Research Methods Flashcards
1
Q
Definition of the experimental method.
A
- Manipulation of variables
- Tests hypotheses
- Tests cause and effect
2
Q
Strengths and limitations of the experimental method.
A
+ -> more objective that a correlation/questionnaire (not open to interpretation)
- -> lacks ecological validity
3
Q
Definition of a lab experiment.
A
- A controlled/artificial environment
- Directly manipulated IV’s
- High levels of control
4
Q
Strengths and limitations of a lab experiment.
A
+ -> less chance of extraneous variables (high levels of control), higher reliability
- -> lacks ecological validity, higher chance of social desirability (lacks construct validity)
5
Q
Definition of a field experiment.
A
- A natural environment
- Directly manipulated IV’s
- Some situational variables are controlled
6
Q
Strengths and limitations of a field experiment.
A
+ -> high in ecological validity, lower chance of demand characteristics
- -> higher chance of extraneous variables, less reliability
7
Q
Definition of a quasi experiment.
A
- Naturally occurring IV’s (not directly manipulated)
- Lab OR field environment
8
Q
Strengths and limitations of a quasi experiment.
A
+ -> high in ecological validity, more ethical (less manipulated)
- -> higher chance of individual differences, higher chance of extraneous variables, less reliable
9
Q
Definition of an observation.
A
- Researcher watches and records participants behaviour
- Doesn’t manipulate variables
10
Q
Strengths and limitations of an observation.
A
+ -> high in ecological validity, less chance of social desirability
- -> less objective, doesn’t test cause and effect
11
Q
Definition of a structured observation.
A
- Planned out
- Predefined coding categories
12
Q
Strengths and limitations of a structured observation.
A
+ -> easier to record, easier to establish inter-rater reliability
- -> reductionist, can reduce validity, open to observer bias
13
Q
Definition of an unstructured observation.
A
- Not planned out
- Recording everything observed during the observation
14
Q
Strengths and limitations of an unstructured observation.
A
+ -> increases validity, applicable to a wider range of contexts
- -> harder to record, harder to establish reliability, open to observer bias
15
Q
Definition of a naturalistic observation.
A
- Observe participants in their natural environments
16
Q
Strengths and limitations of a naturalistic observation.
A
+ -> high in ecological validity
- -> lower in reliability
17
Q
Definition of a controlled observation.
A
- Conducted in a lab-type setting
18
Q
Strengths and limitations of a controlled observation.
A
+ -> higher in reliability
- -> lower in ecological validity
19
Q
Definition of a covert observation.
A
- Participants don’t know they are being watched
20
Q
Strengths and limitations of a covert observation.
A
+ -> increases validity, less social desirability
- -> increases ethical issues
21
Q
Definition of an overt observation.
A
- Participants are aware that they are being watched
22
Q
Strengths and limitations of an overt observation.
A
+ -> reduces ethical issues
- -> decreases validity, higher chance of social desirability
23
Q
Definition of a participant observation.
A
- Observer is taking part in the activities
24
Q
Strengths and limitations of a participant observation.
A
+ -> only way to observe behaviour (cults/gangs), greater accuracy and detail
- -> harder to remain objective, can influence behaviour, more ethical issues
25
Definition of a non-participant observation.
- Observer is not taking part in the activities
26
Strengths and limitations of a non-participant observation.
+ -> easier to remain objective, can't influence behaviour, less ethical issues
- -> can't observe certain behaviour, less detail and accuracy
27
Definition of event sampling.
- Every behaviour is recorded within a specific period of time (specified on a predetermined checklist)
28
Strengths and limitations of event sampling.
+ -> easier to record, easier to establish inter-rater reliability
- -> reductionist, lowers validity, open to observer bias, produces quantitive data
29
Definition of time sampling.
- Behaviour is recorded at specific time intervals (specified on a predetermined checklist)
30
Strengths and limitations of time sampling.
+ -> higher reliability
- -> could miss behaviours
31
Strengths and limitations of a questionnaire.
+ -> quicker with a large sample, more ethical (confidentiality)
- -> social desirability, higher chance of leading questions
32
Definition of closed questions.
