to different groups wjere each group represnets one condition
- when having more than 1 group we usually have an experimental condition and a controlled condition
- ppts will be split and accolated to one of the two groups
- this mean that all ppts only experience one condition each
- scores/behaviour from each group will then be compared
- mean+compare

49
Q

Repeated measures design

A

all ppts take part in all conditions of the experiment
- will this design we still have an experimental and control condition
- howerever ppts will take part in all conditions one at a time
- we usually use this meathod to test before/after

50
Q

experimental desgin

controls

A

randomisation
standerdisation
counterbalancing

51
Q

single blind procedures

A

when ppts are unware of what condition/group they’re in

prevents demand characteristics

52
Q

double blind procedures

A

when both participants and researchers are unaware of what condition/ group theyre in

prevents investigator effects

53
Q

controls

Randomisation

A

the use of chance in order to control for the effects of bias when designing materials and deciding the order of conditions
- this is different from random allocation

random allocation only refers to randomly assigning

ppts to thier conditions/groups

54
Q

what should we randomise in an experiment?

A
  • alphabetical order
  • difficulty of words
  • meaning of words

this controls demand characteristics and investigator effects

55
Q

Standerdisation

A

using exactly the same formulised procedures and instructions for all ppts in a research study
- if conditions arent the same for all ppts they may have different experiences, unreliable
- also controls for investigator effects
- e.g. task indtructions, word lists

56
Q

Counterbalancing

A

when ppts in a repeated measues design are split into half with half ppts completeing conditions in reverse order
- we use this control when we have a repeated measures desgin
- aims to prevent the main confounding variable that we may come across using this design

57
Q
A
57
Q

Explain how to counterbalance

A
  • split ppts into 2 groups
  • get the 1st group to complete the conditions in one order
  • get second group to do conditions in opposite order
  • put the data together and compare each condition (not each group)
58
Q

Range and standard deviation

A

both measure the spread of data- standard deviation is just a more sophisticated measure

Rule:
bigger the standard deviation value, the wider the spread of data, more variation in scores/data

smaller the standard deviation value, the closer the spread of data, less variation in scores/data, roughly the same level, less varriation

59
Q
A
60
Q

quantitative

A

data that can be counted, usually given as nmbers
e.g. scores on test
can be analysed statistically and converted into graphs/ charts

61
Q

qualitative

A

data that is expressed in words and non-numerical
e.g. interviews, diary, observation notes
- it may be converted into quantitative later on for further analysis

62
Q

evaluation

qualitative

A

+ richness of detail
+ allows ppts to give thoughts and opinions
+ data tends to be more meaningful
+ high validity
- can be difficult to analayse/ compare
- hard to find trends and patterns
- analysed under subjective interpritaion
- may lead to researcher bias, low internal validity

63
Q

evaluation

quantitative

A

+less subjective
+ easier to analyse
+ conclusions cab be drawn quicker
- may include less detail
- may not fully represent real life/behaviour, lacking external validity

64
Q

Presenation of quantitative data

A
  • tables: usually display the mean and SD for each group
  • bar charts: graphs that show the frequencey of each variable represented by the height of bars
  • scattergraphs: graphs that represent the strength/ direction of a relationship between co variables
65
Q

How to draw a graph

A
  1. labled axis (opperationalised)
  2. descriptive title
  3. labled y axis
  4. correctly plotted data (bar with gaps)
66
Q

Bar charts vs Histograms

A

bar: categorical data e.g. class A vs class B, tall vs short
histograms: bars are connected as data runs on continups scale

67
Q

extraneous variable

A

any variable that has potential to affect the DV
ppt/situational varbles- affect the person/setting

68
Q

confounding

A

any varable that affects only one group/ condition in a study- they vary systematically whin the IV

69
Q

ppt variables

examples

A

fatigue
knowledge of task
energy
concentartion
mood

70
Q

situational variables

examples

A

temp of room
disctracions
noise outside
comfort

71
Q

confounding variables

A

extranous variable that only affects one group e.g. y7’s watching a movie when observing if y9/y7 has better concentration levels

