Research Methods (Section C- 48 Marks) Flashcards
(314 cards)
1
Q
Book 1 of 4:
Name the key scientific principles in Psychology
A
Theory construction
Hypothesis Testing
Empirical method
Paradigms
Replicability
Objectivity
Falsifiability
2
Q
Define Theory Construction
A
The process of developing an explanation for the causes of behaviour by systematically gathering evidence and then organising this into a coherent account
3
Q
State and describe the method of developing a theory where there is not a pre-existing theory to begin with
A
Inductive reasoning-
-Make a specific observation
-Recognise a pattern that can be generalised and test it
-Draw a general conclusion or theory
4
Q
State and Describe the method of developing a theory which is pre-existing
A
Deductive reasoning-
-existing theory (e.g ‘research suggests we obey authority figures’)
-make a hypothesis
-experiment and collect data
5
Q
Define Empiricism
A
The belief that factual knowledge can only come from our direct experience with the world- conducting rigorous scientific research (not based on speculation)
6
Q
Define hypothesis testing
A
Theories should produce statements (hypothesis) that can be tested to prove its truthfulness
7
Q
Outline the process of hypothesis testing
A
- State the hypothesis
- Conduct experiment
- Choosing test statistics
- Decision making
- Drawing conclusions about population
8
Q
Outline the difference between an aim and a hypothesis
A
An aim is the information an experimenter wishes to gain from the research, a hypothesis is what they think the test results will be
9
Q
Describe what a null hypotheses states and the format of them
A
Predicts no significant effect or relationship between variables
‘There will be no significant relationship/difference between operationalised IV+DV’
10
Q
When to choose directional or non-directional hypotheses? What are they?
A
Directional= one tailed hypothesis- when there is previous evidence that suggests a possible outcome of the research.
Non-directional= two tailed hypothesis- when there is no consistent previous evidence that suggests a research outcome
11
Q
Describe the format for a directional hypothesis
A
‘Operationalised IV group 1 will have a significant increase/decrease on operationalised DV compared to IV group 2’
12
Q
Describe the format for a non-directional hypothesis
A
‘There will be a significant relationship/difference between operationalised IV group 1 and operationalised IV group 2
13
Q
Briefly outline the variables involved in hypothesis testing
A
IV: manipulated/changed variable
DV: the variable which is measured
Covariables: the variables in correlation (e.g population vs theft)
14
Q
Briefly summarise the difference between correlations and experiments
A
Correlations test for a relationship
Experiments test for a difference
(your hypothesis should mimic this language)
15
Q
Define paradigms and paradigm shifts
A
A set of shared assumptions and agreed methods within a subject discipline
Paradigm shift: the result of a scientific revolution where the dominant unifying theory changes
16
Q
Define replicability
A
The extent to which scientific procedures and findings can be repeated by other researchers
17
Q
Describe 3 ways which make research more replicable.
A
- Standardisation- keeping things the same for all participants, using standardised instructions
- Training researchers how to properly conduct research
- Under a controlled environment (e.g a lab)
18
Q
Define objectivity
A
Based on factual, unbiased analysis that is not open to interpretation. Personal bias is minimised.
19
Q
How do we keep research objective?
A
-Researchers keep a critical distance
-Higher levels of control and replicability through carefully designed methods, peer reviewed papers and blinded researchers
20
Q
Explain 2 reasons why replicability is important in psychology
A
- Being able to repeat research and find the same thing across contexts means it can be enlisted- more accurate
-Demonstrates measurements are reliable- e.g a personality test actually tests for personality only
21
Q
Define falsifiability
A
The principle that a theory cannot be considered scientific unless it admits the possibility of being proved untrue
22
Q
Define quantitative data
A
Numerical data that can be statistically analysed and converted easily into a graphical format, e.g milgram
23
Q
Outline two strengths of quantitative data
A
-easily to analyse statistically- trends and comparisons easily seen
-objective
24
Q
Outline 3 weaknesses of quantitative data
A
-lack of representativeness- lacks meaning and context
-responses narrow in explaining complex human behaviour
-lack validity
25
Define qualitative data
Non-numerical language based data (expressed in words)- e.g speaking to a patient
26
Give 3 strengths of qualitative data
-rich in detail
-meaningful insights
-high external validity- real world view
27
Give 2 weaknesses of qualitative data
-subjective- interpretations from researcher to researcher may differ
-preconceptions held by the researcher might lead to biased conclusions
28
Define primary data
Original data which is collected first hand by the researcher, specifically for that study
29
Outline 3 strengths of primary data
-more authentic
-specifically targets required information
-high levels of control mean less time wasted on irrelevant data
30
Outline a weakness of primary data
-lots of time money and effort required as it is entirely coordinated by the researcher
31
Define secondary data
Data collected by someone other than the person conducting the research- it already exists e.g reports, books etc
32
Outline 2 strengths of secondary data
-less time consuming, less effort required and less money spent
-collection and use of data much easier
33
Outline 3 weaknesses of secondary data
-concerns over accuracy and validity
-variability in the quality and specificity of the data
-may be incomplete or outdated, so unuseful= time wasted
34
Outline meta analysis
-a research method that uses secondary data
-does so by combining many previous findings from studies which test the same hypothesis, to gather an overall conclusion
35
Give a strength and weakness of meta analysis
-Strength: creates a larger more varied sample which is generalisable across larger populations- more valid
-Weakness: can be prone to publication bias- only considers studies with significant data- invalid
36
Outline what ethics are, describing how they are ensured in Britain
Ethics are a key part of psychological investigation- researchers have the responsibility to ensure their practice is morally correct. The British Psychological Society has a ‘code of ethics’ which is a set of guidelines for anyone carrying out psychological research in the UK.
37
State all the ethical considerations
Informed Consent
Deception
Confidentiality
Debrief
Right to Withdraw
Protection from Harm
38
Outline informed consent- how is it obtained?
Participants must be briefed on the aims of the investigation and what is required of them should they take part- put under no pressure via a consent form
39
Outline Right to Withdraw
Participants must be informed that they can leave the investigation at any point, and they don’t have to disclose why or face any penalty
40
Outline confidentiality- how is it ensured?
