Research Methods Flashcards

1
Q

What does replicability mean

A

repeating research under identical conditions to check validity
Same or similar results must be obtained to be reliable

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2
Q

What does objectivity mean

A

Observations made through sensory experience, independent of beliefs, opinions and biased viewpoint of researchers
-to lesson possibility of unconscious bias and reduce subjectivity
-peer reviews can act asana gate keeper to stop this and replication can help check validity

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3
Q

What is falsifiability

A

-A scientific theory has to be empirically testable to see if its false
- one example of falsification is enough to render a theory untrue

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4
Q

How can falsifiability be determined

A

Replication

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5
Q

7 main scientific factors of a method to be scientific

A

-replicable
-objective
-controlled variable
-reliable
-cause and effect can be established
-quantitative data
-valid
-standardised
-falsifiable

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6
Q

What does reliability mean

A

The extent to which a test or measurement produces consistent results

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7
Q

What does validity mean

A

The extent to which results accurately measure what they are supposed to Meade

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8
Q

What is qualitative data

A

Expressed in words rather than numbers and may take the form of written description of thoughts feeling and opinions of participants

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9
Q

Advantages of qualitative data

A

-More richness of detail in a much broader scope
-Participant has more license to develop their thought feeling and opinions on a given subject so greater external validity
-researcher has more meaningful; insight into participants work view

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10
Q

Disadvantages to qualitative data

A

-difficult to analyse
-hard to be summarised statistically
-patterns and comparisons within data hard to identify
-concussion often rely on subjective interpretations of the researcher which may be subject to bias

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11
Q

What is quantitative data

A

Data represented numerical data and collection technique often gather numerical data in the form of individual scores

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12
Q

Quantitative data advantages

A

-easier to analyse
-patterns and comparisons within data easily drawn
-more objective and less open to bias
-analysed statistically
-easily converted into graphs and charts etc

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13
Q

Quantitative data disadvantage

A

-narrower scope with less meaning
-participant less chance to develop thoughts feelings and opinions so less external validity
-researcher doesn’t gain meaningful insight and may fail to represent a real life

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14
Q

Which is better:qualitative or quantitative data

A

-depends on purpose and aims of research
-researchers collecting quantitative data may also interview participants
-qualitative can sometimes be converted to numerical data

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15
Q

What is primary data

A

Original data has been collected specifically for the purpose of the investigation by the researcher ans arrives first hand from participants themselves

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16
Q

What can primary data also be referred to as

A

Field research

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17
Q

How is primary data gathered

A

Conducting and experiment, questionnaire, interview or observations

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18
Q

Primary data advantages

A

-authentic data obtained from participants for the purpose of the particular investigation so specifically targets info required

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19
Q

primary data disadvantages

A

-requires time and effort
-can be expensive

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20
Q

What is secondary data

A

Data collected by singing other than the person who is conducting that research and already exists before starting research

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21
Q

What is secondary data often. Referred to as

A

Desk research

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22
Q

Where might secondary data be located

A

Journal articles, books, website, statistical information held by the government, population records

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23
Q

What is meta analysis

A

Research method that uses secondary data and refers to process in which the data from a large number of studies involving the same research questions and methods are combines

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24
Q

Positive of meta analysis

A

Allows to view data with much more confidence and results can be generalised across much larger populations

