rsm Flashcards
(185 cards)
1
Q
what is an aim
A
a statement of the study’s purpose.
should be stated beforehand so it is clear what the study intends to investigate
2
Q
What is a one-tailed (directional) hypothesis
A
a hypothesis that predicts a difference between your variables. it makes a directional prediction e.g. higher or lower
3
Q
when would you use a one tailed hypothesis
A
when you have previous research findings which suggest which way the results will go
4
Q
what is a two-tailed (non directional) hypothesis
A
a hypothesis that predicts a difference but doesn’t state where the difference lies
5
Q
when you you use a two tailed investigation
A
when there is no or little previous research in the area or when results are mixed or inconclusive
6
Q
what is a null hypothesis
A
this is what you assume is true during the study. any satay you collect will either back this assumption or it won’t. if the data doesn’t support you null hypothesis, you reject it and go with your alternative hypothesis instead
7
Q
what is a typical null hypothesis
A
the null hypothesis will predict that there is no difference/ relationship between your variables
8
Q
what is a bar chart
A
used to present non-
continuous data
9
Q
how is a bar chart different to a histogram
A
columns do not touch
10
Q
what is a histogram
A
used when you have continuous data- the columns touch and it is the height of the column that shows the number of values in each interval
11
Q
what is correlational analysis
A
a measure of how closely two variables are related
12
Q
what are advantages of correlational analysis
A
-do not need to use a controlled experiment
-can use sensitive data obtained from hospitals e.g
13
Q
what are disadvantages of correlational analysis
A
-cannot establish cause and effect- third variable
- coefficients can be due to chance, may be other unknown variables or extraneous variables that may lead to false conclusions
14
Q
what is correlation coefficient
A
a number between -1 and +1 = the closer it is, the stronger the relationship between the variables
15
Q
correlations
A
positive correlation- as one variable rises the other rises
negative correlation- as one variable rises the other falls
no correlation- the variables are not linked
16
Q
what is normal distribution
A
a symmetrical spread of frequency data that forms a bell-shaped pattern
the mean, medium and mode are all located at the highest peak
17
Q
what is skewed distribution
A
a spread of frequency data that is not symmetrical where the clusters to one data
18
Q
negative distribution
A
a type of distribution in which the long tail is on the negative (left) side of the peak and most of the distribution is concentrated on the right
the mode is more than the median which is more than the mean
19
Q
positive distribution
A
a type of distribution in which the long tail is on the positive (right) side of the peak and most of the distribution is concentrated on the left
the mode is less than the med, which is less than the mean
20
Q
what is the independent variable
A
the variable directly manipulated by the researcher ( what you are changing)
21
Q
what is the dependent variable
A
the variable you think will be affected by the changes in the IV
22
Q
what is meant by operationalisation
A
describing the process by which the variable is measured. this allows other researchers to see exactly how you are defining and means your variables
23
Q
random allocation
A
everyone has an equal chance of doing either condition
24
Q
counterbalancing
A
mixing up the order of the tasks. this he,ps with order effects in repeated measures designs
25
randomisation
when materials are presented to the participants in random order
26
standardisation
everything should be as similar as possible for all the participants
27
what are extraneous variables
any variable (other than the IV) that could affect what you’re trying to measure
28
how can extraneous variables be controlled
random sampling creates more equality between groups
29
confounding variables
any variables that influences your DV
30
validity
accuracy- internal and external
31
ecological validity
generalisable to real life settings
32
concurrent validity
results from the new test can be compared to previously well-established test
33
population validity
whether you can reasonably generalise the findings from your sample to a larger group of people
34
temporal validity
assesses to what degree research findings remain over time
35
face validity
the extent to which a test appears to measure what is intended to measure
36
what is reliability
the overall consistency of a measure
37
what is internal reliability
the extent to which a test is consistent within itself
38
external reliability
the ability of the test to produce the same results each time it is carried out
39
what are ethical guidelines
ethical guidelines were developed for psychologists to follow when they are designing studies so that participants are protected
40
informed consent
participants should always give informed consent (under 16 by parents or guardians) they should be told the aims and nature of the study and the right to withdraw
41
deception
if participants have been deceived then they cannot give informed consent. sometimes researchers must withhold information about the study because the participants would not behave naturally if they knew what the aims were
42
right to withdraw
participants are allowed to withdraw from the research at any point
43