- Predetermined set of responses
33
Strengths and limitations of closed questions.
+ -> easy to analyse
- -> decreased construct validity
34
Definition of open questions.
- No set of predetermined responses
35
Strengths and limitations of open questions.
+ -> increased construct validity
- -> harder to analyse
36
Types of closed questions.
- rating scales (labelled ends)
- likert scales (agree/disagree)
- semantic differential scales (opposing adjectives)
37
Strengths and limitations of interviews.
+ -> can double-check questions, body language, more detail
- -> social desirability
38
Definition of a structured interview.
- Predetermined set of questions asked
39
Strengths and limitations of a structured interview.
+ -> increased internal reliability
- -> social desirability
40
Definition of an unstructured interview.
- No predetermined questions
- Like a conversation
41
Strengths and limitations of an unstructured interview.
+ -> more detail, can continue the conversation on that specific topic
- -> social desirability
42
Definition of a semi-structured interview.
- Some predetermined questions
- Some none set questions
43
Strengths and limitations of a semi-structured interview.
+ -> increased internal reliability, more detail
- -> social desirability
44
What occurs in a positive correlation?
- As one variable goes up, the other goes up
45
What occurs in a negative correlation?
- As one variable goes up, the other goes down
46
Definition of independent variable.
- The thing you directly manipulate, conditions - control and experimental.
47
Definition of dependent variable.
- The measure of the behaviour in an experiment
48
Definition of extraneous variable.
- A naturally occurring IV in an experiment
- Affects the DV, not the IV
- Lack of control
49
Types of extraneous variables.
- Individual differences (age, gender, culture)
- Situational variables
50
Definition of confounding variable.
- Extraneous variable if it did occur
- If you don't control an extraneous variable, it becomes a confounding variable.
51
Structure of a one-tailed hypothesis.
- IV1 will/will not DV than IV2. (directional)
52
Structure of a two-tailed hypothesis.
- There will be/not be a difference in DV whether IV1 or IV2. (non-directional)
53
Definition of experimental designs.
- How the participants are assigned to conditions
54
Definition of repeated measures.
- Participants take part in all conditions of the experiment
55
Strengths and limitations of repeated measures.
+ -> less chance of individual differences
- -> higher chances of demand characteristics (order effects)
56
Definition of independent measures.
- Participants take part in only one condition of the experiment
57
Strengths and limitations of independent measures.
+ -> less chance demand characteristics
- -> higher chance of individual differences
58
Definition of matched pairs design.
- Match participants based on individual characteristics you are looking for
59
Strengths and limitations of matched pairs design.
+ -> less chance of individual differences
- -> time consuming and expensive to match up participants
60
Definition of sample.
- The group of participants in a study that are representative of the target population
61
Definition of target population.
- The people that an experiment's results are generalised to
- The sample is taken from the target population
62
Definition of random sampling.
- Every member of the target population must have an equal chance of being selected
- There has to be a clear and finite target population
63
Strengths and limitations of random sampling.
+ -> least biased method of sampling, all members have an equal chance of being chosen
- -> difficult and time consuming, representativeness is not guaranteed
64
Definition of self-selecting sampling.
- People will volunteer themselves to take part in the research
65
Strengths and limitations of self-selecting sampling.
+ -> wide range of access to potential participants, convenient and ethical if it leads to informed consent
- -> often unrepresentative as leads to biased sample, more likely to respond with demand characteristics as will only respond to adverts if they have a strong interest
66
Definition of opportunity sampling.
- The researcher selects the most convenient people to study
67
Strengths and limitations of opportunity sampling.
+ -> easiest method as first participants found are used, less time to locate sample
- -> likely to produce biased sample, only certain types of people will be chosen so not representative
68
Definition of snowball sampling.
- The researcher selects one person for the study then they ask that person if they know anyone who is willing to take part within the target population, this process then continues.
69
Strengths and limitations of snowball sampling.
+ -> possible to include members of groups that may not be easy to access
- -> biased because sample is drawn from small part of the target population
70
Definition of nominal data.