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25
Negative of meta analysis
Maybe prone to bias as researcher may not select all relevant studies choosing to leave out those with non significant results
26
Secondary advantages
-may be inexpensive, easily accessed and minimal effort
27
Secondary disadvantages
-may be substantial variation in quality and accuracy of secondary data -data may be out dated or incomplete -data may not quite match the researchers needs/objective -dont know how scientific/Ethical
28
What are the 6 research methods
-experiments -observation -self report -correlation -content analysis -case studies
29
What is an aim
General statement of what the researcher intends to investigate/ the purpose of study as we have to start with an initial idea then narrow the focus of our research to produce an aim
30
What do you start and exam answer with if asked to write an aim
To investigate
31
What is a hypothesis
Clear precise testable state,ent that states the relationship between the variable to be investigated and is written in the present or future tense
32
What are the 4 different types of hypotheses
-Alternative/experimental -directional -non directional -null
33
What is a directional (one tailed) hypothesis
Clear sort of difference anticipated between two conditions or two groups of people and includ words eg more less higher lower faster
34
What is a non directional (two tailed ) hypothesis
Simply states there will be a difference between conditions or groups of people but the nature of the diffference is not specified
35
What is a null hypothesis
States there will be no significant difference between the two groups
36
What is and alternative hypothesis
When experiment is done results analysed to decide if the alternative hypothesis should be accepted or the null one
37
Which type of hypothesis should be used ?
Directional tend to be used when the findings of previous research studies suggest a particular outcome Non directional when there’s no previous research of findings of earlier studies are contradictory
38
Experiments Why are variables used
Determine if changes in on thing results in changes to another
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Experiments What is an independent variable
Aspect of the experimental situation that is manipulated by the researchers or changes naturally
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Experiments What is a dependent variable
Variable that measured by the researcher and recorded
41
What three levels of measurement can quantitative data be put into
Nominal Ordinal Interval
42
What is nominal data
Data represented in the form of categories eg males and females, school dinner or packed lunch
43
What id ordinal data
Data can be put in order eg scale of 1-10 and doesn’t have equal intervals between each unit
44
Limitations of ordinal data
Based on subjective option not objective so lacks precision As the data is ‘unsafe, raw scores are converted into ranks when doing statistical testing
45
What is interval data
Based on a numerical scale that includes units of equal, precisely defined size eg time temp and weight Most precise and sophisticated form of data
46
For nominal level of measurement which is the measure of central tendency
Mode
47
For ordinal level of measurement which is the measure of central tendency
Median
48
For interval level of measurement which is the measure of central tendency
Mean
49
For nominal level of measurement which is the measure of dispersion
Range and standard deviation cannot be calculated so n/a
50
For ordinal level of measurement which is the measure of dispersion
Range
51
For interval level of measurement which is the measure of dispersion
Standard deviation
52
Why isn’t it appropriate to use the mean or standard deviation for ordinal data
Intervals between units of measurement are not equal of size
53
Experimental method What are conditions
Different testing groups which reflect what the IV is
54
Experimental method What is operationalisation of variables
Clearly defining variables into measurable factors
55
Experimental method Why is operationalisation of factors necessary
Many things psychologists are interested in are difficult to define therefore the psychologist needs to ensure the variables being investigated are clear and measurable
56
Experimental method When are variables operationalised
When writing the hypothesis
57
Experimental method why do we need to control variables
Be sure that the IV has caused the change in the DV so any other variable that might potentially interfere should be controlled or removed
58
Experimental method What are additional unwanted variables then need to be controlled called
Extraneous variables
59
Experimental method How do you limit the affect of extrenuous variables
Need to be identified before the study and minimised
60
Experimental method what are confounding variables
Extrenuous variables that have systematically changed the IV Affects relationship between IV and DV
61
Experimental method What are demand characteristics
Cues picked up by the participants from the researcher or research situation about what’s going on and possible reveal the purpose of the investigation which may lead to a change in behaviour
62
Experimental method Types of demand characteristics
Please you effect Screw you effect
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Experimental method Impact of demand characteristics
Behaviour no longer natural
64
Experimental method What are investigator effects
Effect of investigator behaviour (conscious or unconscious) that impact on research outcome
65
Experimental method Example of investigator effect
Design of study , selection of participants, interactions with participants eg smiling or words said
66
Experimental method What’s randomisation
Use of chance wherever possible to control for the effects of biased when deigning materials and allocating participants
67
Experimental method What’s standardisation
All participants should be subject to the same environment information and experience
68
What is experimental design/ participants design
