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research methods Flashcards

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1
Q

Empirical Approach

A

The source of knowledge comes through our senses - knowledge is gained through experience.
If a theory hasn’t been tested empirically, then it cannot be classed as scientific.

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2
Q

PARADIGM

A

A general theory or law that is accepted by the majority of scientists in a specific field of study

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3
Q

Pre-science

A

No paradigm exists, and there is much debate about what the subject is and its theoretical approach

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4
Q

Normal science

A

A generally accepted paradigm that can account for all the phenomena related to the subject, and can explain and interpret all findings

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5
Q

Scientific revolution

A

Evidence against the old paradigm reaches a certain point, and there is a paradigm shift. The old paradigm is replaced by a new one

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6
Q

Null hypothesis

A

A statement which predicts no difference/relationship in results, and predicts all possible outcomes

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7
Q

Experimental/alternative/research hypothesis

A

A statement that predicts a difference/relationship in results - predicts a difference between the conditions of an independent and dependent variable

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8
Q

Aim

A

The intended purpose of an investigation

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9
Q

Hypothesis

A

A clear, precise and testable statement about the expected outcome of the research

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10
Q

Independent variable

A

Variable that is manipulated or changed by the researcher

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11
Q

Dependent variable

A

Variable that is measured

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12
Q

Operationalisation

A

The process of clearly defining observable behaviours that represent a more general construct in order for them to be measured

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13
Q

Independent groups

A

Two separate groups of participants experience two different conditions of the experiment

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14
Q

Repeated measures

A

All participants experience both conditions of the independent variable

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15
Q

Matched pairs

A

Participants are paired together on a variable/variables relevant to the experiment

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16
Q

Random allocation

A

In an experiment were participants are involved in a number of different conditions, the order of those conditions should be random

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17
Q

Counterbalancing

A

An attempt to control order effects in a repeated measures design - half the participants take part in condition A and B, the other half visa versa

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18
Q

Hawthorn effect

A

People change their behaviour due to the fact that they are being observed

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19
Q

Demand Characteristics

A

Participants are influenced by their environment/what’s going on in the study, so their is a change in their behaviour

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20
Q

Social desirability bias

A

Participants answer in ways which make them look good to others

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21
Q

Standardisation

A

Using exactly the same procedures and instructions for all participants in the research study, each time the experiment is conducted

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22
Q

Investigator effects

A

Any effect of the investigators behaviour on the research outcome. They reveal to the participants how they should behave or what the experiment is about.

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23
Q

Demand characteristics

A

Participants are influenced by their environment to the point they change the way they are acting

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24
Q

Single - blind techniques

A

Participants don’t know about the test being conducted, but the researchers do

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25
Q

Double - blind techniques

A

Both participants and the doctors don’t know about the study, therefore this reduces investigator effects

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26
Q

Ethics

A

Governs what psychologists can and cannot do, based on morals

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27
Q

Informed consent

A

Participants above the age of 18 have the ability to give consent if they are willing to take part in a study

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28
Q

Right to withdraw

A

Participants should have the right to leave any study, at any point.

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29
Q

Confidentiality

A

Data given to researchers, by participants of the study, must be kept anonymous unless said otherwise.

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30
Q

Deception

A

This is when participants are not told the entire truth about the study

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31
Q

Protection

A

Protecting participants from mental and physical harm whilst conducting the study

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32
Q

Debriefing

A

Researchers and participants talk over the experiment/study in order to remove any anxieties or misconceptions

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33
Q

Sample

A

A small representative group gained from the target population

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34
Q

Sampling

A

Method used to identify and obtain the sample of participants in a study

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35
Q

Generalisation

A

Applying the findings of a particular study to the population

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36
Q

Sample bias

A

When a sampling method results in unrepresentative sample

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37
Q

Volunteer bias

A

people who volunteer to participate in research are likely to be different and this can distort data/research

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38
Q

Random sampling

A

Selecting a sample using a random technique, meaning that everyone has an equal chance of being picked:
- picking numbers from a hat (lottery method)
- random number table