Participants should remain anonymous so data can’t be identified as theirs
Researchers shouldn’t obtain any irrelevant data to the study, and should anonymise scores via using numbers instead of names
41
Outline deception, and how is it used appropriately
-Sometimes participants are purposefully misled to mask the true aims of the investigation- to ensure valid results
- if deception is necessary, the person must be debriefed on the true aims after- and if they fibe consent to their data being used
42
Outline protection from harm. How is it obtained?
-It is the researchers responsibility to not cause any long term physical/mental damage
-research pre- approved by an ethics committee
-ensure they leave in the same physical+psychological state afterwards- help offered if not.
43
Outline what debriefing is. How is it carried out?
- when a study ends, the true motivations of the study should be revealed for ultimate transparency
- a verbal and written debrief is given, explaining the aim and any comparator groups used
44
What are the 4 key principles of ethics?
Respect
Integrity
Responsibility
Competence
45
What are the key parts of a consent form?
-space for name
-informed consent given (needs,expectations, time)
-understand right to withdraw due to harm
-the aims of the study
-no pressure placed on participant
-consent yes/no
46
What are the key parts of a debrief?
-thank them for taking part
-how data will be used (anonymity, comparator etc)
-withdraw any data
-counselling availability if needed
-any further questions?
47
Define population
The entire group or groups of individuals about whom the research is concerned
48
Define sample
A smaller group selected from the population, which is used to represent a larger group, where findings are generalised to the wider population
49
State all the types of sampling
Random
Systematic
Stratified
Opportunity
Volunteer
50
Define random sampling
Where every member of the population has an equal chance of being selected in the sample by entering all the names of the population
51
Define systematic sampling
Selecting every nth member of the population based on a characteristic, then randomly sampling from each subgroup proportionally
52
Define stratified sampling
Dividing the population into relevant subgroups based on a characteristic, then randomly sampling from each subgroup proportionally
53
Define opportunity sampling
Participants who are both willing and able to take part are chosen, particularly from 1 physical area
54
Define volunteer sampling
Individuals self select to be part of the study following an advertisement
55
Define bias in sampling
When certain groups or overly or underly represented in the sample selected- the opposite of stratified sampling.
56
Define generalisability
The extent to which findings and conclusions from an investigation can be broadly applied to the population
57
Define sampling technique
Methods used to select participants from a population to take part in research
58
How is a random sample collected?
• Get a complete list of all the names of people in the target population
• assign each name a number
• use a lottery method to select a decided sample size (computer method/ names in a hat)
59
1 strength and 1 weakness of random sampling
• Strength: objective due to the lack of researcher involvement and potentially representative due to laws of chance
• Weakness: difficult and time consuming as a full list of the target population is needed
Possibility of bias as chance isn’t a perfect science- if participants refuse it becomes more of a volunteer sample
60
How is a statified sample collected?
• Identify the strata (or subgroups)
• work out the representative proportions of each strata for the sample
• use random sampling to select the number needed in each strata
61
1 strength and 1 weakness of a stratified sample
Strength: most likely to lead to a representative sample- designed to reflect the population
Weakness: strata can’t reflect all the ways people differentiate
Time consuming to calculate the strata
62
How is an opportunity sample collected?
The researcher would ask anyone who is around at the time if they would like to take part
63
1 strength and 1 weakness of an opportunity sample
Strength: quick and convenient as participants are readily available- reduces time and cost
Weakness: unrepresentative as it is from one physical area and is subject to research bias as they have full control over sample selection
64
How is volunteer sample conducted?
The researcher places an advert in a relevant place (poster, newspaper, online) and waits for responses
65
1 strength and 1 weakness of volunteer sampling
-Strength: convenient- less input needed from researcher so less time consuming
Less chance of attrition as participants actually want to take part
-Weakness: volunteer bias is likely as there may be a certain type of person more likely to volunteer (demand characteristics)
66
How is a systematic sample collected?
•Create a sampling frame (everybody’s name in the population in alphabetical order)
•choose a sampling system (e.g every 5th person)
•start your sampling from a random point
67
1 strength and 1 weakness of systematic sampling
Strength: if the initial list is randomised then the sample is objective as the researcher has no involvement
Weakness: time consuming and people may refuse
Each person doesn’t have an equal chance especially if initial list isn’t randomised, so some unrepresentativeness
68
What is meant by a pilot study? (2)
Small scale preliminary studies carried out before the main research project
69
What is the purpose of pilot studies? (3)
-researchers can identify and address potential issues that may arise in the study, like logistical challenges
-ensures procedures are effective and can give insights into the feasibility of the research
-they increase the overall credibility and validity of the research, e.g by tackling any ethical issues
70
What is meant by extraneous variables
Any other variables apart from the IV that could possibly impact the DV- if not controlled they can decrease validity and affect outcomes
71
Explain what confounding variables are, outlining them with an example on teaching style on academic performance
-specific types of extraneous variable which vary systematically with the IV- provides an alternate explanation for the results
-e.g if the students have differentiating qualities of reading book, then this could provide an alternative explanation for the difference in student performance
72
State all 6 possible extraneous variables
Participant variables
Participant reactivity
Demand characteristics
Social desirability bias
Situational variables
Investigator effects
73
Define participant variables, giving examples
-minimising differences between participants
-such as age, gender, intelligence, background and mood/motivation
If not controlled, these can all distort the validity of the findings
74
Define participant reactivity
A tendency of participants to read cues from the research environment or researcher and change their behaviour accordingly
these can result in demand characteristics Social desirability
75
Define demand characteristics, mentioning why participants do this, and how it is avoided.
