1
Q
what are the two different types of hypothesis and explain them
A
- null hypothesis: have no difference or correlation, idea that the IV will not effect the DV (e.g ‘there will be no difference’)
- alternative hypothesis: show a difference or correlation, included IV and DV where both are operationalised involving how each variable is to be manipulated (IV) and measured (DV)
2
Q
what are the two different types of alternative hypothesis and explain them
A
-directional: a relationship/direction is shown (better/worse), tends to be used when there has already been a range of research carried out relating to the researcher’s investigation
- non-directional: states there is a correlation or direction but doesn’t specify
3
Q
what is an independent variable
A
something the researcher changes or manipulates to observe effects . It is generally the cause of effect, has an effect on the DV
4
Q
what is a dependant variable
A
something that is measured to see if there is any change. Generally described as the outcome/effect. The IV is a cause that has an effect on the DV
- must be measured using quantitative data
5
Q
what does the term operationalisation mean
A
when the researcher clearly defines the variables in terms of how they are being measured. (more specific)
6
Q
what is an extraneous variable
A
a variable that can effect the dependant variable unless it’s controlled. These are factors that can affect the results of the experiment
- e.g time of day- some ppts may be ‘morning ppl’ so more alert compared to others
- temperature- too hot/cold may affect ppt performance on task
- if extraneous variables are not controlled they can become confounding variables
7
Q
what is a cofounding variable
A
a variable that has an effect on the DV. Unlike the extraneous variable, confounding variables do change systematically with the IV, e.g if time is too early, ppts won’t be fully concentrated as they r too sleepy
8
Q
what are demand characteristics
A
- cues from the procedure that suggest what the research is about, therefore ppts change behaviour accordingly
- guess the aim of the study
9
Q
what is the investigator effects
A
- any unwanted influence from the investigator on the research outcome e.g bias to some ppts, or only picking extraverts
- researchers presence/behaviour interferes with research
- e,g age/gender could influence how ppts interact with them
10
Q
what does the term standardisation mean
A
- identical procedure set up in an experiment
- allows research to be replicated, in turn makes it reliable
- e.g standardised instructions, briefing, debriefing, timings and materials
- a way of controlling extraneous variables by keeping them the same across both conditions
11
Q
define the term randomisation
A
- use of chance wherever possible to reduce the researcher’s influence on the design of the investigation
- ppt allocation random, selecting names out of a hat, using random name generator
12
Q
what is a repeated measures design
A
- the same ppts take part in each condition
- they take part in ALL conditions of the IV
13
Q
what is an independent measures design
A
- ppts are randomly allocated into different conditions and only participate in that condition
- may take names out a hat or use a name generator to assign ppts to each condition
14
Q
what is matched pairs design
A
- ppts are paired together based on characteristics/variables relevant to the experiment and then each pair is allocated to one of the conditions. (each partner does a different condition)
- matched pairs are randomly allocated to one condition each
- often MZ twins are used in matched pairs design as they create perfect matched pair
15
Q
what are the strengths of a repeated measures design
A
- differences can’t be due to individual differences as the same ppts take part in both conditions, act as their own control group, increasing internal validity
- less time is spent recruiting ppts (time efficient)
- researchers are saving money as less ppts are needed
- reduces ppt variables
16
Q
what are the limitations of a repeated measures design
A
- ppts may perform worse on 2nd condition due to boredom (order effect), researcher cannot be confident that the IV has affected the DV or that the results were due to other factors
- ppts may do better in 2nd condition due to practise effects
- demand characteristics - guess aim and change behaviour accordingly
to reduce weaknesses: task may need to be changed between conditions to reduce extraneous variables
17
Q
what are the strengths of an independent group designing
A
- only participate in 1 condition so there will be no order effect or practise effects, won’t become bored or overly practised at the task
- tasks won’t need to be changed, allows control between both conditions
-ppts are less likely to guess the aim, eliminating demand characteristics
18
Q
what are the limitations of an independent group design
A
- differences could be due to individual differences, e.g more ppts with a particular characteristic are all randomly allocated to one condition then this presents an unfair playing field
- more ppts need to be recruited, time and cost ineffective
- to reduce weakness: random allocation can help reduce ppts variables
19
Q
what are the strengths of matched pair design
A
- no order effects or practise effects