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39
Q

Evaluation of random sampling

A

Strengths: Reduces the effect of researcher bias, Increases the chance of having a representative sample
Limitations: Sample could still be biased depending on the population, Time consuming, An impossible method to do without specific data

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40
Q

Stratified sampling

A

A sample produced by identifying sub groups according to their frequency in the population - then participants are selected randomly from their subgroups

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41
Q

Evaluation of stratified sampling

A

Strengths: Representative sample, Accurate, Reduces researcher bias
Limitations: Time consuming, Human error could occur if maths is done wrong

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42
Q

Volunteer sampling

A

A sample relying on volunteers by advertising the study - via newspaper, internet, noticeboard.

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43
Q

Evaluation of volunteer sampling

A

Strengths: Reduces any ethical issues, Reduces researcher bias, Quicker and easier than other sampling methods
Limitations: Biased results could arise based on participants characteristics, Participants are more likely to display demand characteristics

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44
Q

Systematic sampling

A

A sample obtained by selecting every nth person
Example: every 5th person, or every 12th person

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45
Q

Evaluation of systematic sampling

A

Strengths: Reduction of researcher bias, Easier and quicker than other sampling methods,Can be used with large samples
Limitations: Biased by coincidence, More time consuming than other samples, Sometimes impossible to do

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46
Q

Opportunity sampling

A

Recruiting people who are the most convenient, or available and willing to take part

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47
Q

Evaluation of opportunity sample

A

Strengths: Quick, easy, inexpensive and convenient, Participants gathered in one place
Limitations: Not representative because people who aren’t available may differ from those who are available, Researcher has no direct control over the participants or the study

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48
Q

Laboratory experiment

A

An experiment which takes place in a highly controlled environment, and the IV is manipulated by the researcher

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49
Q

Evaluation of laboratory experiment

A

Strengths: Standardisation is possible which increases reliability, The cause and effect can be identified
Limitations: Low ecological validity, Possibility of participant bias due to demand characteristics, Tasks lack mundane realism

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50
Q

Field experiment

A

The independent variable is manipulated in a natural environment of the participants - sometimes they are unaware that they are being studied

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51
Q

Evaluation of Field experiment

A

Strengths: High ecological validity, Demand characteristics are not an issue as participants don’t know that they’re being studied
Limitations: No control of extraneous variables which reduces reliability

52
Q

Natural experiment

A

The independent variable changes naturally - this means that the researcher doesn’t have much control. The DV is recorded

53
Q

Evaluation of Natural experiment

A

Strengths: Provide opportunities for research which might not have happened due to ethical or practical reasons, High in ecological validity
Limitations: Reliability is reduced because these events have no specific time as to when they will take place, Research may still be conducted in a lab

54
Q

Quasi experiment

A

The independent variable just exists, and it isn’t changed or manipulated - it is based on the differences between people (age, gender). The DV can be naturally occurring, or be decided by the researcher

55
Q

Evaluation of quasi experiment

A

Strengths: Often carried out in controlled conditions (laboratory strengths)
Limitations: This type of experiment cannot use random sampling therefore there may be confounding variables, Change of the IV isn’t controlled by the researcher

56
Q

Quantitative data

A

Data that is expressed numerically
- Percentages….

57
Q

Evaluation of quantitative data

A

Strengths: Easy to analyse as it can be presented in a visual format
Limitations: Provides little insight and understanding into the participants thoughts and information

58
Q

Qualitative data

A

Data that is expressed in words
- Written observation notes
- Diary entry….

59
Q

Evaluation of qualitative data

A

Strengths: Provides a detailed understanding and insight into the participants views and information
Limitations: Difficult and time consuming to analyse

60
Q

Primary data

A

Original data that has been collected specifically for the purpose of the research - also called field research
- Observations
- Interviews
-Questionnaires….