Way in which participants are used in experiments and how participants are assigned certain conditions which can be done in three ways
69
What are the three experimental/participant design
Repeated measures Independent groups Marched paired
70
Experimental method What is repeated measures
Participants experience both conditions and results are compared
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Experimental method Strength of repeated measures
Participant variable not an issue as same participants in both conditions Less participants so more economical
72
Experimental method Weakenesses of repeated measures
Order effects are a problem but can be counterbalanced Demand characteristics may be a problem as participants guess the aim More than one test needed
73
Experimental method What is independent groups
Participants take part in one condition then results compared
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Experimental method Weaknesses of independent groups
Participant variables Less economical
75
Experimental method Strengths of independent groups
No order effects as participant only take parent once Participants less likely to guess aim Only ne test needed
76
Experimental method What is matched pairs
Two separate groups of participants and are paired on key characteristics eg matched on IQ so it tries to control participant variables
77
Experimental method Weakness of matched pairs
Still participant variables as can’t match exactly Matching is time consuming and expensive Less economical
78
Experimental method Strength is matched pair
No order effects as participant only in one condition Less demand characteristics as didnt guess aim of the study as only in one conditions
79
Experimental method What’s counterbalancing
Attempt to minimise the effects of order effects in a related measures design and attempts to balance out order effects but cant get rid of them
80
Experimental method How is counter balancing used
Half the participant do condition A then B and Half the participants do B. Then A
81
Experimental method What’s random allocation
Used in independent groups to avoid bias from the researcher and participants who may choose to be in particular conditions to attempt to evenly distributed characteristics across the conditions of the experiment random techniques
82
Experimental method How is random allocation used
Participants randomly allocated to conditions using random techniques to address the problem of participants variables in the two conditions
83
Experimental method What are the four types of experiments
Laboratory experiments, field experiments, natural experiments and Quasi experiments
84
Experimental method Types of experiments What are laboratory experiments
Highly controlled environments eg a classroom or lab Experimenter manipulates IV
85
Experimental method Types of experiments Strengths of lab experiments
-high control over extraneous variables -more confidence that IV has affected the DV -replication is possible because of control
86
Experimental method Types of experiments Weaknesses of lab experiments
-lacks generalisability to other setting so low external validity -lacks generalisability to real life so low ecological validity -participants more likely to act unnaturally so demand characteristics -tasks complete by participants don’t represent real life
87
Experimental method Types of experiments What is field experiments
IV manipulated by experimenter but setting more natural everyday one
88
Experimental method Types of experiments Strengths of field experiments
-higher mundane realism than lab experiments because environment is more natural -may produce behaviour that is more valid and authentic -participants may be unaware they’re being studied so high external validity
89
Experimental method Types of experiments Weaknesses of field experiments
-less control over extraneous variables -cause and effect between the IV and DV more difficult to establish -precise replication not possible -ethical issues informed consent from participants -possible invasion of privacy
90
Experimental method Types of experiments What are natural experiments
-researcher take advantage of pre existing independent variable -variable would’ve changed even if experimenter not there -setting not always natural eg could be a lab
91
Experimental method Types of experiments Strengths of natural experiments
-provides opportunities for research that may not otherwise be undertaken for practical or ethical reasons -often high external validity as they study real life issues and problems as they happen
92
Experimental method Types of experiments Weaknesses of natural experiments
-naturally occurring event may only happen reducing the opportunities for research -generalising findings to other similar situations will be limited -participants may not have been randomly allocated to groups so less sure IV affected the DV
93
Experimental method Types of experiments What are quasi experiments
IV based on existing difference between people eg gender age or having medical condition and it’s not manipulated it already exists
94
Experimental method Types of experiments Strengths of quasi experiments
Often carried out under controlled conditions therefore share the same strengths of a lab experiment
95
Experimental method Types of experiments Weaknesses of quasi experiments
Cannot randomly allocate participants they’re already in this conditions -may be confounding variable
96
Experimental method What is a single blind procedure
Participants sometimes not be told the aim of the study and may also not be told what condition of th experiment they’re in
97
Experimental method What’s the point of single blind procedure
Attempt to control the effects of demand characteristics
98
Experimental method What’s a double blind procedure
Neither participants nor the researcher is aware of there aims of the investigation and often a third party conducts the investigation
99
Experimental method What is the control condition is the drug trial example
Group that receive the placebo
100
Experimental method What’s the experimental conditions on the drug trial example
The groups that receives the real drug
101
Experimental method What’s are pilot studies