•Cues in an experimental setting which could lead to the participant guessing the aim of the study and change their behaviour- leading to bias
•participants do this to please or displease the researcher
•to reduce this, the true aim must be hidden via deception
76
Define situational variables, giving examples
Where the setting takes place- e.g keeping light, sound and temperature levels consistent
77
Define investigator effects/ researcher variables
•Factors such as researcher behaviour, appearance and gender which could affect responses- must be kept constant
•IE= when the researcher influences the participants e.g changing tone of voice
78
Give and describe two ways we control for participant variables (4)
•Experimental designs- using a repeated measure or matched pairs design (repeated allows participants to experience both conditions, matched pairs ensures similar members of population)
•Random allocation- assigning participants randomly into different groups in an experiment e.g placing names in a hat and randomly allocating
79
State the 6 ways of controlling for participant reactivity
Demand Characteristics:
•single-blind procedure
•double-blind procedure
•deception
•unobtrusive methods
•placebos in clinical trials
Social Desirability Bias:
•confidentiality and anonymity
80
Describe and explain how a single-blind procedure would decrease demand characteristics (2)
Where participants aren’t informed of the specific aims of the study- reducing the chance of participants changing their behaviour
81
Describe and explain how a double-blind procedure would decrease the chances of demand characteristics AND investigator effects (2)
Both participants and researchers are unaware of the true aims of the study, which also prevents investigator effects (cues from the researcher)
82
Describe and explain how deception would decrease the chances of demand characteristics (2).
State what would be carried out after. (1)
•By misleading participants about the true aims of the study, they would be less likely to change their behaviour accordingly to please/displease the researcher as they are unaware of the data yielded by the researcher
•a debrief discussing the true aims wouldn’t carried out after
83
Describe and explain how using unobtrusive methods would decrease the chances of demand characteristics (2)
By collecting data without directly interacting with the participant, they would be unaware of them being studied- so less likely to change their behaviour accordingly
84
Describe and explain how the use of placebos in clinical trials would decrease the chances of demand characteristics
They’d ensure that any affects are due to the actual treatment itself rather than the participants expectations, as they don’t know if they have the real drug or not
85
Describe and explain how anonymity and confidentiality during studies would decrease the chances of social desirability bias (2)
Because participant’s identities are hidden, there is less pressure to conform to societal norms, which encourages honest answers
86
State 4 ways of controlling for investigator effects in psychological research
Counterbalancing
Randomisation
Standardisation
Double-blind procedure
87
Describe and explain how counterbalancing would control for investigator effects (2)
Controls for order effects (e.g tiredness/ practice) which can affect participant performance. By ensuring all participants undergo the condition 1st and last, it isolates the IV’s affect.
remember ABBA- group A first then last for condition 2
88
Describe and explain how randomisation controls for investigator affects
Process of using random methods to order and select elements in an experiment
(e.g if participants have to recall 4 letter words, then the order of these will be randomised from person to person)
89
Describe and explain how standardisation would control for investigator effects
By maintaining uniform procedures for all participants in an experiment, (treated in the same way) it is ensured that the DV is only due to the chosen IV rather than experimental variations
90
Describe and explain how a double blind procedure would control for investigator effects (2)
Investigator is unaware of the purpose of the research (as well as the participant) so is less likely to give aware cues on the true aims
91
Define reliability
A measure of whether something stays the same (consistency), through using the exact same methods
92
There are two types of reliability. Define internal reliability
Measures the internal consistency of a measure such as whether all the questions in a questionnaire measure the same thing
93
Define external reliability
Assesses the consistency of a measure from one use to another- e.g if a person obtains a similar memory score one later after the original test
94
Name the 3 tests of reliability used in psychology
•Inter-observer reliability
•Split-half reliability
•Test-retest reliability
95
What is considered a high level of reliability in tests of reliability? Explain what this means
•A high correlation indicates good test-retest reliability
•In inter-observer, greater or equal to 0.8 is a good score as it shows the observers tests are similar
96
Outline inter-observer reliability
•Measures internal reliability
•Checks the agreement between different observers/raters when assessing the same behaviour
97
Outline spilt-half reliability
•Measures internal reliability
•Data collected in randomly spilt in half and either halves are compared to see if results taken from each part are similar
98
Outline Test-retest reliability
•Measures external reliability
•Involves administrating the same test to the same group months/years after the initial test to see if similar results are obtained
99
Outline 3 ways in which researchers can improve reliability. (6)
•Standardisation- ensure all aspects of the study are uniform across conditions+ participants
•Piloting- conducting preliminary studies before the main study to identify and address any sources of inconsitency
•Training researchers- providing useful training to researchers to limit subjective bias
100
Define validity
Accuracy- whether a study measures what is claims to be measuring
101
Define internal validity and name the 3 types of it
A measure of whether the results obtained are solely due to the IV
•Face validity
•Construct validity
•Concurrent validity
102
Outline face validity
A measure of whether a tool looks subjectively promising that it measures what it’s supposed to
103
Outline construct validity
Asks whether a measure measures the concept it’s supposed to
104
Outline concurrent validity
Asks whether a measure is in agreement with existing measures that are validated to test the same concept
105
Define external validity and name the 3 types of it
A measure of whether data can be generalised to other situations outside of the initial
research environment
•Ecological validity
•Population validity
•Temporal validity
106
Outline ecological validity, explaining an example of a study which would lack this
Whether data is generalisable to the real world, based on conditions of the procedure
•lab studies have low ecological validity as they follow strict conditions which could lead to the participants acting unusually
107
Outline population validity
Whether data from the sample is generalisable to the entire population (representativeness)
108
Outline temporal validity, giving an example of an approach which has high TV
This is high when research findings fully apply across time
•Wundt’s method of introspection is still used today
109
Describe how researchers can improve internal validity( 1/2) Relate to construct validity (5)
•Random allocation- randomly assigned participants to the different groups
•Blinding procedures
•Standardised procedures
•Pilot testing- refine measurement tools and procedures
•Eliminate con. variables (ensure changes to DV due to IV)
110
Describe how researchers can improve internal validity (2/2) relate to concurrent validity (2)
•Use multiple measures of the DV and make many comparisons with established measures which measure the same construct
111
Describe how researchers can improve external validity (1/3) relate to ecological validity (3)
•Use tasks that closely mimic real life, and are high in mundane realism
•Unobtrusive measures- less likely to change participant’s behaviour
•Naturalistic settings- measure behaviours in the participants natural environment e.g home
112
Describe how researchers can improve external validity (2/3) relate to population validity (2)
•Large sample sizes- more representativeness
•Representative sampling techniques (Stratified)
113
Describe how researchers can improve external validity (3/3) relate to temporal validity
•Use long term studies
•Compare to past historical events/studies
