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Research Methods Flashcards

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1
Q

What is qualitative data

A

Information in words or pictures; non numerical

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2
Q

Qualitative data - pros

A

+ represents true complexity of human behaviour, thoughts and behaviour is not reduced to numbers — a holistic approach

+ provides rich details of how people think and behave — higher in validity as the researcher is more likely to measure the variable of interest

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3
Q

Qualitative data - cons

A
  • more difficult to detect patterns and draw conclusions, large variety of information collected, words can’t be reduced to simple points
  • interpreting what people mean makes it likely to be subjective, lowering credibility
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4
Q

What is quantitative data

A

Information in numbers, i.e. quantities

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5
Q

Quantitative data - pros

A

+ easier to analyse, data in numbers, using descriptive statistics or inferential statistics

+ more objective measure, more reliable, gives greater credibility

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6
Q

Quantitative data - cons

A
  • May not express participants’ precise thoughts/ feelings because answers provided are fixed — low in validity
  • oversimplifies reality and human experience — reductionist is to reduce human experience to numbers
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7
Q

What is primary data

A

First hand data collected for the purpose of the investigation

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8
Q

What is secondary data

A

Information collected by someone other than the researcher (e.g. books, journals, etc.)

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9
Q

What is random sample

A

A randomly collected sample

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10
Q

Random sample - pros

A

+ unbiased, all members of target population have an equal chance of selection

+ possible to choose a specific subgroup in target population

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11
Q

Random sample - cons

A
  • takes more time and effort (obtaining a list of all target members, identifying them, asking consent)
  • random samples aren’t always random as some might not take part, final may resemble more of a volunteer sample
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12
Q

What is stratified sample

A

Selected from different stratas (subgroups) in proportion to the population

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13
Q

Stratified sample - pro

A

+ most representative, all subgroups represented and in proportion to the numbers in the target population

+ specific subgroups can be chosen according to the variables considered to be important by the researcher

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14
Q

Stratified sample - cons

A
  • deciding the subgroups may be biased
  • a very lengthy process and those selected might not take part — more useful for opinion polls than psychological research
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15
Q

What is a volunteer sample

A

Participants who can volunteer to take part

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16
Q

Volunteer sample - pro

A

+ convenient way to find willing participants (gave informed consent)

+ good way to get a specialised group of participants (purposive sampling)

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17
Q

Volunteer sample - cons

A
  • biased since volunteer participants are more likely to be more highly motivated (volunteer bias)
  • volunteers may be more helpful, higher chance in guessing the aims
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18
Q

What is opportunity sample

A

Those most readily available during the study

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19
Q

Opportunity sample - pros

A

+ most convenient technique — takes little preparation

+ may be the only technique available since target population cannot be listed (like in random and stratified sampling)

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20
Q

Opportunity sampling - cons

A
  • biased since sample is drawn from a small part of the target population might not be representative
  • participants may refuse to take part, making the final sample likely to respond to demand characteristics
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21
Q

What are repeated measures

A

When the participant takes part in all conditions of the study

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22
Q

Repeated measures - pros

A

+ good control of participant variables since the same person is tested twice

+ fewer participants are needed than independent groups design

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23
Q

Repeated measures - cons

A
  • order effects produced, e.g. participants might be better in the second condition after practicing or perform less since they are tired
  • might make it easier for participants to guess the aim of the study
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24
Q

What are independent measures

A

Different participants are allocated to two or more experimental group representing different levels of the independent variable
There may be a control group

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25
Q

Independent measures - pros

A

+ avoids order effects since each participant is only tested once

+ avoids the possibility than a repeated measures design

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26
Q

Independent measures - cons

A
  • no control of participant variables, e.g. participants from group b may be contrastingly different, scoring differently
  • needs more participants than a repeated measures design
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27
Q

What are matched pairs design

A

Participants with similar variables are paired, each in a different group

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28
Q

Matched pairs - pros

A

+ controls for participants through matching — similar to repeated measures

+ avoids order effects since it is similar to independent groups design

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29
Q

Matched pairs - cons

A
  • very time-consuming to match participants on key variables

- may not control all participant variables, only matching variables known to be relevant