Small scale retrial run of actual investigation may involve handful of participants to check it runs smoothly
102
Experimental method Why are pilot studies used
Check the experiment runs smoothly and researcher can identify potential issues and modify the design or procedure to save time and money in the long run
103
Sampling What is the population
Large group of individuals that a particular researcher may be interested in
104
Sampling What is the sample
Selection of participants taken from the target population being studied and intended to be representative of that population
105
Sampling Why is it tricky to get a representation sample
Target population will be so diverse Most samples contain some bias
106
Sampling Why is a representative sample good
Allows generalisation of findings to be possible
107
Sampling What are the five types
Random Systematic Stratified Opportunity Volunteer
108
Sampling What is random sampling
When all members of target population have an equal chance of being selected
109
Sampling How is random sampling done
Complete list of all members of the target population obtained And then assigned a random number Then put in a random number generator or picked out of a hat
110
Sampling Strengths 0f random sampling
Free from researcher bias (no influence over who’s Chloe not just choosing those who support the hypothesis )
111
Sampling Weaknesses of random sampling
Difficult and time consuming Sample may still be unrepresentative eg all females Selected participants may refuse to take part
112
Sampling What happens in systematic sampling
Sampling frame produced Every nth person is selected Interval determined randomly to avoid bias
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Sampling Strengths of systematic sampling
Free from researcher bias Usually fairly representative
114
Sampling Weaknesses of systematic sampling
Complete list of target population may be hard to obtain Selected participants may refuse to take part Still possible to get unrepresentative sample
115
Sampling What is stratified sampling
Composition f the sample reflects the proportions of the strata within the target population
116
Sampling How is stratified sampling done
First identify different strata that make up the population Find proportions of different strata Participants that make up each strata selected through random sampling
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Sampling Strengths of stratified sampling
Free from researcher bias Produced representative sample -designed to accurately represent composition of population Generalisation of findings possible
118
Sampling Weaknesses of stratified sampling
Difficult and time consuming Selected participants may refuse to take part Identified strata cannot reflect all ways people are different
119
Sampling How is opportunity sampling done
Anyone who is available and willing at the time is asked by the researcher
120
Sampling Strengths of opportunity sampling
Convenient-saves researcher time and effort Less costly than other techniques
121
Sampling Weaknesses of opportunity sampling
Suffers from bias Unrepresentative of the target population as it’s drawn from a very specific area and finding can’t be generalised to population Researcher bias as may avoid certain participants
122
Sampling What’s volunteer sampling
Participants select themselves to be part of sample (self-selecting)
123
Sampling Strengths of volunteer sampling
Easy- requires ,minimal input from the researcher and less time consuming than other techniques
124
Sampling Weaknesses of volunteer sampling
Volunteer bias May attract a certain profile of persons eg helpful and keen Might affect generalisability
125
Case study What are cast studies
In-depth detailed investigations of one individual, small group, institution or event usually in the real world
126
Case studies What are case studies in nature (issues and debate)
Idiographic and individualistic
127
Case studies What do they usually involve
Biographical details, behavioural information, experiences of interest, often analysis of unusual individuals or events but may also concentrate on typical cases
128
Case studies What are they exp;anations of
Explanations of behaviour outlines in a subjective way
129
Case studies What type of date is usually produced
Qualitative
130
Case studies How can data be gathered for case studies
Interviews, observations, questionnaires,experimental testing to asses what a person can or can’t do
131
Case studies Often what type of studies
Longitudinal
132
Case studies All advantages
Rich detail – case studies provide great depth and understanding about individuals and acknowledge human diversity Give us insight on unusual forms of behavior and ‘normal’ functioning Case studies are about real people. Information relates to a real person – not just an average gathered from many Case studies can be longitudinal and so changes in experience can be observed over time, rather than just a ‘snapshot’ of experience provided by other methods Case studies usually involve several methods (observation, interviews, etc.), enabling checks for consistency/reliability/validity whereas other methods just use a single method of data collection Allows psychologists to study unique behaviours or experiences that couldn’t have been studied any other way Allows sensitive areas to be explored e.g. effects of sexual abuse Useful for theory contradiction – just one case study can contradict a theory
133
Case studies advantages Detail as an advantage
Rich detail as case studies provide great depth and understanding about individuals and acknowledge human diversity
134
Case studies advantages What do they give insight
Unusual forms of behaviour and normal functioning
135
Case studies advantages Ecological validity
About real people so information relates to a real person and not just average from many Longitudinal and so changes in experience can be observed over time rather than just a snap shot of experience frovided by other methods
136
Case studies advantages Methods to collect data
Often involves several methods a eg observation and interviews enabling checks for consistency/reliability/validity compared to over methods which only use a single method of collection