114
Book 2 of 4:
Identify the 4 types of experiment (experimental methods), stating whether they are related to the setting OR manipulation of the IV
Lab- setting
Field- setting
Natural- IV manipulation
Quasi- IV manipulation
115
Define lab experiment, giving an example
Conducted in a controlled environment where variables can be manipulated
•e.g: reaction time measured in a controlled lab setting
116
Define field experiment, giving an example
Conducted in natural settings where variables can be manipulated
•e.g: noise level effects on concentration in a work environment
117
Define natural experiment, giving an example
Occur naturally without researcher intervention- IV is changed naturally
•e.g: effects of natural disaster on mental health- comparisons with no IV
118
Define quasi experiment, giving an example
Where the researcher isn’t able to manipulate the IV and unable to allocate participants to certain conditions
•e.g: theory of mind on people with autism/tourettes - already existing so no IV manipulation
119
Give 3 strengths of lab experiments
•High control of extraneous variables
•Increases internal reliability
•Replicable+ internal reliability
120
Give 2 weaknesses of lab experiments
• Little ecological validity
• Risk of demand characteristics- change of behaviour as unnatural
121
Give 2 strengths of field experiments
• High in ecological validity
• Less chance of demand characteristics
122
Give 2 weaknesses of field experiments
• More difficult to control extraneous variables
• Harder to replicate- reduces external reliability
123
Give 2 strengths of natural and quasi experiments
• Provides research opportunities for variables due to practical reasons
• High in ecological validity- study of real world issues
124
Give 2 weaknesses of natural and quasi experiments
• Often confounding variables- unable to allocate participants randomly
• Natural experiments are a rare opportunity- hard to get access to
125
Identify the 3 types of experimental designs
Repeated measures
Independent measures
Matched pairs
126
Define a repeated measures experimental design, giving an example
Involves using the same group of participants across all conditions- condition 1 score compared to condition 2 score,
•e.g effects of coffee on memory performance- same participants with coffee/placebo
127
Define independent measures experimental design, giving an example
Assigning different groups of participants to different measures
•e.g: two separate groups of students with traditional/ modern teaching- exam scores compared across groups
128
Define matched pairs experimental design, giving an example
Matching participants on similar characteristics like IQ, gender, age before assigning them to different conditions
•e.g: IQ test on 50 people- 25 pairs drawn with most similar score, assigned to either IV group
129
Outline two strengths of a repeated measures experimental design
• Participant variables are controlled- high validity
• Fewer participants saves time+money
130
Outline a key weakness of a repeated measures experimental design. How can this be accounted for? (3)
Each participant has 2 tasks, so could cause demand characteristics and order effects
•use counterbalancing to minimise these effects
131
Outline one weakness of an independent measures experimental design
Need to obtain more participants- time+money
132
Outline two strengths of an independent measures experimental design
• Order effects aren’t a problem- only 1 condition
• Participants less likely to guess the aim of the study as only exposed to 1 condition
133
Outline 3 strengths of a matched pairs experimental design
• Order effects not a problem- 1 condition
• Less likely to guess the aim of the study, so less demand characteristics
• Participant variables are controlled
134
Outline two weaknesses of a matched pairs experimental design
• More time consuming and less practically efficient
• Can’t fully control all participant variables
135
State 3 rules for drawing a histogram
• Bars touch the axis and touch each other
• X-axis= IV
• Y-axis= frequency within each interval
136
Identify the 6 types of observation used in psychological research
Naturalistic observation
Controlled observation
Participant observation
Non-participant observation
Overt observation
Covert observation
137
What is the main difference between naturalistic and controlled observations?
The location in which they are carried out
138
Define naturalistic observation, giving an example
A research methods that involves observing subjects in their natural environment
•e.g: observing parent+children play in a park
139
Define controlled observation, giving an example
A research method where an observer examines participants in a controlled environment
•e.g: observe parent+child play in a laboratory
140
Explain one strength of naturalistic observations (2)
A realistic environment means the behaviour may be more true to real life, increasing external validity
141
State two weaknesses of naturalistic observations (2)
• Little control over other variables, so lower internal validity
• Replication more difficult
142
Explain one strength of controlled observations (2)
Allowed focus on particular behaviours, making studies easier to replicate
143
Explain one weakness of controlled observations (2)
Feels unnatural to participants, so they may act different than in real life, decreasing external validity
144
What is the main difference between covert and overt observations?
Participant awareness
145
Define covert observations, giving an example
A research method involving observing participants without their knowledge
•e.g: classroom behaviour study with hidden cameras
146
Define overt observations, giving an example
A research method where participants are aware they’re being observed
•e.g: classroom behaviour study with observers in the room
147
Explain one strength of covert observations (3)
Participants are likely to behave more naturally, resulting in higher validity and reducing demand characteristics
148
State 2 weaknesses of covert observations
• More ethics issues as invasion of privacy
• Researcher bias
149
State one strength of overt observations
Reduced ethical issues as informed consent is gained
150
Explain one weakness of overt observations (3)
Participants are more likely to alter their behaviour, increasing the chance of demand characteristics, lowering validity
151
What is the main difference between participant and non-participant observations?
Researcher proximity to participants
152
Define participant observations, giving an example
A research method where the researcher joins the group being studied and participants
•e.g: observating AND taking part in a gym session with gym users
153
Define non-participant observations, giving an example
A research method where the researcher recorded data without actively participating themself
•e.g: observing gym users as a PT without taking part
154
State two strengths of participant observations. Explain why one of them benefits psychological research (4)
• Participants less aware of researcher presence, meaning more natural behaviour, increasing validity
• Insider insight
155
Describe two weaknesses of participant observations (4)
• Reduced objectivity- more chance of observer bias
• Difficult to monitor and record information in an unobtrusive way (hard to take notes)
156
Explain one strength of non-participant observations (2)
More objective as researcher is removed from the situation- at a physical and psychological distance
157
Explain one weakness of non-participant observations (2)
The observer may misinterpret the communications in the group as they are an outsider- may reduce validity
158
Identify the 4 types of observational design
Structured observation
Unstructured observation
Event sampling
Time sampling
159
Define structured observation, giving an example
The researcher uses a predefined framework/checklist to observe and record behaviours
•e.g: relevant behaviours assigned before, such as laughter
160
Define unstructured observation, giving an example
Doesn’t involve a predefined framework- comprehensive and flexible take on data collection
•e.g: any behaviours are noted
161
State 3 strengths of structured observation
• Collecting data made easier and more scientific
• Quantitative data (easier to analyse
• Inter-observer reliably easier to establish
162
State 2 weaknesses of structured observation
• Some behaviours may be unimportant
• Quantitative data may lack detail
163
State one strength of unstructured observation
Provides more in depth and detailed results
164
State 2 weaknesses of unstructured observation
• Produces qualitative data- difficult to analyse
• Greater risk of observer bias
165
What is meant by behavioural categories?
