1
Q
aim
A
a general statement of what the researcher intends to investigate (the purpose of the study)
2
Q
hypothesis
A
a statement that states the predicted outcome of the study
3
Q
directional (one-tailed) hypothesis
A
a prediction that states the direction the results will go in (eg: noise will negatively affect concentration)
4
Q
non directional (two-tailed) hypothesis
A
a prediction that does not state the direction the results will go in (eg: noise will affect concentration)
5
Q
null hypothesis
A
a prediction that suggests there is no relationship between measured variables (eg: noise does not affect concentration)
6
Q
operationalisation
A
clearly defining variables in terms of how they can be measured (eg: speed - 10mph and 60mph)
7
Q
independent variable (IV)
A
an aspect of the experimental situation that is changed
8
Q
dependent variable (DV)
A
what is measured by the experimenter caused by the change in IV
9
Q
extraneous variable (EV)
A
any other variable than the IV that may affect the DV if not controlled
10
Q
confounding variable (CV)
A
influences both the IV and the DV making it hard to determine the true cause and effect relationship
11
Q
demand characteristics
A
any cue from the researcher/situation that may reveal the true purpose of the study changing the participants behaviour
12
Q
investigator effects
A
any effect from the investigator’s behaviour on the research outcome
13
Q
how to minimise EVs/CVs effects?
A
- randomisation = use of chance methods to reduce bias
- standardisation = exactly the same procedures, instructions, etc for all participants
- counter balancing = control repeated measures design by experiencing conditions in different orders
14
Q
independent group design
A
participants are placed in separate groups/conditions
15
Q
strengths of independent group design
A
- order effects are not a problem as participants only experience 1 condition
- less likely to guess the aim of the experiment (demand characteristics)
16
Q
weaknesses of independent group design
A
- lots of time/money spent on recruiting participants
- participant variables as all have different abilities/ characteristics
17
Q
repeated measures design
A
all participants experience both conditions
18
Q
strengths of repeated measures design
A
- participants variables are controlled so high validity
- fewer participants needed so less time consuming
19
Q
weaknesses of repeated measures design
A
- order effects as repeating 2 tasks so may be influence responses
- demand characteristics as participants experience all conditions of experiment
20
Q
matched pair design
A
two groups of participants are matched up on key/similar characteristics
21
Q
strengths of matched pair design
A
- order effects and demand characteristics are less of a problem as only take part in a single condition
22
Q
weaknesses of matched pair design
A
- time consuming and difficult to match participants so large group required
23
Q
laboratory experiment
A
an experiment that takes place in a controlled environment
24
Q
strengths of laboratory experiment
A
- high control over EVs so high internal validity
- easier to replicate as high level of control to check if findings are valid
25
weaknesses of laboratory experiment
- may lack generalisability as artificial environment so low external validity
- participants may not act natural and show demand characteristics
26
field experiment
an experiment that takes place in a natural setting
27
strengths of field experiment
- high mundane realism as more natural than labs so more valid and authentic so high external validity
28
weaknesses of field experiment
- more difficult to replicate as EVs are hard to control
- ethical issues such as lack of consent, invasion of privacy, right to withdraw
29
natural experiment
an experiment where the change in IV would have happened if the researcher was there or not
30
strengths of natural experiment
- high external validity as involves real life problems
- provides opportunities for research that may have practical/ethical issues
31
weaknesses of natural experiment
- rarely opportunities for this research so may limit the scope for generalising findings to similar situations
32
quasi experiment
a study where the IV is naturally occurring and cannot be changed such as age
33
random sampling
when all participants have an equal chance of being selected within the target population
34
strength of random sampling
unbiased so high internal validity as EVs should be equally divided
35
weakness of random sampling
could be difficult and time consuming to conduct
36
systematic sampling
using a predetermined system to select participants (eg: every 3rd house on a street)
37
strength of systematic sampling
unbiased as no influence over who is chosen
38
weakness of systematic sampling
time consuming if participants refuse to take part
39
stratified sampling
sub groups within a population are identified and randomly select participants within
40
strength of stratified sampling
representative sample so easier to generalise findings
41
weakness of stratified sampling
time consuming to identify sub groups and also select randomly
42
opportunity sampling
selecting anyone who is willing and available
43
strength of opportunity sampling
convenient and less costly as an easy method to carry out
44
weakness of opportunity sampling
biased as all participants from one specific area so unrepresentative
45
volunteer sampling
involves participating selecting themselves to be part of a study (though advertisement by researcher)
46
strength of volunteer sampling
requires minimal input from researcher so less time consuming and less costly
47
weakness of volunteer sampling
may attract a certain profile of people so volunteer bias
48
ethical issues and how to deal with them
- informed consent = issue a consent letter
- deception = full debrief and true aim
- protection from harm = provide counselling if required
- privacy and confidentiality = personal data protected
(right to withdraw if wanted at any time)
49
pilot study
a small scale version of an investigation that takes place before the real study is conducted, aims to check the procedure runs smoothly
50
naturalistic observation
watching and recording behaviour in a setting in which it would normally occur
51
strength of naturalistic observation
high external validity as findings can often be generalised to every day life
52
weakness of naturalistic observation
lack of control over research situation making replication difficult
53
controlled observation
watching and recording behaviour within a structured environment where the variables are managed
54
strength of controlled observation
EVs are less of a problem so easier to replicate the observation
55
weakness of controlled observation