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30
Q

What is an experimental hypothesis

A

A statement about the effect of the IV on the DV
Should include both levels of the IV
Should be precise and operationalised

E.g. people who sleep more do better on a memory test
IV: amount of sleep
DV: results of memory test

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31
Q

What is an one tailed directional hypothesis

A

States the direction of the hypothesis

E.g. people who sleep for 8 hours have a higher score on a memory test than those who sleep for 5 hours

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32
Q

What is a two-tailed directional hypothesis

A

States that there is a difference

E.g. .people who sleep for 8 hours will perform differently on a memory test than those who sleep for 5 hours

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33
Q

What is the null hypothesis

A

States that there is no difference

E.g. there is no difference between the memory test scores of people who sleep for 8 hours than those who sleep for 5 hours

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34
Q

What is an experiment

A

A research method which demonstrates casual relationships, all experiments have an IV and DV

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35
Q

What are IV and DV variables

A

IV: a factor directly manipulated by the experimenter to observe the effect of the DV

DV: measured by the experimenter to assess the effects of the IV

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36
Q

What is operationalisation

A

Variables must be operationalised

E.g. operationalising memory would be giving participants the same memory test, the DV would be the memory score

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37
Q

What is a lab experiment (IV and DV)

A

IV manipulated by experimenter: e.g. having them sleep in a lab to control the hours they sleep

DV measured in a laboratory: e.g. a test to measure memory

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38
Q

What is a field experiment

A

IV: manipulated by the experimenter
E.g. telling participants to wake up after 8 hours and conducting the study in home

DV: may be measured in the ‘field’
E.g. the participant’s own home

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39
Q

What are extraneous variables

A

Any variable other than the IV might potentially affect the DV
This includes both participant and situational variables

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40
Q

What are participant variables

A

Characteristic of the participant

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41
Q

What are situational variables

A

The environment that may affect performance

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42
Q

What are confounding variables

A 
Special class of extraneous variables
It changes systematically with the IV, so you cannot be sure that any change int he DV was due to the IV

E.g. study on memory — cannot be sure whether words were remembered better because they are familiar or since they were the first words on the list

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43
Q

What is predictive validity

A

The extent to which a test score is actually related to the behaviour you wanted to measure
Test score can forecast performance on another measure of the same behaviour

E.g. score on a memory test or an IQ test should be positively related to the performance in A level exams

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44
Q

Ecological validity - lab experiment - pros

A

+ high level of control, minimising confounding/ extraneous variables (increasing validity)

+ can be easily replicated because most aspects of the environment is controlled

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45
Q

Ecological validity - lab experiment - cons

A
  • contrived situation where participants may not behave naturally. Low ecological validity
  • demand characteristics and researcher bias/ effects may reduce validity
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46
Q

Ecological validity - field experiment - pros

A

+ less contrived, whole experience has mundane realism, higher ecological validity

+ avoids demand characteristics and researcher bias/ effects if participants’ aren’t aware they’re being studied

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47
Q

Ecological validity - field experiment - cons

A
  • less control of extraneous variables, reduces validity
  • may be more time consuming since experimenters have to set up a field experiment (more expensive)
  • may have ethical issues if covert observation is used
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48
Q

What is a questionnaire

A

Respondents record their own answers, there are predetermined questions, prepared in a written form and there is no face-to—face contact

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49
Q

Questionnaire - pros

A

+ self-reports finds out what people think and feel

+ can be easily repeated so data can be collected from large numbers of people

+ respondents may feel more willing to reveal personal information when it is anonymous

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50
Q

Questionnaire - cons

A
  • might not always tell the truth, social desirability bias

- the sample may be biased since only certain types of people would fill out the questionnaire

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51
Q

What are closed questions (and the type of data they collect)

A

Fixed number of possible answers

Collect quantitative data

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52
Q

Closed questions - pros and cons

A

+ easy to analyse quantitative data since numbers can be summarised through using statistics
+ answers more objective