Specific, clearly defined behaviours that are to be observed and recorded during the study
166
Define event sampling, giving an example
Recording every instance of a behaviour whenever it happens in an observation period
•e.g: researchers note each time a student raises their hand
167
Define time sampling, giving an example
Observing and recording behaviours at specific, regular intervals
•e.g: observers record how many times a student looks at their phone for 1 minute every 10 minutes, and after an hour multiplies this amount by 10
168
Explain one strength of event sampling (2)
Useful if desired behaviour happens infrequently- may be missed with time sampling
169
State one weakness of event sampling
If too complex, observer may overlook important details
170
Explain one strength of time sampling (2)
Effective in reducing the number of observations, making it easier to manage as there is likely to be reoccurring behaviours
171
Explain one weakness of time sampling (2)
May be instances where behaviour is missed, giving a limited understanding of what behaviours actually occurred
172
What is meant by a questionnaire? (2)
A research instrument consisting of a series of written questions designed to gather information from respondents
173
Describe what open questions are and what data they provide (2) +give an example
Open questions allows respondents to answer in as little or as much detail, providing qualitative data
•e.g: ‘how do you feel about the current education system?’
174
Describe what closed questions are and what data they provide (2)
Questions that provide respondents with a set of predefined answers, yielding quantitative data
175
What are the 4 examples of closed questions?
Fixed choice
Likert scale
Semantic differential
Rating scale
176
Define fixed choice questions, giving an example
Provide a limited range of answers
•e.g: ‘Do you agree with the current education system?’ Yes/No
177
Define likert scale questions, giving an example
Asks respondents to indicate level of agreement from 1-5
•e.g: ‘to what extent do you agree with the following statement: “the current education system is enjoyable”
SD D N A SA
178
Define semantic differential questions, giving an example
Asks respondents to rate a concept between two bipolar adjectives
•e.g: ‘please rate the current education system on the following scale’
Effective- - - - -Ineffective
179
Define rating scale questions, giving an example
Asks respondents to assign a value, typically numerical, to indicate their judgment
•e.g: ‘how would you rate the overall quality of the current education system on a scale of 1-10, where 1 is very poor and 10 is excellent?’
1 2 3 4 5 6 7 8 9 10
180
State two strengths of open questions
• Qualitative data- rich in detail and valid understanding
• Free reign- honesty and depth, providing validity
181
State two weaknesses of open questions
• Difficult to analyse- open to interpretation
• Cannot statistically compare
182
State two strengths of fixed choice questions
• Easier to analyse- limited answers so more objective
• Easier to compare
183
State two weaknesses of fixed choice questions
• Narrow range and lacks validity as hard to understand
• Answers may not reflect true feelings= even less validity
184
State two strengths of likert scale questions
• Indicates the strength of their agreement- more insight into behaviour
• Data easy to analyse and compare
185
State two weaknesses of likert scale questions
• Still lacks detail and reasons for answers
• May show central tendency bias
186
State two strengths of semantic differential questions
• More detail as extent of attitude shown
• Easy to analyse
187
State two weaknesses of semantic differential questions
• Participants may interpret scale subjectively
• Central tendency bias
188
State two strengths of rating scale questions
• More insight- strength of feeling shown
• Comparisons made between people
189
State two weaknesses of rating scale questions
• May value scale subjectively
• Central tendency bias
190
What are the 3 things to remember when constructing a questionnaire?
• Ensure you brief participants at the start of the questionnaire
• Ensure questions aren’t ambiguous or leading
• Ensure simple, universalised language is used
191
What are the 3 things to remember NOT to do when constructing a questionnaire?
• Do not have overlapping questions/ too few choices
• Don’t ask for personal details- if you do then do so at the end
• Don’t include technical or vague terms that could lead to confusion
192
Outline the 4 stages of questionnaire development
1• Decide what attitudes/behaviours you want to investigate or measure
2• Decide whether you want to collect quantitative or qualitative data
3• Run a pilot study of the intended study using the questionnaire
4• If there are any issues then participants will feedback- modify questionnaire before full scale study
193
Describe two strengths of questionnaires
• Relatively cheap and quick
• Responses likely to be honest as they can be completed privately
194
Describe 3 weaknesses of questionnaires
• Response rates can be low and data may lack generalisability
• May be flawed if questions are poorly designed- scew results
• Cannot get meaning or clarification on the responses accurately due to social desirability- reduced validity
195
What is meant by a self report? (2)
Method of data collection where individuals provide subjective information about their feelings- helps understand internal psychological states
196
What is meant by a structured interview? (2)
Follows a predetermined set of questions in a specific order- interviewer doesn’t deviate from these chosen questions
197
Describe two strengths of structured interviews
• You can collect useful demographic data about participants
• Results can be checked for reliability (if >0.8)
198
Describe two weaknesses of structured interviews
• Doesn’t allow participants to expand- reduced validity
• Participants may feel frustrated- lower ecological validity
199
What is meant by a semi-structured interview? (2)
Follows a guided topic or framework of questions but allows flexibility for how they’re addressed- e.g follow up questions enabled
200
Describe a strength of semi-structured interviews
The ability to ask follow up questions retrieves detailed, in depth data
201
Describe 3 weaknesses of semi-structured interviews
• Highly trained inter-viewers required- costly
• Only reliable and compatible to a certain extent, affecting replicability
• Follow up questions are subjective
202
What is meant by an unstructured interview? (2)
Don’t follow a specific set of questions- allowing for a more conversational and open- ended interaction with a trained interviewer to guide it
203
State two strengths of unstructured interviews
• Less likely to show demand characteristics
• Most likely to yield ecologically valid data
204
State 4 weaknesses of unstructured interviews
• High skilled interviewer required- more training needed to make interview smooth
• Not possible to replicate
• Data difficult to compare
• Time- consuming
205
State 3 ways in which researchers record participant responses
• Taking notes DURING the interview
• Taking notes AFTER the interview
• Tape recorder- transcribing later
206
State a strength and a weakness of taking notes during an interview