61
Q

Evaluation of primary data

A

Strengths: The researcher has control over what data is collected, Data fits the purpose of the research
Limitations: Requires the time and effort of the researcher

62
Q

Secondary data

A

Data collected by someone other than the person who is conducting the research
- Government statistics…

63
Q

Evaluation of secondary data

A

Strengths: Easy to access, cheap and requires little effort from the researcher
Limitations: The content of the data may not match the purpose of the investigation, Reduction of validity

64
Q

Meta analysis

A

A form of secondary data which refers to a process in which a number of studies are identified which have investigated the same aims/hypothesis. The results of these studies can be pooled together and a joint conclusion is produced

65
Q

Evaluation of meta anlysis

A

Strengths: A larger, varied sample which allows it to be generalised over a larger population
Limitations: Increase of publication bias

66
Q

Evaluation of mean

A

Strengths: Takes all the data into account
Limitations: Extreme values will change results

67
Q

Evaluation of median

A

Strength: Not effected by extreme values
Limitations: Easy to calculate

68
Q

Evaluation of mode

A

Strengths: Easy to calculate, Categorical data
Limitations: Not representative of the whole data set

69
Q

Distributions

A

By plotting frequency data, we can see an overall pattern of the data

70
Q

Normal distribution

A
  • Forms a bell shaped curve
  • Shows symmetry
  • Mean, median and mode are all located at the highest peak
  • On average, most people are scoring in the middle
71
Q

Positively-skewed distribution

A
  • A spread of frequency that is not symmetrical
  • Data clusters to one end
  • The long tail is at the right hand side
72
Q

Negatively-skewed distribution

A
  • The long tail is on the left side of the peak
73
Q

Correlation

A

A technique used to investigate the strength of the relationship between two variables (co-variables)
- Presented using scatter graphs

74
Q

Positive correlation

A

As one co-variable increases, the other co-variable also increases

75
Q

Negative correlation

A

As one co-variable increases, the other co-variable decreases

76
Q

Zero correlation

A

There is no relationship between the co-variables

77
Q

Evaluation of correlations

A

Strengths: Able to analyse situations that could not be manipulated experimentally for ethical or practical reasons, Correlations are useful tools in research - they suggest possible future research if there is a relationship between variables
Limitations: Can only identify linear relationships, Correlation does not establish cause and effect

78
Q

Evaluation of questionnaires

A

Strengths: Doesn’t take much time, money, or effort, Answers collected can be changed into graphs or charts because of how direct they can be
Limitations: Social desirability bias may be an issue as participants might want to present themselves in a good light, Some participants might just agree with the statements given, regardless of the content of the question

79
Q

Structured interview

A

An interview made up of pre-determined questions that are asked in a fixed order

80
Q

Evaluation of structured interviews

A

Strengths: Straight forward to replicate, Reduces differences between interviews - standardisation
Limitations: If the questions are confusing to the participants , their answers will be limited

81
Q

Unstructured interviews

A

An interview where there are no set questions, and it instead resembles a conversation to allow participants to elaborate and explore their answers

82
Q

Evaluation of unstructured interviews

A

Strengths: Participants may feel more comfortable as they can answer however they want to, More detail into answers
Limitations: Due to the vague questions interviewers may have to go through lots of information to gather the information needed, Increased risk of interviews bias as an interview can adapt it as each interview is different

83
Q

Semi-structured interview

A

A list of pre-determined questions which can be used, but interviewers are allowed to ask follow up questions based on previous answers

84
Q

Naturalistic observation

A

Carried out in everyday settings, where the investigator does not interfere

85
Q

Evaluation of naturalistic observation

A

Strengths: High ecological validity because they are conducted in a normal environment
Limitations: Researchers have very little control over extraneous/confounding variables

86
Q

Controlled oberservations

A

Behaviour is observed under conditions where variables have been organised by the researcher

87
Q

Evaluation of controlled observations

A

Strengths: Extraneous and confounding variables are less of a problem
Limitations: Low external/ecological validity, Findings cannot be applied to everyday life