  • many not permit people to give their precise feelings, lacks validity
  • oversimplifies reality and human experience — reductionistic
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53
Q

What are open questions (and the type of data they collect)

A

Respondents to provide their own answers

Collect qualitative data

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54
Q

What are ranked scales (and the type of data they collect)

A

To give an assessment using a scale (e.g. 1-5)

Collects quantitative data

55
Q

Ranked scales - pros and cons

A

+ reasonably objective way to represent feelings and attitudes related to the topic being researched
+ produces quantitative data, easy to analyse

  • participants may prefer to respond the same way to all scales regardless of context
  • social desirability bias in responses
56
Q

What are structured interviews

A

Predetermined questions in an interview

57
Q

Structured interviews - pros and cons

A

+ can be easily replicated
+ easier to analyse than unstructured interviews
+ interviewer can provide extra information

  • interviewer’s expectations may influence the answers the interviewee gives (researcher bias)
  • participants may be reluctant to reveal personal information in face-to-face interviews
58
Q

What are semi-structured interviews

A

When there are a mix of predetermined questions and developed questions (by the interviewer during the interview)

59
Q

Semi-structured interview - pros

A

+ more detailed information obtained since questions can be tailored to the participant

+ can access information that may not be revealed by predetermined questions

60
Q

What are unstructured interviews

A

No questions prepared in advance

61
Q

Unstructured interview - cons

A
  • more affected by interviewer bias, since interviewer creates questions on the spot, they may ask leading questions
  • requires well-trained interviewers, may be difficult to obtain, making it more expensive
62
Q

Questionnaires > interviews

A

Can be given out to lots of people, collecting a large amount of data (interviews takes more time to conduct interview and employ people)

Participants more willing to reveal confidential information since there is no face-to-face contact

63
Q

Interviews > questionnaires

A

People may reveal more information with a skilled interviewer to encourage thoughtful responses

Semi-structured/ unstructured interviews: can access more information that may not be revealed by predetermined questions

64
Q

What is observational research

A

Watching or listening to what participants do

65
Q

Observational research - pros and cons

A

+ what people say they do is different from what they actually do, observing their behaviour possibility has greater validity

  • observers may only ‘see’ what they expect to see
  • observations can’t provide information on what they think
66
Q

Collecting qualitative data in observational research

A

Often through recording everything (writing it down or recording it through tape)

67
Q

Collecting qualitative data in observational research - pros and cons

A

+ first step in creating a structured, qualitative system for classifying observations. Thematic analysis can be used to create behavioural categories

  • behaviours recorded might only be the visible or eye-catching ones
68
Q

What are behavioural categories

A

Objective measures to separated continuous streams of actions
E.g. listing out several different kinds of behaviours and tallying them when it has been observed

69
Q

behavioural categories - pros and cons

A

+ enables systematic observations to be made so important information isn’t overlooked, enhances validity
+ categories can be tallied and conclusions drawn

  • categories may not cover all possibilities, some behaviour not recorded (low validity)
70
Q

What is event sampling

A

Tallying behaviours in a specified time period

71
Q

What is time sampling

A

Counting behaviour at regular intervals

72
Q

Event and time sampling - pros and cons

A

+ both methods make observing behaviour more manageable by taking a sample
+ useful when behaviour to-be-recorded only happens occasionally, missing events would reduce validity
+ time sampling allows for tracking time-related changes in behaviour

  • observations may not be representative if list of events is not comprehensive, reduces validity
  • time sampling may decrease validity because some behaviour occurs outside of the observation interval
73
Q

What is participant observation

A

Observer is a participant in the behaviour being observed

E.g. Rosenhan

74
Q

Participant observation - pros and cons

A

+ provide special insight — greater detail
+ being on the insider means that observer may see more

  • objectivity is reduced (observer bias) — observer is familiar with what’s going on, may be more subjective
  • more difficult to record and monitor behaviour unobtrusively, participants are more likely to realise they are being observed, therefore may alter their behaviour for social desirability
75
Q