- tasks won’t need to be changed
- ppts variables are accounted for as ppts are matched
- ppts are less likely to guess the aim of study, eliminating demand characteristics
20
Q
what are the limitations of matched pairs design
A
- matching ppts can be time consuming and expensive, need to identify key variables and measure them
- can be difficult to know which variables ppts should be matched on
21
Q
define a laboratory experiment
A
- researcher controls environmental factors such as noise/temperature (possible extraneous variables) so the effects of the IV upon the DV can be observed and measured
- use standardised procedures to ensure replicability and reliability
22
Q
what are the strengths and weaknesses of a lab experiment
A
strengths:
- highly controlled over confounding variables
- easier to establish cause and effect relationships, high internal validity
-highly replicable, standardised procedure
weaknesses:
- demand characteristics, ppts aware they are taking part in study
- low ecological validity- tasks aren’t reflective of everyday, artificial tasks
23
Q
define a field experiment
A
- carried out in natural environment- real life setting, researcher directly manipulates IV
- have less control over extraneous variables
- e.g confederate pretends to collapse on the train: IV is whether the victim appears to be drunk or disabled
DV: number of people who go to the victim’s aid
24
Q
what are the strengths and weaknesses of a field experiment
A
strengths:
- less chance of demand characteristics, increasing validity
- higher ecological validity, degree of artificiality is reduced
weaknesses:
-difficult to replicate
-no control over extraneous or confounding variables, reliability is reduced
- not ethical, lack of consent and deception
25
define a natural experiment
- researcher doesn't influence or manipulate study as it is naturally occurring, they just observe and compare data
- IV is naturally occurring
- likely to collect qualitative data e.g through interviews, effects of having lived through a natural disaster on stress levels
- often naturally occurring phenomena would be highly unethical for a researcher to impose on participants, hence they look for ppl who have experienced/are experiencing the specific phenomena
26
what are the strengths and weaknesses of a natural experiment
strengths:
- more ethical, allow researcher to investigate topics which would otherwise be unethical to study using traditional lab experiment
- high ecological validity, dealing with real life issues, from first hand knowledge
weaknesses:
-individual differences
- not easy to replicate
- doesn't control extraneous and confounding variables
- suffers from social desirability bias, sample bias, researchers have to reply on the accounts of the ppts themselves, reducing reliability
- naturally occurring event may only happen very rarely, reducing opportunities for research, may also limit the scope for generalising findings to other similar situations
27
define a quasi experiment
- where the IV is naturally occurring as it is pre-existing within individuals but focuses on this difference in individuals to see the effects on the dependant variable. e.g age, gender or disabilities
28
what are the strengths and weaknesses of a quasi experiment
strengths:
- high control, replicable
- individual differences, allows comparison between types of people, e.g in memory tests, gives insight into effect of age on recall
weaknesses:
- ppts aren't randomly allocated as IV is pre-existing. Ppts variables could have caused change in the DV e.g a younger group who naturally have a much better memory than is representative of their population
-demand characteristics
29
what is a target population
entire set of people psychologists are interested in
30
what is a sample
a group of individuals selected from a larger target population
31
what is generalisability
applying findings to a wider population
32
when do we consider a sample as biased
when the sample isn't representative of the whole population e.g same sex
33
define random sampling
when all members of the population have the same equal chances of being the one that is selected
- complete list of all members of the target population, all names are assigned a number, actual sample is selected through use of some lottery method
34
what are the strengths and weaknesses of random sampling
strengths:
- unbiased, randomly selected, no experimenter effects, enhances internal validity
weaknesses:
- time consuming
35
define systematic sampling
participants are selected using a set 'pattern' (sampling frame)
- every nth member of target population is selected
36
what are the strengths and weaknesses of systematic sampling
strengths:
- avoids researcher bias
weaknesses:
- time consuming
37
define stratified sampling
population is divided into subgroups or 'strata' based on certain characteristics. Ppts are obtained from each subgroup in equal proportions
equation= group amount/target pop total x desired sample size
- ppts that make up each stratum are selected using random sampling
38
what are the strengths and weaknesses of stratified sampling
strengths:
- representative method
weaknesses:
-stratification is not perfect, doesn't reflect all different people
39
define opportunity sampling