137
Case studies advantages What else are they useful for
Theory contradiction as just on case study can contradict a theory
138
Case studies disadvantages
Not representative – no two cases are alike, results cannot be generalised to others Because it is very difficult to replicate a case study, they lack reliability As case studies are unique situations, it’s very difficult to generalize to other situations Researcher bias – researchers conducting case studies may be biased in their interpretations Reliance on memory – the information gathered is often based on retrospective data (often depend upon participants having full and accurate memories) so may not be accurate
139
Case studies disadvantages Why isn’t it representative
No two cases are alike so results can’t be generalised to other
140
Case studies disadvantages Why do they lack reliability
Because its very difficult to replicate a case study as they’re all unique
141
Case studies disadvantages Researcher bias
Researchers conducting case studies may be biased in their interpretations
142
Case studies disadvantages Reliance on memory
Information gathered is often based on retrospective date often dependent upon participants having full and accurate memories so may not be representative
143
Measures of central tendency and dispersion What are measures of central tendency
Averages which give us information about the most typical values in a set of data Mean mode and median
144
Measures of central tendency and dispersion What are measures of dispersion
Tell us about the spread of scores and how they differ and vary form one another Range and standard deviation
145
Measures of central tendency and dispersion How do you find the mean
Add up all values and divide by number of values
146
Measures of central tendency and dispersion Strengths of the mean
Most sensitive of the measures of central tendency as it includes all the scores in the data set More representative of the data as a whole
147
Measures of central tendency and dispersion Weaknesses of mean
Easily distorted by extreme values so the mean may to be representative in this case Can’t be used with ordinal Mean may not be one of the actual scores in the data set
148
Measures of central tendency and dispersion What the median
Middle value in a data set when scores arranged from lowest to highest
149
Measures of central tendency and dispersion Strengths of median
Extreme scores don’t affect the middle value Easy to calculate Can be used with ordinal data
150
Measures of central tendency and dispersion Weaknesses of median
Less sensitive than the mean as not all scores are included in the final calculation
151
Measures of central tendency and dispersion What’s the mode
Most frequently occurring value in a data set Can be two modes or no modes
152
Measures of central tendency and dispersion Strengths of mode
Easy to calculate Less prone to distortion by extreme values May be only method you can use eg ordinal
153
Measures of central tendency and dispersion Weaknesses of mode
Very crude measure Doesn’t use all scores May not e a mode May not be representative of data as a whole
154
Measures of central tendency and dispersion What is the range
Simple calculation of spread of values Take lowest value from the highest value
155
Measures of central tendency and dispersion Strength of the range
Easy to calculate
156
Measures of central tendency and dispersion Weaknesses of range
Only takes into accounts two most extreme values therefore unrepresentative of data set as a whole Doesn’t show whether data is clustered or spreads evenly around the mean
157
Measures of central tendency and dispersion What is standard deviation
Single values that tells us how far scored deviate from the mean The larger, the greater spread of score
158
Measures of central tendency and dispersion When talking about a particular condition within an experiment what does a large standard deviation mean
Not all participants were affected in the same way by the IV
159
Measures of central tendency and dispersion What does a low standard deviation mean within an experiment
Implies participants responded in a fairly similar way
160
Measures of central tendency and dispersion Strength of standard deviation
Much more précis measure of dispersion than the range as it includes all values
161
Measures of central tendency and dispersion Weakness of standard deviation
More complicated to calculate Can be distorted by extreme values
162
Measures of central tendency and dispersion What measures can be used in nominal level of measurement
Mode No dispersion
163
Measures of central tendency and dispersion What measures can be used in ordinal level of measurement
Median and mode Range
164
Measures of central tendency and dispersion What measures can be used in interval level of measurement
Mean median and mode Range and standard deviation
165
Measures of central tendency and dispersion Why is it not appropriate to use the mean or standard deviation for ordinal data
Intervals between the units of measurement are not of equal size
166
Measures of central tendency and dispersion How do you answer the 4 mark question for mean and standard deviation
General statement about mean (include IV and DV) (1) Evidence about mean and conditions specific (1) General statement about standard deviation (include IV and DV) (1) Evidence about standard deviation and condition specific (1)
167
Correlation What is correlation not
Repeated measure’s independent groups or matched pairs
168
Correlation What does each participant do
Provide data for two measures
169
Correlationwhat are covariables
Correlations haver two variables and both are measured
170
Correlation What do they not show
Cause and effect they’re looking for a relationship between the two variables
171
Correlation What is a correlation
Relationship between two variables measured on a scale and where both measures come from one individual
172
Correlation What is a positive correlation
Where as one variable increases so does the other
173
Correlation Positive correlation coefficient