What is non-participant observation

A

Observer is not a participant in the behaviour being observed
E.g. Reicher and Haslam

76
Q

Non-participant observation — pros and cons

A

+ high in objectivity — since the observer is not an actual participant, not psychologically involved
+ can observe unobtrusively (observations likely to be covert, more natural behaviour)

  • observer may misinterpret the communications within the group because they are an outsider (Reduced validity)
  • the observer may see less as they are not a participant
77
Q

What are structured observations

A

Participants are in a contained environment (often lab experiment)
They are aware that they are being observed but are randomly assigned to different independent groups by the researcher
E.g. Capafons

78
Q

Structured observations - pros and cons

A

+ controlled environment allows focus on particular aspects of behaviour specific, so conclusions can be drawn more easily with a clearer cause and effect relation

  • if participants know that they are being observed, they may respond to demand characteristics
  • environment is unnatural, so participants may not behave as they would in everyday life, lowering ecological validity
79
Q

What are naturalistic observations

A

Everything is left as usual, in an unstructured environment

E.g. learning theories practical of observing helping behaviour

80
Q

Naturalistic observations - pros and cons

A

+ a realistic picture of a natural, spontaneous behaviour, participants more likely to behave normally – high in ecological validity
+ useful method to use when investigating a new are of research, giving the research more idea and investigation to plan

  • observation more likely to be covert, raises ethical issues
  • would be harder to draw conclusions as the focus would be really wide
81
Q

What are overt observations

A

Participant is aware that they are being observed

E.g. Reicher and Haslam

82
Q

Overt observation - pros and cons

A

+ avoids a lack of informed consent since participants know that they are being observed
+ easier to see everything that is going on as the observer doesn’t have to hide

  • if participants know they are being observed, they are likely to alter their behaviour (demand characteristics or social desirability bias, depending on the study)
83
Q

What are covert observations

A

When the researcher is ‘undercover’, participants are unaware that they are being observed
E.g. Sherif

84
Q

Covert observation - pros and cons

A

+ participants behave more naturally because they are not aware of being observed, increases internal validity

  • ethical issues, no informed consent
  • invasion of privacy
85
Q

What are case studies

A

A detailed study of a case (one person or one group of people)
E.g. HM or KF

86
Q

Case studies - pros

A

+ can be used to investigate instances of human behaviours and rare cases
+ method produces rich, in-depth data, a more holistic approach

87
Q

Case studies - cons

A
  • difficult to generalise from individual cases, each one is unique, can’t make before and after comparisons
  • necessary to use a recollection of past events which may be unreliable as memory isn’t always accurate
  • researchers may lack objectivity as they get to know the case
  • there might be important ethical issues like confidentiality and anonymity
88
Q

Case study - Phineas Gage

A

1848, railway dynamite explosion resulted in a tamping iron going through his skull
He survived and functioned normally, but his personality was very different
Showed that parts of the brain could be removed without any fatal effects
Indicated that the frontal lobe is important in aspects of behaviour such as conscientiousness
Doubt in the validity of these reports on his behaviour

89
Q

Case study - 2011 London riots

A

Studied the ‘mob’ behaviour in London riots

Observing the patterns of what they attack and don’t attack

90
Q

HM case study

A

Had epilepsy — doctor bored 2 holes into his skull to remove his hippocampus
Resulted in significant memory loss, incapable to form new LTM
His brain was sliced after death and preserved to be studied till this day
Ethical issues: he had no memory, couldn’t give informed consent for research on him to be published, but the information was kept ‘confidential’, he was referred to as HM until he passed away

91
Q

Correctional research - pros

A

+Looks at relationships between continuous variables and determining whether the relationship is significant

+ useful way to conduct a preliminary analysis on data, if it isn’t strong, we can rule out a casual relationship

92
Q

Correlational research - cons

A
  • cannot show a cause-and-effect relationship since there is no IV being deliberately altered
  • if co-variables are correlated, one may be causing the changes in the other but we won’t know the direction of the possible effect
  • may be intervening variables explaining why it is linked
  • lacks reliability and validity since the method used to measure the co-variable may do so
93
Q