confidentiality
none of the participants in the study should be identifiable from any reports that are produced. data must be confidential and anonymous
44
protection from harm
risk of harm to participants in the study should be no greater than they would face in their normal lives
45
what is a debrief
this should return participants to the state they were in before the researcher. researchers must fully explain what the research involved and what the results might show
46
what are independent groups
there are different participants in each group
47
what is an advantage of independent groups
no order effects
fewer demand characteristics
48
what are weaknesses of independent groups
participant variables- individual differences
number of participants- twice as many
49
what are repeated measures
all participants do all conditions
used to compare each condition to each other
50
advantages of repeated measures
participant variables
number of participants
51
weaknesses of repeated measures
order effects
demand characteristics
52
what are matched pairs
there are different participants in each condition but they are matched on important variables
53
matched pairs advantages
no order effects
participant variables
54
matched pairs weaknesses
number of participants
practicalities- time consuming and difficult to find people who match
55
what is the nature and use of a field experiment
experiments conducted outside of the lab. behaviour is measured in a natural environment such as a school. a key variable is still altered so it’s effect can be measured
56
advantage of a field experiment
casual relationship
ecological validity
57
weaknesses of field experiments
less control
ethics
58
what is the nature and use of a laboratory experiment
an experiment that controls all relevant variables except one key variable, which is altered to see to what the effect is
59
what are advantages of lab experiments
controlled
replicable
60
what are weaknesses to laboratory experiments
artificial
demand characteristics
61
what is a confederate
someone who is involved in the research that tries to influence the participants
62
what is an experimental group
the participants are the experiment who the researcher is testing e.g. they may receive a drug
63
what is a control group
the other condition where participants are taking part in the experiment but no manipulation is used. e.g. they may receive a saline solution instead of the drug that the experimental group received
64
what are demand characteristics
participants may have determined the aims of the study
they might act deliberately to please the researcher or the opposite
65
how can demand characteristics be controlled
counterbalancing / randomisation
66
what is a double blind experiment
neither the participants or the researchers know which condition the participants are in
this use used in medical trials
67
what is a single blind experiment
the participants do not know what condition they are in
used for experiments and control groups
68
what is the nature and use of a natural experiment
where the researcher look at how the IV, which is not manipulated by the researcher, effects the DV. the IV is an event that occurs naturally
for example, single sex schools and mixed schools
69
advantages of natural experiments
demand characteristics
ecological validity
70
weaknesses of natural experiments
casual relationship
ethics
71
what is the nature and use of quasi experiments
the researcher is not able to use random allocation to put participants into different conditions. naturally occurring IV, for example, biological sex
72
advantages of quasi experiment
control
ecological validity
73
disadvantages of quasi
participant allocation
casual relationship
74
what are behavioural categories
categories defined by the researcher to observe during the experiment
for example aggression in children
75
what is event sampling
researcher records every event (if a behaviour category) when observed in research
76
what is time sampling
researcher records every behaviour within a certain time frame
77
what is a controlled observation
takes place in a laboratory so the researcher can control the conditions
78
what are strengths of controlled observation
replication is possible due to highly controlled procedures
extraneous variables can be controlled
79
what are weaknesses of controlled observations
lower ecological validity
participants may alter their behaviour if they know they are being observed
80
what is naturalistic observation
takes place in a natural environment
they can be structured in advance to make sure no behaviours as missed
81
what are strengths of naturalistic observation
ecological validity
theory development
82
what are weaknesses of naturalistic observation
extraneous variables
observer bias
ethics
83
what is covert observation
researchers presence is unknown to the participants
84
what are strengths of covert observation
the participants are more likely to act naturally
85
what is a weakness of covert observation
gaining ethics can be difficult
86
what is overt observation
researchers presence is obvious to participants
87
strengths of overt observation
more ethically sound than other methods because the participants are aware of the research
88
weaknesses of overt observation
people might change their behaviour if they know they are being observed
89
what is participant observation
when the researcher participants in the study
90
strengths of participant observation