• S: prevents detail being lost
• W: lowers ecological validity
207
State a strength and weakness of taking notes after an interview
• S: will not disrupt the interview
• W: details may be lost due to forgetting
208
State a strength and a weakness of using a tape recorder to record notes
• S: increases validity as unobtrusive
• W: cannot record non-verbal details like body language
209
Describe 2 strengths of interviews (in general)
• Allows participants to freely express themselves
• Detailed information can be obtained- allows researcher to clarify the significance of the information being provided
210
Describe two weaknesses of interviews (in general)
• Greater chance of investigator effects as interviewer heavily involved in the study
• Time consuming and training is costly
211
Define the term ‘self report’
Any method asking participants about their feelings, beliefs or attitudes
includes questionnaires and interviews
212
Describe one strength and one weaknesses of self reports (in general)
• S: allows researchers to gather detail into people’s feelings
• W: subject to social desirability bias and therefore may lack validity
213
Outline what is meant by a correlation
The statistical technique used to find the relationship between two co-variables
214
Compare correlations and experiments (3)
• Correlations identify relationships between variables, experiments manipulate the IV to observe DV effect
• Correlations don’t establish causation, experiments allow for cause- effect relationships to be established
• Correlations are useful for preliminary research, experiments involve control groups and random assignment to limit bias+ confounding variables
215
Outline what is meant by positive, negative and no correlation
• PC: As X increases, Y increases proportionally
• NC: as X increases, Y decreases proportionally
• NOC: no trend in X and Y
216
Outline what is meant by a ‘correlation coefficient’
The strength and direction of a correlation- ranges from +1 to -1 as a statistical measure
217
What correlation coefficient does an r value of +0.66 indicate?
Strong+ (0.6-0.8)
218
What correlation coefficient does an r value of -0.23 indicate?
Weak- (-0.2- -0.4)
219
What correlation coefficient does an r value of -1.0 indicate?
Perfect
220
What correlation coefficient does an r value of 0.18 indicate?
Very weak+ (0-0.2)
221
What correlation coefficient does an r value of -0.47 indicate?
Moderate- (-0.4 -0.6)
222
What correlation coefficient does an r value of 0.99 indicate?
Very strong (0.8-0.99)
223
State a correlation hypothesis of steps done in a day and tiredness rating at night (/10)
There will be a significant relationship between the amount of steps and tiredness rating
224
Book 3 of 4: Outline what is meant by a case study, describing the key features (3)
•An in-depth, detailed examination of an individual, group of situation
•Usually longitudinal in nature- span over several years
•Collecting comprehensive data to develop a complex understanding
225
Outline two key case studies in psychology
• Freud (Little Hans)- focused in detail on one person about a complex theory (The Oedipus Complex)
• The Case of HM- brain surgery- loss of memory due to removal of the hippocampus- unique case with focus on one topic in detail
226
Outline 3 strengths of case studies
• In depth analysis which brings high levels of validity
• Studying abnormal psychology can give insight into how something works when it is functioning correctly
• The detail collected may lead to interesting findings
227
Outline 3 weaknesses of case studies
• Little control over extraneous variables- difficult to establish causal relationships
• Poor reliability- they’re unusual so hard to replicate
• Small sample size- hard to generalise to wider population
• Researcher bias as they may be more involved
228
What is meant by content analysis? Give an example.
A method used to analyse qualitative data by quantifying it
•e.g: a research examines frequency of opposite/negative words in therapy
229
Outline the procedure for a content analysis (5)
1• A sample of materials is examined by at least 2 different researchers
2• Reading/looking over the material leads to identifying suitable relevant categories
3• The categaories are operationalised
4• Coding occurs- two researchers read over the material and count the frequency of each event
5• Frequencies tallied by each researcher and compared for inter-rater reliability
230
Outline 3 strengths of content analysis
• Useful for gathering data from a wide range of areas
• High ecological validity as participant talks about real life experiences
• Reliable as they can easily be replicated
231
Outline 2 weaknesses of content analysis
• Can be time consuming as it is difficult to objectively operationalise coding units
• Illusion of objectivity: system may be biased by the researcher
232
What is meant by thematic analysis? Give an example
A qualitative method for identifying and analysing patterns within data- more flexible and interpretative
•e.g: exploring themes in resilience about people who have experienced trauma
233
Outline the procedure for carrying out thematic analysis (6)
1• Familiarise yourself with the data- look for repeating patterns
2• Begin coding- write initial codes into a transcript
3• When all codes are identified and listed, search for themes (sets of codes grouped together at a broader level)
4• Seperate between major and sub-themes clearly that explain the data
5• Define and name themes- make a detailed account of each theme
6• Producing the report- a logical and coherent write up- data should tell a story through themes
234
Outline the three differences between content and thematic analysis
1• Content is quantitative, thematic is qualitative- counting against interpreting themes
2• Coding approach- content uses predefined categories, thematic is flexible uses interpretative coding
3• Depth of analysis- content follows an objective and structured interview, thematic follows deeper, more nuanced understanding
235
Outline two strengths of thematic analysis
• Useful for analysing qualitative data so the richness of data is not lost
• Can check concurrent validity by comparing to another similar validated piece of data
236
Outline two weaknesses of thematic analysis
• Lacks objectivity
• Prone to subjective interpretation- people tend to be studied indirectly and so communication can be analysed outside of the context
237
Define nominal data , giving an example
Frequency data where data is categorised without a specific order- qualitative and categorical
•e.g: gender (male or female) or fruits (banana, apple, orange)
238
Define ordinal data, giving an example
Data that is presented in rank order but does not specify the size of differences between ranks- still qualitative
•e.g: school grades, education level (bachelor,masters,PhD), seniority level (junior/mid/senior)
239
Define interval data, giving an example
Quantitative data measured in fixed units where values are meaningful with equal Intervals between values, but there is no true zero point (can go below zero)
•e.g: degrees Celsius)
240
Define ratio data, giving an example
Has all the properties of interval data, as well as a true zero point- cannot go below 0.