individuals who are the most available and willing at the time the study is being carried out
40
what are the strengths and weaknesses of opportunity sampling
strengths:
-time and cost effective
weaknesses:
-unrepresentative/biased, drawn from specific area not representative to population
- demand characteristics
- not representative to population, researcher bias as researcher has complete control over selection so may avoid people they don’t like the look of
41
define volunteer sampling
individuals will select themselves to take part in a study
- self selection through advert/ poster on noticeboard
- willing ppts
42
what are the strengths and weaknesses of volunteer sampling
strengths:
-informal consent
- quick and easy
weaknesses:
-bias, some people more likely to volunteer than others, keen/motivated individuals gathered
43
what are the 5 ethical issues
Can- consent
Do- deception
Can’t- confidentiality and privacy
With- withdrawal
Participants- protection from harm
44
explain lack of informed consent and a way to solve it
- informed consent involves whether the ppt agrees to take part, but may reveal aims of the study
- to solve, ask ppts to sign a consent form where appropriate
45
explain deception and a way to deal with it
- deception is deliberately withholding or misleading information so consent is not informed
- to deal, at end of study ppts should be given a debrief where they are told the true aims of the study and what their data will be used for
46
explain the right to withdraw and a way to deal with it
- refers to ability for ppts to stop participating in study for any reason
- to deal, once made aware of study, a debriefing process of the right to withdraw the data that has been gathered
47
explain psychological harm and a way to deal with it
- when psychological research causes ppts distress, discomfort and embarrassment
- to deal, ppts should always have the right to withdraw, and should be reassured their behaviour was normal/typical
-researcher should provide counselling
48
explain confidentiality and privacy and a way to deal with it
- refers to the right to control information about ourselves and have personal data protected
- to deal, data gathered should remain anonymous
49
what are the 6 observational techniques
1. naturalistic observations
2. controlled observations
3. covert observations
4. overt observations
5. participant observation
6. non-participant observation
50
what are observational techniques
a way of seeing or listening to what people do without having to ask them.
51
what are the strengths and weaknesses of observational techniques
strengths:
-capture what people do, give insight on spontaneous behaviour
weakness:
-risk of observer bias
52
what is a naturalistic observation
-observation takes place where target behaviour would normally occur
- no manipulation of an IV
- used when it would be inappropriate/unfeasible to run an experiment
- ppts may be unaware they are being observed as they are simply going about their regular everyday activities
53
what are the strengths and weaknesses of a naturalistic observation
strengths:
-high ecological validity, more generalisable to every day life, behaviour is natural and unforced
weakness:
- raises ethical concerns, ppts cannot give informed consent
- cannot be replicated, difficult to apply scientific rigour, no control over variables, may be overly subjective
54
what is a controlled observation
- observing behaviour in a structured environment e.g lab setting
- implementing replicable procedures
- predetermined behavioural categories
- e.g Ainsworth strange situation (separation anxiety, stranger anxiety, reunion behaviours)
- ppts aware they are being observed
55
what are the strengths and weaknesses of a controlled observation
strengths:
-control over EVs and CVs
- can be replicated, standardised procedure, good reliability, inter observer reliability
- more confident of a cause-effect relationship
weakness:
-low external validity e.g Ainsworth used unfamiliar environment meaning behaviour was not truly representative
-demand characteristics
56
what is a covert observation
-when ppts are unaware that their behaviour is being studied
- unable to see researcher observing them
- likely to occur with naturalistic observations
57
what are the strengths and weaknesses of a covert observation
strengths:
-demand characteristics reduced
-high internal validity, natural behaviour recorded, likely to be real
weaknesses:
-ethical issues, no informed consent
- unable to replicate
58
what is an overt observation
-ppts are aware that their behaviour is being watched and recorded
- likely to occur in controlled lab conditions
- researcher is keen to test the effect of IV on the DV
59
what are the strengths and weaknesses of an overt observation
strengths:
-ethically acceptable, consent is given
weaknesses:
-demand characteristics, reduces validity
- ppts reactivity (type of demand characteristics) e.g trying too hard/not trying enough
- researcher bias- may look for behaviours which support their hypothesis rather than keeping an open mind
60
what is a participant observation
the researcher who is observing joins and becomes part of the group that is being observed
- unlikely that the group is aware they are being observed (overt observation)
61
what are the strengths and weaknesses of a participant observation