the researcher develops a relationship with the group in the study
91
weaknesses of participant observation
the researcher loses objectivity by becoming part of the group
the participants might act differently if they know there is a researcher amongst them
92
what is non participant observation
when the researcher observes the activity without getting involved in it
93
strengths of non participation
the researcher can remain objective throughout the study
94
weaknesses of non participation
the researcher loses a sense of the group dynamics by staying separate from the group
95
what is structured observation
the researcher gee determines precise what behaviours are to be observed and uses a standardised checklist to record the frequency with which they are observed within a specific time frame
96
strengths of structured observation
controlled
can be repeated
97
weaknesses of structured observation
might miss relevant information if too controlled
98
what is unstructured observation
the observer recalls all relevant behaviour but has no system
99
strengths of unstructured
all behaviour is recorded
100
weakness of unstructured
not controlled or repeatable
101
what is inter-rather reliability
the test should give consistent results regardless of who administers it. this can be assessed by correlating the scores that each researcher produces and comparing them. consistenty is key
102
what is the nature and use of an interview
used to gather qualitative research- can be face to face or over the phone
103
what are advantages of interviews
rich data
pilot study
104
what are weaknesses of interviews
impractical
ethics
105
what is a structured interview
fixed set of questions that are the same for all participants
106
what are strengths of structured interviews
can be easily repeated
requires less skill
easier to analyse
107
weaknesses of structured interviews
interview bias can still occur
social desirability
data collection is restricted by pre determined questions
108
what is the nature and use of a unstructured interview
the interview starts with some general aims and questions and then let’s the interviewees answers guide subsequent questions
109
strengths of unstructured interviews
Detailed information can be obtained
High validity – good rapport
Deeper insight into thoughts and feelings
110
weaknesses of unstructured interviews
• Interviewer bias
• Requires training
• Harder to analyse
111
what are investigator effects
These can be anything that the researcher does which can affect how the participant behaves. If a researcher’s expectations influence how they behave towards their participants, the participants might respond to demand characteristics.
112
what is researcher bias
researchers’ expectations can influence how they design their study and how they behave towards the participants. Their expectations may influence how they take measurements and analyse their data, resulting in errors that can lead, to accepting a hypothesis that is actually false.
113
how can you avoid investigator effects
A research assistant can conduct the research using standardised procedures to avoid bias/ effects.
114
what is content analysis
Research analysing secondary data and data you have already collected. Data is split into categories.
115
describe the process involved in content analysis
A representative sample of qualitative data is collected, for example, from an interview, magazine Coding units are identified to analyse the data. A coding unit could be, for example, an act of violence. The qualitative data is then analysed to see how often each coding unit occurs.
116
on what type of data is content analysis used
secondary data
117
strengths of content analysis
• Inexpensive
• Ethics – participants are not directly involved, so less ethical issues.
118
weaknesses of content analysis
• Data analysis- can be very time consuming • Subjectivity
119
what is thematic analysis
making summaries of data and identifying key themes and categories. • The researcher becomes familiar with the data. Then they start to look for different themes,
review the themes, define and name the themes and then write a report.
120
strengths of thematicanalysis
• Qualitative data preserves the detail in the data
• Creating hypotheses during the analysis allows for new insights to be developed
• Some objectivity can be established by using triangulation – other sources of data are used to check conclusions
121
weaknesses of thematic analysis
• Deciding which categories to use and whether a statement fits a particular category
• Deciding what to leave out of the summary- data can be lost
• Subjective
122
how is the mean calculated
Adding all the scores in a data set and then dividing by the number of scores.
123
advantages of mean
Uses all scores in the data
It is a very sensitive statistic because it takes account of the exact distance between all the values of all the data
124
weaknesses of mean
If one of the values is extremely high or low (anomalous), then the overall mean can be very distorted and therefore misrepresent the data.
• It cannot be used with nominal data
125
what is mode
The score that occurs most often
126
what are strengths of mode
Shows the most common score
• Unaffected by extreme values and is
useful for discrete data and is the only method which can be used for nominal data.
127
what are weaknesses of mode
Sometimes there are so many modes that the data cannot be described using this statistic.