•e.g: weight, height, heart rate
241
What are the mean, median and mode known as? What does this mean?
Measures of central tendency- a single value which represents the centre of a dataset
242
When should a mean be used?
For interval or ratio data that are symmetrically distributed without outliers
(No. Numbers divided by total amount)
243
State two strengths of using the mean as a measure of central tendency
• Includes every value in the dataset
• Best for normal distributions without outliers
244
State two weaknesses of the mean
• Susceptible to the influence of outliers
• Bot suitable for a screwed distribution
245
When should the median be used?
For ordinal, interval or ratio data- especially when the data is skewed and contains outliers
(middle number)
246
One strength of using the median
Less effected by outliers/skewed data
247
State two weaknesses of using the median as a measure of central tendency
• May not be representative of the rest of the values
• Less sensitive than the mean
248
When should the mode be used?
For nominal data or any data where there is a high frequency of specific values
(most common)
249
A strength of using the mode?
Useful when dealing with categorical data to understand the most common category
250
A weakness of using the mode?
Not very useful/unique and issues may be caused when two+ values share the highest frequency
251
What % of data falls within one standard deviation of the mean in a normal distribution?
68%
252
What % of data falls within two standard deviations of the mean in a standard distribution?
95%
253
What % of data falls within 3 standard deviations of the mean in a standard distribution?
99.7%
254
What is meant by a normal distribution? Give an example in psychology to outline this.
The mean, median and mode are all equal and at the centre, symmetrical graph
•e.g: IQ scores in a population- most fall around the mean, with very few being extremely high or low
255
What is meant by a positively skewed distribution curve? (3) Give an example in psychology to outline this.
•Asymmetrical with a long tail on the right- concentration of data on the left
•Mean>Median>Mode (mean largest, mode smallest)
•e.g: income levels in a population often exhibit a positive skew- most people earning lower incomes and very few earning high incomes
256
What is meant by a negatively skewed distribution curve? (3) give an example in psychology to outline this.
•Asymmetrical with a long tail on the left- concentration of data on the right
•Mean
257
What is meant by measures of dispersion? Give examples
•The spread or variability of a dataset
•Range or standard deviation
258
How to calculate the range and when to use?
(Highest-lowest) -1
•useful for a quick, basic measure of dispersion in interval or ratio data
259
State one strength of the range
Useful and easy to calculate
260
State one weakness of the range
Vulnerable to extreme scores- can look misleading
261
When to use standard deviation?
Best used with interval or ratio data that are normally a distributed presentation of quantitative data
262
Explain one strength of using the standard deviation (2)
Not as effected by extreme values as they take every days score into account- more accurate
263
State 2 weaknesses of using standard deviation as a measure of dispersion
• Assumes a normal distribution
• Still sensitive to outliers
• Only used when an IV is plotted against the frequency of it
264
What is the term for the likelihood of an event occurring?
Probability
265
What level of significance is most commonly used in psychology?
P is smaller or equal to 0.05 (5% probability due to chance)
266
What p value is used otherwise? Why? (2)
Equal to or less than 0.01- in studies requiring high confidence e.g drug testing
267
State three assumptions of parametric tests
• Data is normally distributed
• Variances are equal across groups
• Data is at interval or ratio level
268
2 advantages of parametric tests?
• More powerful than nonparametric test when assumptions are met
• Allows for more detailed inferences about population parameters
269
A disadvantage of parametric tests?
Not suitable when data does not meet the assumptions (non-normal distribution, ordinal data)
270
State two assumptions of non-parametric tests
• Few or no assumptions about data distribution
• Can be used with ordinal or non-normally distributed interval data
271
2 advantages of non-parametric tests?
• More flexible with fewer assumptions about the data
• Useful for small sample sizes or ordinal data
272
2 disadvantages of non-parametric tests?
• Less powerful than parametric tests when parametric assumptions are met
• Limited in the detail they can provide about the population parameters
273
How do you know when the test is referring to an experiment?
When the hypothesis is framed to compare groups or conditions- e.g difference in test scores between students who study in the morning and at night
274
What is the difference in the variables involved in an experiment and a correlation?
•Experiment: at least one independent variable and one dependent variable
•Correlation: both variables are co variables (two Dependent variables)- e.g hours of study and exam scores
275
When deciding the stats test, does matched pairs go under independent or repeated measures?
Independent
different participants are used for either condition
276
What variable should the level of measurement be decided on?
The dependant variables- independent variables are always categorical (nominal)
277
When deciding which stats test, and there are two dependent variables with different levels of measurement, which one should be used to interpret the table?
The one with the lowest level of measurement (so nominal or ordinal- nominal has the lowest)
278
Difference, independent measures, at least ordinal data
Mann Whitney U
Symbol= U
279
Difference, repeated measures, nominal data
Sign test
Symbol= S
280
Correlation, interval/ratio data
Pearson’s product moment
Symbol= R
281
Correlation, at least ordinal data
Spearman’s Rho
Symbol= Rs
282
Difference, independent measures, interval/ratio data
Unrelated t-test
Symbol= R
283
Difference, independent measures, nominal data
Chi Squared
Symbol=X^2
284
Difference, repeated measures, at least ordinal data
Wilcoxon test
Symbol=T
285
Difference, repeated measures, interval/ratio data
Related t-test
Symbol=R
286
Correlation, nominal data
Chi squared
Symbol=X^2
287
How do remember rule about calculated value being greater or smaller than critical value?
•If there is an R anywhere in the test, the calculated value must be equal to or greateR than the critical value for the test to be significant
•If there isn’t an R anywhere in the test, the calculated value must be equal to or less than the critical value for the test to be significant
288
How to tell what critical value is?
Value in the table, indicated by degrees of freedom/ level of significance used
289
In a Spearman’s Rho test, the critical value is greater than the calculated value. Is this significant? Explain.
Not significant- the calculated value should be greater than the critical value (as the test contains an R)
290
In the sign test the critical value is less than the calculated value. Is this test significant? Explain.
