Research Methods Flashcards

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)
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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

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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

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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

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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)

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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

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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

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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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

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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
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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

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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
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
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
34
what are the strengths and weaknesses of random sampling
strengths: - unbiased, randomly selected, no experimenter effects weaknesses: - time consuming
35
define systematic sampling
participants are selected using a set 'pattern' (sampling frame)
36
what are the strengths and weaknesses of a lab experiment
strengths: -highly controlled, extraneous and confounding variables - highly replicable weaknesses: - demand characteristics -lacks ecological validity, doesn't reflect every day tasks
37
define a field experiment
researcher directly manipulates the IV in a natural environment
38
what are the strengths and weaknesses of a field experiment
strengths: -less chance of demand characteristics -higher external validity weaknesses: - difficult to replicate - no control over extraneous or confounding variables - ethical issues, lack of consent and deception
39
define a natural experiment
- the researcher doesn't directly manipulate the IV as it is naturally occurring.
40
what are the strengths and weaknesses of a natural experiment
strengths: -more ethical, nothing is being changed or manipulated - high external validity, dealing with real life issues weaknesses: - individual differences, no random allocation -not easy to replicate - no control over extraneous and confounding variables
41
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 DV. e.g age, gender or disability
42
what are the strengths and weaknesses of a quasi experiment
strengths: -high control over variables so replication is possible -individual differences, allows comparisons to be made weaknesses: - demand characteristics - ppts not randomly allocated
43
what is a target population
the entire set of people psychologists are interested in
44
what is a sample
a group of individuals selected from a larger target population
45
what is generalisability
applying findings to a wider population
46
when do we consider a sample as biased
when the sample isn't representative of the whole population e.g same sex
47
define random sampling
all members of population have the same equal chance of being the one that is selected
48
what are the strengths and weaknesses of random sampling
strengths: -unbiased, randomly selected weaknesses: - time consuming
49
define systematic sampling
ppts are selected using a set 'pattern' (sampling frame)
50
what are the strengths and weaknesses of systematic sampling
strengths: - avoids researcher bias weaknesses: - time consuming
51
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
52
what are the strengths and weaknesses of stratified sampling
strengths: - representative method weaknesses: -stratification is not perfect, doesn't reflect all different people
53
define opportunity sampling
individuals who are the most available and willing at the time the study is being carried out
54
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
55
define volunteer sampling
individuals will select themselves to take part in a study
56
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
57
what are the 5 ethical issues
1. lack of informed consent 2. deception 3. right to withdraw 4. psychological harm 5. confidentiality and privacy
58
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
59
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
60
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
61
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
62
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
63
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
64
what are observational techniques
a way of seeing or listening to what people do without having to ask them.
65
what are the strengths and weaknesses of observational techniques
strengths: -capture what people do, give insight on spontaneous behaviour weakness: -risk of observer bias
66
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
67
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
68
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
69
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
70
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
71
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
72
what is an overt observation
-ppts are aware that their behaviour is being watched and recorded - likely to occur in controlled lab conditions
73
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
74
what is a participant observation
the researcher who is observing joins and becomes part of the group that is being observed
75
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
76
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
77
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 - lack explanatory power -open to observer bias
78
what are the two observational designs
1. structured 2. unstructured
79
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
80
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
81
what is an unstructured observation
- consists of continuous recording where the researcher records everything they see - flexible and open ended - gather qualitative data
82
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
83
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
84
what are the two types of sampling methods
1. event sampling 2. time sampling
85
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
86
what is time sampling
observations are made at regular intervals e.g once every 15 secs
87
what is inter observer reliability
when more than one observer agrees
88
what is a questionnaire
- made up of a pre-set list of written questions or items which a participant responds - self report
89
what are the strengths and weaknesses of questionnaires
strengths: - can be distributed to lots of people - straightforward to analyse, quick and easy weaknesses: - responses may not always be truthful, social desirability bias
90
what is an interview
face-to-face or online interaction between an interviewer and interviewee
91
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
92
what are the strengths and weaknesses of a structured interview
strengths: -easy to replicate - minimises researcher effect weaknesses: - interviews cannot elaborate, restrictive
93
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
94
what are the strengths and weaknesses of closed questions
strengths: - easier to analyse - patterns can be drawn weaknesses: - responses are restricted
95
what are the strengths and weaknesses of open questions
strengths: - responses aren't restricted weaknesses: -difficult to analyse and time consuming
96
what is a positive correlation
as one variable increases the other variable increases
97
what is a negative correlation
as one variable increases the other variable decreases
98
what are the strengths and weaknesses of correlations
strengths: - can highlight relationships - can show direction and strength of relationships - allows predictions to be made weaknesses: - doesn't show cause and effect - intervening variables, leading to false conclusions
99
what is the difference between qualitative and quantitative data
qualitative- expressed in words and in depth quantitative- numerical data
100
what are the strengths and weaknesses of qualitative data
strengths: - richness in detail weaknesses: - difficult to analyse and time consuming -subjective
101
what are the strengths and weaknesses of quantitative data
strengths: - easier to analyse - objective weakness: - narrower in meaning - lacks construct validity
102
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
103
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
104
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 are omitted
105
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
106
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
107
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
108
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
109
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
110
A01 What are the different sections of a scientific report in order
1) Abstract 2) Introduction 3) Method 4) Results 5) Discussion 6) Referencing
111
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
112
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
113
A01 What is included in the method of a scientific report
- sufficient detail so researchers can replicate - experimental design - sample - apparatus - procedure - ethics
114
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
115
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
116
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
117
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
118
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
119
A01 What is meant by a paradigm
- shared set of ideas/assumptions
120
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
121
A01 What is meant by falsifiability
- where hypothesis can be tested and proved false
122
A01 What is the importance of falsifiability
- it makes a theory scientific - this is why we have a null hypothesis
123
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)
124
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
125
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
126
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
127
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
128
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
129
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
130
What is an example of secondary data
- meta analysis
131
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
132
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
133
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
134
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
135
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
136
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
137
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
138
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
139
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
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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
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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
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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
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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
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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