• Has little further use in data analysis
128
how is the median calculated
the middle score when the data is put in order
129
strengths of median
It’s quick and easy to work out
• It is not affected by extremely high or low scores
130
weaknesses of median
Not all the scores are used to work out the median
131
what is the range
highest score minus the lowest score
132
advantages of range
it is easy and quick to calculate
133
weaknesses of range
it completely ignores the central values of data set, so it can be misleading if there are very high or low scores
effected by extreme values
134
what is the standard deviation
measures on average how much scores deviate from the mean
135
advantages of standard deviation
all scores in the set are considered so it is more accurate than the range
136
weaknesses of standard deviation
it is not quick or easy to calculate
137
what is qualitative data
data involving words, videos or audio
138
what is quantitative data
numbers
139
what is primary and secondary data
Primary data is data collected first hand by the researcher. Secondary data is data collected from a source such as a book or newspaper (national statistics).
140
what is meta analysis
this is where you analyse the results from loads of different studies and come up with some general conclusions
141
what is a pilot study
a 'feasibility' study, is a small-scale preliminary study conducted before any large-scale quantitative research in order to evaluate the potential for a future, full-scale project. Pilot studies are a fundamental stage of the research process. Pilot studies allow researchers to check the methodology, standardise the instructions and allow the research can be conducted.
142
what is the nature and use of a questionnaire
can be written, face to face, on the phone or online
143
what is the design of questionnaire
open questions are questions that allow the participants to respond in any way and in as much detail as they like. This gives detailed, qualitative information. Closed questions limit the answers that can be given. They give quantitative data which is easier to analyse.
144
what are advantages of questionnaires
Practical – you can collect a lot of data
145
disadvantages
• Bad questions – leading questions or unclear questions can be a problem
• Biased samples
• Self-report
146
what is social desirability
People usually try to show themselves in the best possible light. They might not be completely truthful
but give answers that are more socially acceptable.
147
how does social desirability affect validity
Not a true representation of someone’s opinions/ thoughts/ feelings.
148
what is the nature and use of case studies
case studies have intensive descriptions of a single individual or case. Case studies allow researchers to analyse unusual cases in a lot of detail.
149
what are the advantages of case studies
rich data
unique cases
150
what are weaknesses of case studies
Causal relationship – cause and effect cannot be established
Cannot be generalised
151
what is a sample
a representative group of people from a target population
152
what is meant by a population
All the people in a particular group- for example, a certain age or
background
153
what is random sampling
this is when every member of a target group has an equal chance of being selected for the sample. This could be done either manually or by a computer.
154
what are advantages to random sampling
Fair – everyone has a chance of being selected
Sample is likely to be representative
155
what are weaknesses of random sampling
Not guaranteed to have a representative sample
The researcher may end up with a biased sample because the sample is too small.
156
what is a volunteer sampling
this is when people actively volunteer to be in a study by responding to a request for participants advertised by the researcher, for example, in a newspaper or on a notice board.
157
what are advantages of volunteering
A large number of people may respond • In-depth analysis and accurate results if
larger sample
158
what are weaknesses of volunteering
Not representative- only sample of
people who have responded
159
what is opportunity sampling
when the researcher samples whoever is available and willing to be studied. Since many researchers work in universities, they often use opportunity samples made up of students
160
what are advantages of opportunity sampling
quick and practical
161
what are weaknesses in opportunity sampling
Unlikely to be a representative sample
• Cannot generalise the findings
162
what is stratified sampling
this is where important subgroups in the population, for example, different age groups, are identified and a proportionate number of each is randomly obtained. For example, in a class of 20 students, ten are 16 years old, eight are 17-year olds, and two are 18 years old. If you take a stratified sample of 10 students, the number of 16-, 17- and 18- year-olds in the sample needs to be 50% of the full class. You would need five 16-year olds, four 17-year olds and one 18-year-old in your sample.
163
what are advantages of stratified sampling
Fairly representative sample
164
what weaknesses of stratified
• It is time-consuming because all potential participants need to be assessed and categorised.
• Some groups within a sample may not be represented if a small sample is used
165
what is systematic sampling
this is where every nth name from a sampling frame (a record of all the names in a population) is taken, for example, every 3rd name from a register, or every 50th name from a phone book.
166
advantages of systematic sampling
Simple and effective way of generating a sample with a random element
• Population is more likely to be evenly sampled
167
weaknesses of systematic sampling
Subgroups might be missed
• Not necessarily representative if the pattern used for the sample coincides with a pattern in the population.
168
what are alternative ways of getting consent
Presumptive consent: ask a similar group of people for consent.
Prior general consent: consent for different studies, including one that may involve deception. Retrospective consent: ask for consent during debrief.