What are CAT scans

A

X-rays and computer to create detailed structural images

Each image is a cross-section of the person’s brain

94
Q

CAT scans - pros and cons

A

+ useful in revealing abnormal structures in the brain such as tumours or structural damage

  • require more radiation, cannot be used often
  • only provide structural information, not live brain
95
Q

What are PET scans

A

Measures metabolic activity in the brain

Person injected with small amount of radioactive substance, will be detected scanner

96
Q

PET scans - pros and cons

A

+ shows the brain in action, useful for psychological research
+ indicates the specific areas of the brain involved in experience

  • sometimes results aren’t easy to interpret
  • precise location of active is difficult to pinpoint
  • ethical issues to inject radioactive glucose (may damage cells in the body)
97
Q

What are fMRI scans

A

Uses radio waves to measure blood oxygen levels in the brain

Areas of the brain most active will show the most oxygen

98
Q

fMRI scan - pros and cons

A

+ fMRI shows important information about which areas of the brain are being used at any one time
+ doesn’t use radiation
+ images are extremely clear and can show brain activity to the millimetre

  • expensive to use
  • only effective if person whose brain is being investigated stays perfectly still
  • 5-second lag between brain activity and image appearing on screen, may cause interpretation problems
99
Q

Other biological methods used in psychology

A

MRI scans - provide higher resolution if images than fMRI

EEG - measures brain activity through brainwaves, useful in diagnosing epilepsy and sleep and dream habits

Post-mortem - studies the brain after death

Lesioning - cutting lesion areas in animals to observe behavioural effects

Measuring hormones - hormones like testosterone can be measured through blood sample

Identifying genes - research on genetic influences through genes analysis

100
Q

What are twin studies

A

When twins are compared on a specific trait to see how similar they are: MZ vs. DZ twins

101
Q

Twin studies - pros and cons

A

+ enables researchers to investigate the influence of genes, assuming that both MZ and DZ twins share the same environment
+ although twins are unusual, information is often taken from twin registries, they hold data on thousands of twins and possible variable informations

  • may overestimate genetic influence, twins still share the same environments, so it might be environmental factors as well
102
Q

What are adoption studies

A

Genetic factors are implicated if children are more similar to their biological parents than to their adoptive parents

103
Q

Adoption studies - pros and cons

A

+ adoption studies can remove the extraneous variables of environment, know that environment is not shared or genes are not shared
+ have been useful in showing that twin studies overestimate genetic factors

  • children may be adopted to families similar to their biological families, so environmental influences may be similar
  • people who adopt other people’s offsprings are unusual, so they are likely unrepresentative of the greater population
104
Q

What are descriptive statistics

A

Measures of central tendency, frequency tables, graphs (bar chart, histogram, scatter diagram), normal distribution (including standard deviation), skewed distribution, sense checking data, measures of dispersion (range, standard deviation)
Produce, handle, interpret data-including drawing comparisons (e.g. between means of two sets of data)

105
Q

Mean - pros and cons

A

+ ‘sensitive’ measure, reflects the values of al the data in the final calculation

  • can be unrepresentative of data if there are extreme values
106
Q

Median - pros and cons

A

+ not affected by extreme scores

  • not as ‘sensitive’ as mean since not all values are reflected in the final calculation
107
Q

Mode - pros and cons

A

+ useful when data is in categories (nominal data)

  • not a useful way to describe data when there are several modes
108
Q

Range - pros and cons

A

+ convenient way to express how spread out a data set is as both highest and lowest values are used
+ easy to calculate

  • affected by extreme values
  • fails to take into account the distribution of data set
109
Q

Standard deviation - pros and cons

A

+ precise measure of dispersion since all exact values are taken into account
+ not difficult to work out with a calculator

  • may hide some of the characteristics of the data set
  • cannot be immediately sensed from the data, while range is fairly quick to identify
110
Q

What are raw data tables

A

Arranging raw data in rows and columns (like chi squared data)