strengths:
-more insightful, access to real thoughts and feelings
weaknesses:
-may lose objectivity, may identify too strongly with participants
- may have restricted view of behaviours as a whole
62
what is a non participant observation
- the researcher observes from a distance so is not part of the group being observed
- could be overt or covert
63
what are the strengths and weaknesses of a non participant observation
strengths:
-more objective, less likely to identify with ppts
- reduces bias
weakness:
-loss of insight, lack detail as removed at a distance from the ‘action’
- lack explanatory power
-open to observer bias
64
what are the two observational designs
1. structured
2. unstructured
65
what is a structured observation
- researchers quantify their observation using a pre-determined list of behaviours (behavioural categories) and sampling methods
- gathering quantitative data
- allows them to quantify behaviours
66
what are the strengths and weaknesses of a structured observation
strengths:
-easier, more systematic
-less risk of observer bias
-quantitative data is easier to analyse
weaknesses:
- not much depth of detail, lacks explanatory power
- difficult to achieve high inter observer reliability
67
what is an unstructured observation
- consists of continuous recording where the researcher records everything they see
- flexible and open ended
- gather qualitative data
68
what are the strengths and weaknesses of an unstructured observation
strengths:
-more richness and depth of detail
weaknesses:
-qualitive data is more difficult to analyse
- greater risk of observer bias due to interpretation of data
69
what are behavioural categories
-the target behaviour to be observed should be broken up into a set of observable categories. Requires operationalisation.
-this ensures the target behaviour is clearly defined, the observation is more objective and increases the simplicity
70
what are the two types of sampling methods
1. event sampling
2. time sampling
71
what is event sampling
involves recording the number of times particular behaviour within the behavioural categories occurs whilst observing
- e.g every time litter is dropped rather than put in the bin
72
what is time sampling
observations are made at regular intervals e.g once every 15 secs
73
what is inter observer reliability
when more than one observer agrees
74
what is a questionnaire
- made up of a pre-set list of written questions or items which a participant responds
- self report
75
what are the strengths and weaknesses of questionnaires
strengths:
- can be distributed to lots of people
- straightforward to analyse, quick and easy
- researcher doesn’t need to be present
weaknesses:
- responses may not always be truthful, social desirability bias
76
what is an interview
face-to-face or online interaction between an interviewer and interviewee
77
what are the two types of interviews and explain them
1. structured interview- made up of a pre-determined set of questions that are asked in a fixed order
2. unstructured interview- informal interviews, free-flowing and not set questions
78
what are the strengths and weaknesses of a structured interview
strengths:
-easy to replicate
- minimises researcher effect
weaknesses:
- interviews cannot elaborate, restrictive
79
what are the strengths and weaknesses of an unstructured interview
strengths:
- greater flexibility
weakness:
- increased risk of interviewer bias
- may go off topic on things which are irrelevant to the research where drawing conclusions may be difficult
80
what are the strengths and weaknesses of closed questions
strengths:
- easier to analyse
- patterns can be drawn
weaknesses:
- responses are restricted
81
what are the strengths and weaknesses of open questions
strengths:
- responses aren't restricted
weaknesses:
-difficult to analyse and time consuming
82
what is a positive correlation
as one variable increases the other variable increases
83
what is a negative correlation
as one variable increases the other variable decreases
84
what are the strengths and weaknesses of correlations
strengths:
- can highlight relationships
- can show direction and strength of relationships
- allows predictions to be made
- less time consuming than experiments- can use secondary data
weaknesses:
- doesn't show cause and effect
- intervening variables, leading to false conclusions (third variable problem)
- misused or misinterpreted in the media
85
what is the difference between qualitative and quantitative data
qualitative- expressed in words and in depth
quantitative- numerical data
86
what are the strengths and weaknesses of qualitative data
strengths:
- richness in detail, greater external validity as provides insight into participants worldview
weaknesses:
- difficult to analyse and time consuming
-subjective interpretations of researcher , especially if they have preconceptions about what they are expecting to find
87
what are the strengths and weaknesses of quantitative data
strengths:
- easier to analyse
- objective
weakness:
- narrower in meaning
- lacks construct validity
88
A01
Explain what is meant by reliability
- a measure of ‘consistency’
- if a result can be repeated then its described as reliable
- reliability of methods : replicability
- reliability of findings: consistency