169
what is nominal data
data represented in the form of categories. For example, how many students in the 6th form drive to school, how many walk etc.
Nominal data is discrete, one item can only appear in one category.
170
what is ordinal data
data which is ordered in some way. Ask everyone in the class how much they like the 6th form on a scale of 1 – 10.
Ordinal data does not have equal intervals between each unit. It would not make sense to say that someone who rated the 6th form as an 8 enjoys it twice as much as someone who rated it 4.
171
what are interval/ratio data
is based on numerical scales that include units of equal precisely defined size. Units of measurements for height, time and temperature for example.
172
how to do statistical testing
1. Null hypothesis – this is the prediction you want to test - You assume the null hypothesis is true
2. Significance level – this is the level of proof you are looking at before you read into your results
- The smaller the significance level the stronger the evidence you’re looking for that your
results are not just down to chance.
- A significance level is a probability and the number is between 0 and 1
- Significance levels are very small- usually 0.05 or less.
3. You turn your experimental results into a single statistics test
- You can find out what the probability is that this test statistic and your results were the
results of a fluke (making your null hypothesis true)
4. If the probability of your results being a fluke is less than the significance level, you can suggest
that your null hypothesis was not true. You can then assume that the difference between groups was down to the change your made in your independent variable.
- You reject the null hypothesis and assume your alternative hypothesis is true
5. Your results are therefore statistically significant (if you reject the null hypothesis)
6. If you do not reject the null hypothesis, it means that your results could have occurred by
chance
7. Using a significance level of 0.05 is suitable for most tests
- If the probability of your results being down to chance is less than or equal to (p≤ 0.05) then it is good evidence that the null hypothesis was not true.
- You are 95% confident in your conclusion
- If you use a significance level of 0.01, then you have really strong evidence that the null
hypothesis is not true. The researchers can be at least 99% confident.
173
mann whitney
- test of difference
- independant group
-ordinal data- scores
174
wilcoxon
- experimental design can be repeated measures or matched pairs
-alternative hypothesis
- there is a difference in people with ocd scores on happiness questionnaire before and after treatment
null hypothesis- there is no difference in people with ocd scores on a happiness questionnaire before and after treatment
175
spearman’s rho
- two sets of values at an ordinal level
- its a correlation so we are looking for a relationship
176
pearsons r
- both variables must be interval or ratio and be normally distributed
- the correlation of the two variables must fall between -1 and +1
- the closer r is to -1 and +1 the stronger the relationship
-degrees of freedom N-2
- a relationship between 2 co variables
177
related t tests
- repeated measures design or matched pairs
- test of difference with interval or ratio data
178
unrelated t-test
- independant groups
- interval data is needed
- test of difference
179
chi squared test
- test of difference or association
- the data is norminal and recorded as a frequency
-independent groups design- unrelated
180
features of science
- paradigms and paradigm shifts
- theory construct and hypothesis testing
- falsifiability
- replicability
- objectivity and the empirical method
181
paradigms and paradigm shifts
-kuhn stated that the way to distinguish between scientific and non scientific disciplines is to the shared set of assumptions and methods
-social sciences lack a universally accepted paradigm and should be seen as ‘pre-science’
-progress within an established science occurs when there is a scientific revolution
- a paradigm shift occurs when there is contradictory evidence to a theory
- cognitive neuroscience, and behavioural approach, classical and operant conditioning changes what we theorised about behaviour
182
theory construct and hypothesis testing
what is a theory?
• a set of general laws or principles that have the ability to explain particular events or behaviours
• theory construction occurs through gathering evidence via direct observations (the empirical method)
what is a hypothesis?
• prediction based on theory
• deduction new hypothesis from an existing theory
183
falsifiability
popper ‘genuine scientific theories should hold themselves up for hypothesis testing and the possibility of being proven false’
• even ‘proven’ research is not true, it has just not yet been proven false!
• ‘this supports’ or ‘this seems to support’ and the null hypothesis
184
replicability
an element of poppers hypothetical-deductive method
• trusted findings should be repeatable across a number of contexts and circumstances
• validity and reliability
185
objectivity and the empirical methods
• ‘critical distance’ - putting away any bias
• controlled laboratory studies
• experience- knowledge is determined only by experience and sensory perception (locke)