+1 would be the perfect positive correlation so the closer to this number you get shows a positive correlation
174
Correlation What is a considered a strong positive correlation
0.7 ands above
175
Correlation What is a negative correlation
Where’s as pone variable increases the other decreases
176
Correlation Negative correlation coefficient
-1 would be perfect negative correlation so the closer you get to this number you get shows a negative correlation
177
Correlation What’s condsidered a strong negative correlation
-0.7
178
Correlation What is no correlation
Where there’s no relationship between the two variable
179
Correlation What is correlational data presented on
Scatter graph
180
Correlation How are correlations hypotheses different to experiments
No IV and DV Hypothesis still has to clearly state the expected relationship between the covariables and must be clearly operationalised
181
Correlation How do you write a non directional correlation all hypothesis
There will be a correlation between … and … (operationalised)
182
Correlation How do you write a directional correlational hypothesis
There will be a positive/negative correlation between … and … (operationalised )
183
Correlation How do you write a null correlational hypothesis
There will be no correlation between … and … (operationalised
184
Correlation What are the strengths of a correlational design
Little manipulation of variables Show unexpected relationships Study something which can’t be changed deliberately Show statistical relationships
185
Correlation Why is there being little manipulation of variables a strength of this design
Measures often taken in existing situations with few controls needed and design is quite straight forward compared with other methods
186
Correlation Why is being able to show unexpected relationships a strength of this’d design
Can prompt future research in new areas
187
Correlation Why is being able to study something which can’t be deliberately changed a strength
Allow to study something that an experimenter can’t change as it would be unethical or something which happens naturally which can’t be done by other designs
188
Correlation Why is showing a statistical relationships between variables a strength
It’s objective reliable and scientific and if correlation isn’t significant can rule out a causal relationship
189
Correlation What are the weaknesses of a correlational design
Don’t prove cause and effect Tend to lack validity
190
Correlation Why is correlations not proving a cause and effect between variables a weakness
Only proves covariables may be related. Variable a may cause variable b or vice versa and may be a third variable having an effect as extraneous variables are not controlled
191
Correlation Why is correlational studies lacking validity a weakness
Whenever a score is manufactured there’s always a chance its not meaningful
192
Distributions What are distributions
Visual representations of psychological data used to interpret data and how the data is distributed
193
Distributions Where should the mode lways be
At the highest point
194
Distributions What is the idea of a normal distribution
For a given attributes such as IQ most scores will be on or around the mean
195
Distributions What shape should a normal distribution form
A bell shaped curve
196
Distributions What should all count the same point on a normal distribution
Mean mode and median
197
Distributions What is true of the tails of the curve on a normal distribution
Extend outwards and never touch the x axis
198
Distributions What are skewed distributions
Data doesn’t form a balanced symmetrical pattern ands appear to lean to one side or another
199
Distributions What is a positive skew
Most of distribution is concentrated towards the left of the graph resulting in a long tail on the right
200
Distributions Where’s the mean mode and median on a positive skew
Mode remains at highest point of the peak Median in the middle Mean is on the rright
201
Distributions How to remember a positive skew
From standing at the origins as though a whale is swimming towards you and its a positive thing
202
Distributions What is a negative skew
Most of the distributions towards the right of the graph and results in along tail of anomalous data on the left
203
Distributions Where is the mean median and mode on a negative skew
Mode remains at highest point of the peak Median always in the middle Mean is on the left
204
Distributions How to remember negative skew
Standing from the origin as if the whale is swimming away which is a bad thing
205
Ethics What are ethics
Issues around hat is seen as right and wrong and acceptable with regards to the actions of others or or societies Values and beliefs
206
Ethics When can ethical issues arise
When there’s a conflict between the rights of participants and the researchers need to gain valuable and meaningful findings
207
Ethics What is the BPS code of ethics
Reseachers have professional duty which ensures all participants are treated with respect and consideration Cost benefit approach taken by the ethics committees
208
Ethics Types of ethical issues
Informed consent Deception Protection from harm Right to withdraw Privacy and confidentiality
209
Ethics What is informed consent
Investigators should give participants sufficient details of an investigation that they can make a considered choice to whether they wish to participate
210
Ethics When is parental consent needed
Children under the age of 16
211
Ethics Who can’t informed consent be gained from
Those under the influence of alcohol or drugs or mentally unfit
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Ethics How is informed consent dealt with
Participants should be issued with a consent letter or form detailing all relevant information that might affect the decision to participate
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Ethics What are the three alternative ways of getting consent and why is it used
Presumptive consent Prior general consent Retrospective consent Researchers think consent and participant knowing aim could spoil the research
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Ethics What is presumptive consent