- lab experiments are most reliability method as they take place in neutral space under controlled conditions
89
A01
What are the ways of assessing reliability
- test-retest method
- giving ppts ‘same test’ or ‘questionnaire’ to same person/group of people on different occasions
- if test is reliable then results obtained should be the same or very similar
- there must be sufficient time between test and retest so ppts can’t just recall their answers
- if correlation is 0.8 or above then we can assume good reliability of the questionnaire/tool
- inter observer reliability, researchers have to agree consistency between their recordings
- must agree on behavioural categories, and conduct separately
90
A01
How do you improve reliability
- reliability of observations: procedures should be controlled and standardised, ensuring IV and DV are operationalised, behavioural categories are observable behaviours, distinct with no overlapping
- reliability of questionnaires: using test-retest method, excluding qs which don’t show consistency
- e.g if some questions are ambiguous they may be interpreted differently
- potentially replace some ‘open ended’ qs
- reliability of interviews: using same interviewer for separate interview
- using trained interviewers, ensured leading qs and double barrelled qs are omitted
91
A01
How can we ensure an observation maintains reliability
- conduct observations in teams of at least two, researcher can check for inter-observer reliability
- conduct small scale ‘pilot study’ and administer appropriate ‘behavioural categories’
- behavioural categories: researcher will break down target behaviour into smaller sub categories
- should be clear, not overlapping, not ambiguous or vague or require interpretation
- researcher can record data using a tally chart using agreed behavioural categories
92
A01
Explain what is meant by validity
- whether a psychological test produces a result that is ‘legitimate’ and whether the researcher has actually measured what they intended to measure
- also refers to the extent which findings can be generalised beyond the research setting (external validity)
Examples:
- Milgram’s shock experiment lacks external validity as some ppts guessed the shocks weren’t real (Blass and Schmitz found 1/3 of ppts guessed the shocks weren’t real)
- artificial/ controlled nature of environment
- Asch’s line experiment lacks ecological validity due to artificial environment
93
A01
Explain the steps of a content analysis
1) data needs to be in a transcript/ written data
2) coding and quantitative data, where researchers analyse transcripts and categorise this information into meaningful units. May involve counting number of times a particular word/phrase appears in a text (e.g keeping a tally chart)
3) thematic analysis and qualitative data: through coding researchers can identify certain themes, a theme refers to any idea that is recurrent. Once satisfied with the themes they may collect a new set of data to test validity of the themes and categories
4) assessing reliability: analyse data, tally chart using established themes, correlational analysis of 2 sets of data, +0.8 good inter-rater reliability
- test retest reliability, run content analysis again and compare results
94
A03
What are strengths of a content analysis
1) ‘gets around’ many of the ethical issues normally associated with psychological research e.g materials such as TV, film, newspaper may already exist within the public domain, there are no issues with obtaining permission
2) it is flexible as it can produce both quantitative and qualitative data depending on the research aims
95
A03
What are the weaknesses of content analysis
1) interpretative bias: the researcher may ignore some things but pay extra attention to others
- researcher may misinterpret, researcher may attribute opinions and motivations to the speaker or writer that were not intended originally, therefore lack of objectivity
- researcher doesn’t know true context of data’s origin
96
A01
What are the different sections of a scientific report in order
1) Abstract
2) Introduction
3) Method
4) Results
5) Discussion
6) Referencing
97
A01
Explain what is included in an Abstract
- first section in report/journal article
- a short summary including the major elements of investigation e.g aim, hypothesis, method/procedure, results, conclusion
98
A01
What is included in the introduction of a scientific report
- literature review of general areas of investigation
- details, theories, concepts and studies that are related to current study
- review should follow a logical progression, beginning broadly and gradually more specific
- aims and hypothesis is presented
99
A01
What is included in the method of a scientific report
- sufficient detail so researchers can replicate
- experimental design
- sample
- apparatus
- procedure
- ethics
100
A01
What is included in the results section of a scientific report
- summarise key findings of investigation
- descriptive statistics: tables, graphs, charts, measures of central tendency
- inferential statistics: statistical test, calculated and critical values, level of significance
101
A01
What is included in the discussion section of a scientific report
- summarise findings in written form
- limitations of investigation: method, sample, issues?