72
Q

Investigator effects

A

anything that a reserahcer may say or do (consciously or subconsiouly) that may influence the behaviour from a ppt
e.g. researchers movment, tone of voice

73
Q
A
74
Q

social desirability

A
  • when ppt changes nehaviour in order to be favoured by others
  • if true answer is taboo/ embarassing you may chnage it to avoid judgment
75
Q

demand characteristics

A

when teh ppt changes thier behaviour de to guessing the aim of the study

76
Q

Leading questions

A

“what do you think about Rishi Sunak?”
“what do you think about our so-called PM Rishi Sunak?”
no longer testing what we aim, low internal validity

77
Q

when is it suitable to carry out a case stdy rather than an experiment

A
  • get more qualitative data
  • in depth
  • specific senarios
  • historical conext
  • things that arent observable/opperationolised
78
Q

case study

A

an in depth, detailed investigationor a small group (victim to the same event)
they use a wide variety of techniques including retrospective data, interviews, observations an psychological testing
they are usually longitudinal (long piecses of reserach) and are carrried out over a long time period

79
Q

evaluation

case studies

strengths

A

+in depth, more qualitative data, high explanatory power
can dis/prove theories, theoretical value
+richer in detail, can explore sensitive topics
can provide direction for new hypothesisies, practical value

80
Q

evaluation

case studies

weaknesses

A
  • low generalisibility, looks at one person, small sample, low population validity
  • retrospective data - may be issues such at data may be outdtated and not useful to modern day
  • must rely on self-report- social desirability/ poor memory, innacurate, low internal validity
  • subjective, bias, investigator effects, researchers may only look into areas they are interested in, low internal validity
  • ethical issues, breach of confientally e.g. uisng their real name psychology harm - acessing trauma
81
Q

types of experiments

lab

A

when reseraher manipulates an IV to test its effect on the DV
e.g. skinner, bandura

82
Q

types of experiments

field

A

when reseraher manipulates an IV to test its effect on the DV in a natural setting
e.g. bus, park

83
Q

evaluation

Natural

A

rely on natral events, so control is limited
the events are real (IV) effects are real, can be sure the Dv is natural, high ecological validity

the events are ratre so you cant check for reliability, no replication

lots of extraneous variables we cannot control, low internal validity

84
Q

evaluation

Quasi

A

+high control (just like lab), high interanl validity

  • we cannot control group allocation
  • if the IV is within ppts we cannot control how we seperate them into groups- there way of existing differences between our groups(other than IV) that affect our stdy
  • these are confounding variables
85
Q

weakness of quasi and natural

A

neither method allows us to establish cause and effect
- the purpose of an experminet is to measure the effect that one varable has on another
- due to lack of control we can never trule know whether it is in fact the IV that changes the DV (it could be the other extranous varibles), this lowers the internal validity

86
Q

evaluation

Lab

A

+high control, minimise extraneous variables, high internal validity
+ easy tp replicate, reliable
+less likely to have ethical issues
- lacks ecological validity, artificl task/setting doenst reflect real life

87
Q

evaluation

Field

A
  • low control, extranous variables low internal validity
  • harder to replicate, real life is unpredictable
  • ethical issues more likely to arise, informded ocnsent, right to withdraw, deception, goes agaisnt BPS guidlenes
    + high ecological valueu, ppts are more likely to behave natually, natral setting/task, reflect real life
88
Q

Natral experiment

A

when change in the IV is not brought about by the researcher (natutrally occuring event)
they just record the effect of teh DV
e.g. number of stdents that applied beofre the fees tripled
how may flights wre ebook ed to ukraine before/after war

89
Q

Quasi

A

when teh Iv pre-exists within ppts and has not been determned by anyone, techinally not a real experiment, no manipukation
e.g. different testosterone levels in males and femals
something thats fixed, IQ

90
Q
A
91
Q

open questions

A

qualitative data
no fixed response
detailed

92
Q

closed questions

A

“yes or no” answers

Psychology A-level (5 decks)

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