- Categorical data
- Will create a frequency of totals
71
Strengths and limitations of nominal data.
+ -> quickest to analyse, easy to generate from closed questions, increased reliability
- -> lacks detail, lacks a scale
72
Definition of ordinal data.
- Can be ranked
- Rating scales
73
Strengths and limitations of ordinal data.
+ -> more information, linear scale
- -> gaps between values aren't equal (mean can't be used)
74
Definition of interval data.
- Can be nominal or ordinal
- Divisions between the points are equal
75
Strengths and limitations of interval data.
+ -> more information, scientific measures, highly reliable, more comparison
- -> no absolute baseline, extraneous variables
76
Definition of primary data.
- Data collected first hand (interviews, focus groups)
77
Strengths and limitations of primary data.
+ -> increased validity, more detail
- -> time consuming, expensive
78
Definition of secondary data.
- Data collected by other people (articles, other research)
79
Strengths and limitations of secondary data.
+ -> quick to acquire, doesn't cost a lot
- -> lower validity, potentially less detail, can't find out exactly what you want to know
80
Describe the observed value.
- Final mathematical result
- Comparison between observed value and critical value tells us significant/not significant
- P (probability) value - significance level, set at p
81
Describe levels of significance.
- Aiming to reject the null hypothesis
- Could have occurred by chance (if unlikely we can accept the alternate)
- Can satisfy the falsifiability requirement of the scientific method
- Must be confident that it was the variables rather than the extraneous variables
82
Definition of dispersion.
- Spread around the mean (range, variance, standard deviation)
83
Definition of variance.
- Spread of scores around the mean
- Small variance = scores all similar (more consistency), large variance = scores at larger distance from mean
84
Definition of standard deviation.
- Square root of the variance, average amount a number differs from the mean, puts figure into a more readable format
85
Definition of type 1 errors.
- false positive
86
Describe type 1 errors.
- refers to a situation in which we assume our findings show something when they don't
- rejected null hypothesis incorrectly, accepted alternate hypothesis incorrectly
- assuming results were down to IVs when they were due to chance
- risk of type 1 errors occurring if p value is too lenient, e.g., p < 0.10/10%
- higher p value, higher possibility of results being down to chance
87
Definition of type 2 errors.
- false negative
88
Describe type 2 errors.
- refers to a situation in which we assume our findings don’t show something when they do
- accepted null hypothesis incorrectly, rejected alternate hypothesis incorrectly
- assuming results were due to chance when they were down to the IVs
- risk of type 2 errors if p value is too harsh, e.g., p < 0.01/1%
- lower p value, lower possibility that results were down to chance
- sometimes necessary for p value to be harsh, especially in regards to the medical field
89
Some features of science.
- Objective measures/data
- Experimental method
- Quantifiable data
- Cause & effect
- Induction/deduction
- Reliability
90
Definition of internal reliability.
- Standardisation (keeping the same) of procedure
91
Definition of external reliability.
- Consistency of findings outside of the study
92
Definition of inter-rater reliability.
- Agreement/consensus
93
Definition of split-half method.
- Applies mainly to self-report, 2 halves of a questionnaire are similar
94
Definition of test-retest method.
- Experimental method, testing participants more than once, measure could be administered to same group of people twice
95
Definition of validity.
- Refers to the aim of the study by asking the question, has the research tested/ measured the behaviour of what it set out to test?
96
Definition of internal validity.
- Whether the research measures what it set out to measure or could other factors such as extraneous variables have affected the results other than what is being tested
97
Definition of external validity.
- Whether the research is generalisable to wider populations or situations
98
Definition of face validity.
- Whether something looks like it will measure what it is supposed to measure
99
Definition of construct validity.
- Whether a test measures all facets of the behaviour in question in research
100
Definition of concurrent validity.
- Whether a test or measure correlates with a previously validated measure
101
Definition of criterion validity.
- Whether the measure used can predict another measure of behaviour
102
Definition of ecological validity.
- Whether the task, environment, or situation are generalisable to real life situations
103
Definition of population validity.
- Whether the sample is representative of the wider target population of the research