- how these limitations might be addressed in a future study
- wider implications of research: real word applications and conclusions
102
A01
What is meant by referencing in a scientific report
- full details of any source material that the researcher drew upon or cited in the report
- journal and title of book are in italics
- surname, initial of first name, year, title and age
- if a book then place of publication is included and name of publisher
103
A01
What is the importance of referencing
- enables reader to track down the sources used
- to give credit to other researchers/acknowledges their ideas
- can avoid plagiarism
104
A01
What is meant by empirical methods
- refers to how information is gathered
- methods that allow for direct testing are empirical (e.g direct observation or experimental research/ lab based)
- produce factual information/data
- some methods in psych are more scientific than others meaning there is ‘internal disagreement’ meaning it’s scientific status is questioned
105
A01
What is meant by a paradigm
- shared set of ideas/assumptions with particular discipline that distinguishes science from non science
- psychology viewed as a pre-science as it has too much disparity between various approaches e.g cognitive versus biological
106
A01
What does Kuhn argue about psychology being a science
- most scientific disciplines have one predominant paradigm that the vast majority of scientists subscribe to
- psychology lacks a universally accepted paradigm and is best seen as a ‘pre-science’ due to the multiple paradigms
- therefore psychology not seen as a science as there are multiple paradigms
107
A01
What is meant by falsifiability
- where hypothesis can be tested and proved false
108
A01
What is the importance of falsifiability
- it makes a theory scientific
- this is why we have a null hypothesis
109
A01
What approaches are unfalsifiable
- psychodynamic and humanistic approaches are based on abstract concepts which are difficult to empirically test, therefore not falsifiable (non-scientific)
110
A01
What is the importance of replicability when referring to scientific
- if a theory is to be trusted the findings must be shown to be repeatable across a number of different contexts
- controlled observations (empirical methods) allow for replication due to control of extraneous variables and use of standardised procedures
- methods which generate qualitative data do not lend themselves to replicability e.g case study based on one individual, not replicable as data only applies to that individual
- unstructured interview follows no set plan means ppt response will be different every time
111
How can extraneous variables be controlled, give examples
Time of day- run experiment during midday which should be a neutral time for everyone
Temperature- ensure space has an ambient temperature
Mood- treat ppts in a pleasant but neutral way
112
How could investigator effects be controlled
- using a double-blind procedure where the ppts and researcher don’t know which condition each ppts has been assigned to
- researcher is not able to exercise any forms of bias during the procedure
113
What is a pilot study
- small scale trials that are run to test aspects of the proposed investigation
- ‘dress rehearsal’ of the procedure
- identifies any issues which could cause problems further down the line
E.g flaws in design, ethical issues, feasibility (possible and practicable?)
- pilot studies can identify if it’s worth the time, money and effort to run the investigation
114
What is a single-blind procedure
- research method in which the researchers do not tell the ppts if they are being given a test treatment or control treatment
- to ensure that ppts do not bias the results by acting in ways they ‘think’ they should act, avoids demand characteristics
115
What is peer review
- assessment of scientific work by experts in the same field
- done to make sure that all research intended to eventually be published is of high quality
- validates the relevance and quality of research
- check research h is original and has not been plagiarised
116
What is an example of secondary data
- meta analysis
117
What is a case study
- detailed and in depth investigation of small group or an individual
- qualitative data may be collected using interviews, observations, open ended questions and a questionnaire
118
What are strengths of a case study
- provide rich in-depth data which is high in explanatory power
- gain insight into unique experiences
- holistic, idiographic approach where whole individual is considered
- high in ecological validity
119
What are limitations of a case study
- only represent one individual/ unique experience
- can’t generalise to wider population
- researcher may begin to feel too close to individual, result in them losing objectivity and possibly using bias in their results
120
Explain what internal and external reliability means
- internal reliability: extent to which a measure is consistent with itself
- external reliability: extent to which a measure is consistent over time
121
Explain what internal, external and temporal validity are
Internal validity: measure the extent to which the results are due to manipulation of the IV rather than the influence of uncontrolled confounding variables (whether test measured what intended to measure)
External validity: measures the extent to which the results can be generalised beyond the research setting
Temporal validity: measures extent to which research findings are still relevant in current age e.g Bowlby concept of mother being primary caregiver is outdated in the modern world where many different permutations of a family are around