88
Q

Participant observation

A

The researcher participates in the activity being observed

89
Q

Evaluation of participant observation

A

Strengths: Provides the researcher with increased insight into the people being studied
Limitations: Researchers may ‘go native’ and lose objectivity

90
Q

Non-participant observations

A

The observer stays separate from people being observed

91
Q

Evaluation of non-participant

A

Strengths: Researcher can remain objective so there is less danger of ‘going native’
Limitations: Lose valuable insight of the group

92
Q

Overt observation

A

Participants are observed with their knowledge

93
Q

Evaluation of overt observation

A

Strengths: Ethically acceptable, Researcher’s can gain consent from participants
Limitations: Demand characteristics may occur because participants know they are being studied

94
Q

Covert observation

A

Participants are observed without their knowledge

95
Q

Evaluation of covert observation

A

Strengths: Reduces demand characteristics because participants are unaware that they’re being studied
Limitations: Ethical issues (consent, withdrawal)

96
Q

Unstructured observation

A

The researcher records all relevant behaviour but has no system

97
Q

Evaluation of unstructured observation

A

Strengths: Researchers collect qualitative data which allows a detailed understanding of behaviour
Limitations: Qualitative data is time consuming and difficult to analyse

98
Q

Structured observation

A

The researcher uses systems to record the behaviour, such as behavioural categories and event or time sampling

99
Q

Evaluation of structured observations

A

Strengths: Behavioural categories make it easier to record data and produces quantitative data
Limitations: Using quantitative data means that meanings behind behaviour cannot be gained

100
Q

Behavioural categories

A

When a target behaviour is broken up into components that are observable and measurable

101
Q

Event sampling

A

Counting the number of times a particular behaviour occurs within a group

102
Q

Time sampling

A

Recording behaviour within a pre-established time frame

103
Q

Pilot study

A

A trial run of a research study, involving only a few participants who are representative of the target population

104
Q

Pilotting

A

Testing a part of the eventual study

105
Q

Peer review

A

Other people in the same field as you check the quality of your research and give improvements

106
Q

Reliability

A

The extent to which a test or a study produces consistent results

107
Q

Internal reliability

A

Measure of the extent to which something is consistent within itself

108
Q

External reliability

A

Measure of consistency over a number of different occasions

109
Q

Assessing reliability methods:

A
  • Split-half method
  • Test-retest method
110
Q

Split-half method

A

When one half of the test compared with the other in order to check whether the scores are consistent

111
Q

Test-retest method

A

The same test or interview is given to the same participant on two occasions to see if the same results are gained

112
Q

Inter-rater reliability

A

The degree of agreement between different researchers - a result of 0.80 or more suggests good inter-rater reliability

113
Q

Validity

A

The extent to which an observed effect is genuine

114
Q

Internal validity

A

Whether the study has tested what it set out to test

115
Q

External validity

A

The degree to which a research finding can be generalised to…
- other settings (ecological validity)
- to other groups of people (population validity)
- over time (temporal validity)

116
Q

Face validity

A

Does the tests look correct?

117
Q

Concurrent validity

A

Do results of this test match with results of a prior similar test?

118
Q

Predictive validity

A

Based on prior knowledge, are the results ones that were expected

119
Q

Improving validity

A
  • Lie scale
  • Covert Observation
  • Behavioural categories
  • Standardise
  • Double blind
120
Q

Level of significance

A

0.05 or 5%

121
Q

Type 1 error

A

The null hypothesis is rejected and the alternative hypothesis was accepted, when it should’ve been the other way round.
- Often referred to as a false positive

122
Q

Type 2 error

A

When the null hypothesis is accepted, and the alternative hypothesis was rejected when it should’ve been accepted.

123
Q

Interval data

A

Data that can be ranked or put in order, but has a fixed scale

124
Q

Ordinal data

A

Data that can be ranked or put in order but doesn’t have a fixed scale

125
Q

Nominal data

A

Data that can be put into categories or frequencies or tally

psychology paper 2 (3 decks)

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