Significant as calculated value should be greater than the critical value (as test contains an R)
291
Outline how to write up significance statements (5)
1• State whether the calculated value is greater than/less or equal to the critical value, putting the values in brackets
2• State whether the result are significant or not
3• State whether the null is accepted or rejected, THEN the alternate
4• Write out the relevant hypothesis (whichever is accepted)
5• Then report the figures in brackets, in this order:
• calculated value
• the number of participants used in analysis- N=
(df if chi squared
• report whether p was more or less than 0.05- depending if null or alternate was accepted
• finally write whether the hypothesis was one or two tailed
292
Write out an example significance statement of a spearman’s rho test, on annual income and age, with 10 participants (4)
one-tailed
Calc value= 0.88
Crit value= 0.564
As the calculated value of rho (0.88) is higher than the critical value (0.564), the results are significant. Therefore, the null hypothesis can be rejected and alternate hypothesis accepted. It can be reported that there is a significant positive relationship between age and annual income (rS=0.88, N=10, p<0.05, one-tailed)
293
Write out an example of a significance statement of a Mann Whitney U test.
DV= maths score test (4)
IV= part of a maths scheme or not
Condition 1= 9
Condition 2= 10
calc value = 8
crit value = 24
One tailed
As the calculated value of U (8) is less than the critical value (24), the results are significant. Therefore, the null hypothesis can be rejected and the alternate hypothesis can be accepted. It can be reported that children using the maths scheme attain significantly higher maths scores than children not using the maths scheme. (U=8, N1=9, N2=10, P<0.05,one-tailed)
294
Write out an example significance statement of a chi squared test, with subject studied against personality type. (4)
df=1
two-tailed
calc value= 3.22
crit value= 3.84
As the calculated value of X2 (3.22) is less than the critical value (3.84), the results are not significant. Therefore, the null hypothesis must be accepted and the alternate hypothesis rejected. It can be reported that there is no significant difference between the subject studied and personality (X2=3.22, df=1, p>0.05, two-tailed)
295
What is meant by a type 1 error?
False positive- wrongly accepts the alternate hypothesis when the null hypothesis was true
296
What is meant by a type 2 error?
False negative- when the null hypothesis is wrongly accepted, when the alternate hypothesis is actually true, missing the genuine effect
297
Explain how to reduce the chance of a type 1 error (2)
Reduce the significance level- e.g 0.01 instead of 0.05- less probability that it occurred due to chance
298
Explain how to reduce the chance of a type 2 error (2)
Using a larger sample size- allows for a greater correlation/difference to be seen
299
Null hypothesis: Dave is having a cardiac arrest.
Write a type 1 and 2 error in this case. (2)
Type 1: Dave thinks he is having a cardiac arrest, when he actually isn’t.
Type 2: Dave doesn’t think he is having a cardiac arrest, when he actually is.
300
Which statistical test needs to be conducted yourself?
The sign test
(difference, repeated measures, nominal data)
301
Outline how to conduct the sign test (4)
• Tally the number of pluses and minuses in the data (from the independent variables)
• The lower number is the calculated value. (E.g, if 4 pluses and 6 minuses, the 4 is the calculated value)
• Use the information in the stem (no participants, directional/non, level of significance) to find the critical value
-if some results show no + or -, exclude these from the number of participants (only + or - are included)
• If significant, calculated value is equal to or lower than critical value (as no R in name)
302
Write a significance statement for the sign test (4)
DV= energy drink/water
IV= works spoken in 1 minute
calc value= 3
crit value= 1
N=9
two-tailed
As the calculated value (S=3) is higher than the critical value (1), the result is not significant. Therefore, the null hypothesis has to be accepted and the alternate hypothesis rejected. It can be reported that there is no significant difference between water and an energy drink in the number of words spoken in a minute. (S=3, N=9, P>0.05, two-tailed)
303
State the 8 sections of a report, in order
Title
Abstract
Introduction
Method
Results
Discussion
References
Appendices
304
Describe the features of an abstract in a scientific report (3)
• A short-paragraph long section at the very beginning of a report
• Usually a 100-300 word brief overview of what the contents will be about
• Summary of the aims, methods, results and conclusions of the study
305
Describe the features of the appendices in a scientific report (2)
At the very end of the report- includes information that would swamp the reader due to over elaborate details
306
Describe what would be found in the introduction section of a scientific report (2)
• Presents the problem and reviews previous findings on the topic
• Provides context into the research
307
Define peer review (2)
The assessment of scientific work by specialists who are in the same field
308
Outline the process of peer review (6)
1• Quality control- ensures validity and reliability of research
2• Credibility and trust- makes research more credible, building trust in scientific theories
3• Improvement and refinement- peer reviewers provide feedback for significant enhancements
4• Preventing plagiarism and misconduct- by scrutinising work reviewers can identify issues
5• Encouraging rigorous scientific standards- promotes adherence to high scientific standards
6• Gatekeeping- peer review ensures only research that meets certain standards is published
309
What is the purpose of peer review? (3)
• To allocate research funding
• To validate the quality and relevance of the research- all elements are assessed for accuracy
• To suggest amendments/ improvements- reviewers may request minor changes to the work
310
State two strengths of peer review
• The ‘peer’ is anonymous- more like to produce an honest appraisal
• Useful in assessing the validity of new research- allows for higher quality research to be produced
311
Outline 3 weaknesses of peer review
• Some reviewers may use their anonymity to criticise rival researchers, as they are in direct competition for funding
• Publication bias- some editors may only publish significant headline grabbing findings to increase their credibility. They may also disregard ones that accept the null, and publish positive results (file drawer problem). This masks the truth about data
• May suppress opposition to mainstream theories, maintaining the status quo within particular scientific theories
• Reviewers may be overly critical with research that opposes theirs
• Established scientists are more likely to be chosen- so findings that agree with the consensus are passed, slowing down the rate of change
•
312
What is meant by the economy?
The state of a country or region in terms of the production and consumption of its goods and services
313
Outline why it is important to consider the economy in psychological research (3)
• Absence from work costs the economy £15 billion a year- 1/3rd caused by mild to moderate mental health disorders
• PR into causes+treatments of mental disorders is supporting a healthy workforce
• If quickly diagnosed due to good PR, they can access treatment quicker
314
Explain how psychological research has impacted childcare (2)
Before childcare was seen as a mothers responsibility- recently research shows fathers just fulfil a different role, but just as important- PR has shown both parents are capable of providing emotional support