122
What is face and predictive validity
Face validity: assess whether a test or study measured what it set out to measure
Predictive validity: measures how well a test or a study can predict future behaviour
123
How can validity be improved
Lab experiments: ensuring controlled conditions and standardised procedures
- use single or double blind procedures
Observations: using covert methods in naturalistic observation, behaviour is likely to be unforced and natural, ensure behavioural categories are clear, unambiguous, and observable with no overlapping
Questionnaires: using a lie scale to show up inconsistencies in responses
124
What are strengths and weaknesses of the mean as a central tendency
Strengths: most sensitive measure of central tendency, takes into account all scores
- more representative score, most reliable measure
Limitations: sensitive to extreme scores (outliers) so can only be used when scores are reasonably close
125
What are the strengths and weaknesses of the median
Strengths: not affected by extreme scores, means it can be used on data sets with anomalies
Limitations: arranging data in ascending or descending order is time-consuming, more problematic in large data sets
126
What are the strengths and weaknesses of the mode
Strengths: mode is not affected by extreme values, analysis of qualitative data
Limitations: data may include two modes which blurs the meaning of the data, means mode is least reliable
127
What is standard deviation
- provides insight into how clustered or spread out the scores are from the mean
- a low standard deviation indicates scores are clustered tightly around mean, indicating reliability
- high standard deviation indicates scores are more spread out, indicating lower reliability
128
What are the strengths and weaknesses of standard deviation as a measure of tendency
Strength: provides info as how scores are distributes
- strength as it can indicate to what extent the data set is reliable and consistent
- more sensitive than the range as it uses all scores in data set, more valid representation
Limitations: can be skewed by extreme outliers, may inflate or depress the standard deviation, giving misleading representation
129
What’s primary and secondary data
Primary: first hand collected data, collected from source, specifically to the research aim
Secondary data: consists of any research findings/results that are pre-existing
- have not been collected at source, is not original data
- obtained by other researchers
130
What is nominal, ordinal and interval data
Nominal: used when data is put into categories, categoric data
Ordinal data: scores can be arranged in order e.g ranking (scores in a test)
Interval data: specific units e.g cm, seconds
- temperature is interval data
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What is a positive skew
- most values are found towards the left side of the graph, giving a long tail on the right
- mode and median are higher than the mean
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What is a negative skew
- most values are found towards the right side of the graph, giving a long tail on the left
- mode and median are higher than the mean
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What is a type 1 error
- when the null hypothesis is wrongly rejected, should’ve been accepted
- researcher claims that the results are significant when they are in fact not
- known as false positive
- likely to happen when a more lenient level of significance is used
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What is a type two error
- when the null hypothesis is wrongly accepted, should have been rejected
- researcher claims the results are not significant when in fact they are
- false negative
- usually happens when a more stringent level of significance is used
- more likely to take place when testing things that can cause potential harm e.g drug trials
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What is the criteria of when to use the sign test in psychology
- if the researcher investigates a difference
- repeated measures design, each ppt experiences both conditions
- nominal data, data is in categorises
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How would the Sign Test be carried out
- calculate the difference between values in tables either positive or negative result
- scores of 0 difference have neither a positive or negative sign
- count the number of + and - signs
- whichever number is lowest, becomes the observed value (S)
- identify critical value using stats table, select p=0.05 level
- use N (number of ppts) to find critical value, if difference is 0 this doesn’t count as a ppt
- if S value is more than critical value, the researcher would accept the null hypothesis
- if value is equal to or less than critical value, researcher would reject null hypothesis and accept the alternative hypothesis
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What is the saying for the inferential stats table
- carrots should come mashed with swede under roast potatoes
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What is meant by empirical method
- involves using scientific methods, collect quantitative data in ways which are controlled by researcher and are replicable
- tests hypotheses using methods gained from, direct observations, e.g lab experiments
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What is meant by response bias
- answering questions to align with what you think the researcher is looking for
Psychology
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