may produce findings that cannot be applied to real life
56
participant observation
the researcher is a member of the group whose behaviour they are observing
57
strength of participant observation
increased insight into the study so high external validity
58
weakness of participant observation
researcher could lose objectivity and identify too strongly with their role
59
non participant observation
the researcher remains outside of the group whose behaviour they are observing
60
strength of non participant observation
allows researcher to maintain an objective psychological distance from participants
61
weakness of non participant observation
may lose valuable insight as they are too far removed from participants
62
covert observation
participants behaviour is being watched and recorded without their knowledge or consent
63
strength of covert observation
removes demand characteristics as behaviour will be natural increasing internal validity
64
weakness of covert observation
ethics may be questioned as right to privacy
65
overt observation
participants behaviour is watched and recorded with their knowledge and consent
66
strength of overt observation
more ethically acceptable as participants have given consent
67
weakness of overt observation
may influence the participants behaviour so demand characteristics
68
behavioural catergories
when a target behaviour is broken into components that are observable and measurable (operationalisation)
69
strength of behavioural categories
makes data collection more structured and objective as clear categories which reduces subjectivity and increases reliability
70
weakness of behavioural categories
limited flexibility as predefined categories might not capture all relevant behaviours leading to incomplete data
71
event sampling
a target behaviour is first established and then the researcher records this event every time it occurs (eg: recording every instance of hitting during break in playground)
72
time sampling
a target individual or group is first established then the researcher records their behaviour in a fixed time frame (eg: recording whether a student is paying attention in class every 30 seconds)
73
questionnaires
a self report technique which involves a set of questions to assess a persons thoughts or experiences
74
strength of questionnaires
cost effective as can gather large amounts of data quickly as can be distributed to many people
75
weakness of questionnaires
responses may not be truthful due to social desirability bias if they are embarrassed about their answer especially if not anonymous
76
structured and unstructured interviews
structured - made up of pre determined questions that are asked in a fixed order
unstructured - no set questions, a free flowing interaction
77
strength and weakness of structured interviews
+ straightforward to replicate due to standardised format
- limit the richness/detail of data collected as may not be able to fully explain answers
78
strength and weakness of unstructured interviews
+ more flexibility so gain more insight for more detailed data
- difficult to analyse due to irrelevant information and drawing conclusions may be difficult
79
open questions
no fixed response/choice
80
closed questions
fixed response/choice
81
writing good questions
- easy to understand
- no leading questions
- remain unbiased
82
correlations
an association between co-variables
83
correlation co-efficient
a number between -1 and 1 that shows the strength and direction of the relationship between two variables
84
strength of correlations
provides a precise and quantifiable measure of how two variables are related
85
weakness of correlations
will only tell how variables are related but not why so cannot determine the cause and effect relationship
86
qualitative data
data expressed through words (non-numerical)
87
strength of qualitative data
offers more detailed and broader answers so greater external validity
88
weakness of qualitative data
analysis of data may require interpretations by researcher which could result in bias
difficult and time consuming to analyse as more difficult to identify patterns
89
quantitative data
data expressed numerically
90
strength of quantitative data
simpler to analyse so easier to make conclusions as more objective
91
weakness of quantitative data
narrower in meaning and detail so may fail to represent real life
92
primary data
information collected first hand by researcher specifically for the purpose of a study
93
strength of primary data
high control over the data gathered to fit the purpose of the study
94
weakness of primary data
lengthy and costly process requiring lots of planning and resources
95
secondary data
information that has already been collected by someone else
96
strength of secondary data
much simpler and cheaper to use others' data requiring minimal effort
97
weakness of secondary data
information may be outdated or incomplete and may not match the exact needs of the current study reducing validity of conclusions drawn
98
meta analysis
uses secondary data from a number of studies on a particular topic producing an overall conclusion
99
strength of meta analysis
allows a larger, more varied sample where results can be generalised across much larger populations increasing validity
100
weakness of meta analysis
may not have quite relevant studies and researcher may only pick certain studies with results they want leading to biased conclusions
101
measures of central tendency
- mean
- mode
- median
102
measures of dispersion
- range
- standard deviation
103
standard deviation (small/large)
small SD = data is similar, closer to mean
large SD = data is varied, further from mean
104
when to use the sign test
- repeated measures or matched pair design (2 sets of data from each participant)
- nominal data (categories)
- test of difference
105
calculation of sign test
1. workout difference between the 2 data sets
2. delete any participants with a score of 0
3. count number of + and - signs
4. the smaller value is the calculated/observed value (S)
5. workout critical value from table
6. compare critical value with calculated/observed value (if the calculated value is equal to or less than the critical value, the result is significant)
106
role of peer review
to validate the quality and relevance of research and suggest improvements
107
issue with peer review
reviewers remain anonymous which is good for honesty but may result in bias criticising rival researchers in competition for funding
108
psychological research impact of the economy example
attachment research into the role of the father shows that both parents are equally capable of being the primary caregiver which means the can maximise their income and contribute more to the economy
psychology
flashcards
Decks in class (6)
# Cards