111
Q

What is a frequency table

A

Displays a record of how often an event occurred
E.g. choosing favourite colour
Red III, Yellow II, Blue IIII

112
Q

What are bar graphs/ charts

A

Height of each bar represents frequency of item

113
Q

What is a histogram

A

Similar to bar graph, but for continuous data, area within bars must be proportional to frequencies represented

114
Q

What is a line graph

A

Like histogram, has continuous data on x-axis, uses a dot and line to mark categories

115
Q

What is a scatter diagram

A

Graph to display correlation data. Values are represented by dots

116
Q

What is an inferential test

A

Procedures for drawing logical conclusions (inferences) about the target population from which samples are drawn

117
Q

What is an observed value

A 
The number (value) produced after applying an inferential test formula
Sometimes called the calculated value since the researcher calculates it
118
Q

What is the critical value

A

The number (value) which must be achieved in order for a result to be significant

119
Q

What is the probability (p)

A

A measure of the likelihood that an event may occur
Probability given as a number between 0 and 1
The lower the probability, the more likely it was actually caused, instead of a casual relationship

120
Q

Significance - inferential statistics

A

Statistical term indicating that the research findings are sufficiently strong to enable a researcher to reject the null hypothesis and accept the alternate hypothesis

121
Q

Levels of significance - inferential statistics

A

Level of probability it has been agreed to reject the null hypothesis

122
Q

Critical values table

A

List of numbers that inform whether an observed value is significant or not
There are different tables for each inferential test

123
Q

What are the four types of data

A

Ratio: scale, includes zero (e.g. age, weight, height)

Interval: scale, excludes zero (e.g. Year, IQ, test scores)

Nominal: Tally (e.g. football team rankings)

Ordinal: Ranking based on categories (e.g. marital status, gender)

124
Q

When do you use Mann Whitney U

A

Independent groups design

Ordinal level data

125
Q

When do you use Wilcoxon

A

Repeated measures/ matched pairs

Ordinal level data

126
Q

When do you use Spearman’s rho

A

Correlation

Ordinal level data

127
Q

When do you use Chi-squared

A

Independent groups

Nominal level data

128
Q

Self reports - internal validity

A

Whether a questionnaire does assess what it intended to assess
If a respondent doesn’t give representative answer, then there will be a low validity
Affected by ambiguous questions, social desirability bias and leading questions

129
Q

Self-reports - ecological validity

A

Concerns the extent to which findings form a questionnaire or interview can be generalised
Depends on internal validity to an extent
Sample affects ecological validity, if sample not representative to wider population, then there will be a lower ecological validity

130
Q

Self-reports - inter-rater reliability

A

Often more than one researcher to collect data

Findings can be cross-checked for reliability

131
Q

Self-reports - test-retest reliability

A

Measure of whether something varies from one time to another
Same questionnaire or interview given to same participants on two different occasions to see if they have the same results
Interval between test and retest must be long enough so participant can’t remember their previous answers

132
Q

What is thematic analysis

A

Identifying themes to impose a kind of order on the data. Ensures the ‘order’ represents the participants’ perspective
Summarises the data and enables general conclusions to be drawn

133
Q

Steps to conducting thematic analysis

A
  1. Reading and rereading data, understanding the meanings of participants’ answers
  2. Breaking data into meaningful units: sentences or phrases which convey meaning
  3. Assigning a name or code to each unit, these represent themes you will be using
  4. Themes identified by grouping together in similar units
  5. Data chunks may be given more than one name/ code
  6. Rereading the text and ensuring that themes are correctly allocated, including all important aspects of the data
  7. Final report: should discuss and use quotes or other material to illustrate these themes
  8. Conclusions can be drawn which may include new theories
134
Q

Thematic analysis - converting qualitative data to quantitative

A

Results obtained can be reduced to quantitative form
E.g. content analysis involves counting the content of anything
Once categories/ themes are created, instances can be counted and graphs can be used to represent the findings
If you represent each category/ theme with examples, it remains qualitative
If you count instances, data becomes quantitative

Psychology A Level (21 decks)

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