Ask similar group of people if the study is acceptable if they agree consent of original particiapants is presumed
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Ethics What’s prior general consent
Participant give their permission to take part in a number of studied including one that will involve deception
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Ethics What’s retrospective consent
Participants asked for consent after taking part in the study
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Ethics What’s deception
Withholding of information or misleading participant and it’s unacceptable if participants are likely to object or shown unease once debriefed
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Ethics What should be a voided in relation to deception
Intentionally deceiving over the purpose and general nature of investigations Shouldn’t deliberately be misled without scientific or medical justification
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Ethics How should deception be dealt with if participants can’t know the aim
In an ethical manner
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Ethics What is protection from harm
As a result of their involvement participants should not be placed at any more risk than they would normally physical or psychological
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Ethics How is protection from harm and deception dealt with
Debriefing where participant should be made of the true aim of study, what their data will be used for and given right to withdraw data Reassure behaviour was typical And may need to refer to a counsellor
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Ethics What is right to withdraw
Participants have right to leave the study at any point without giving reason and without consequence
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Ethics How is right to withdraw dealt with
Participants should be informed throughout they can withdraw and if they do even though frustrating they can Afterwards have right to withdraw their data
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Ethics What is right of privacy
Participant have right to control information about themselves and if invaded confidentiality should be protected
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Ethics What’s confidentiality
Right to have any personal data protected
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Ethics Observational research in privacy and confidentiality
Observation only made in public spaced where people might expect to be observed by stranger
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Ethics How is confidentiality dealt with
Personal data must be protected Numbers used instead of names in papers In briefing and debriefing participant reminded data protected
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Ethics What is briefing and debriefing
When participants arrive give briefing to provide informed consent after they will be debriefed
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Ethics What is a brief
Instructions and consent before research starts
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Ethics Checklist for writing a brief
Who you are Area of research Who’s conducting research What procedure is Where research will happen How long it’ll take If recorded Data stored securely Will remain anonymous Can withdraw More detail Chance to ask questions Appropriate ending (name signature and date)
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Ethics Checklist for writing a debrief
Thank participant Make aware of true aims Know rational as why it’s important Give any extra detail that wasn’t know before Where data will be used Remind of withdrawal Behaviour was typical May require counselling Refer to any professionals or service Ask for any questions Name and email
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Observations What is the main way of obtaining data
Watching
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Observations What does observations allow to do
Psychologists to see what people do without asking them and to observe behaviour in a natural or controlled setting
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Observations Why is the absence of variables a positive
Can study more complex interactions
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Observations What is the crossover with experiments
Observation sometimes used within an experiment to assss the DV
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Observations What is the cross over with case studies
Can involve observation that is not the main way of collecting data
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Observations What are the types of observations
Naturalistic or controlled Participant or non-participant Covert or overt
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Observations What are naturalistic observations
Watching and recording behaviour in the setting within which it would normally occur Aspects of environment free to vary Interactions take place as they normally would
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Observations Advantages of naturalistic observations
High external validity so findings can be generalised to everyday life Behaviour more natural and unaffected by anxiety or need to impress
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Observations Disadvantages of naturalistic observations
Uncontrolled extraneous variables so difficult to judge any pattern of behaviour Replication harder to achieve so less reliable Behaviour not likely to be repeated
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Observations What are controlled observations
Watching and recording behaviour within a structured environment Some control over variables might be manipulate to observe affects Control over extraneous variables
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Observations Advantages of controlled observations
Replication is easier as extraneous variables can be controlled
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Observations Disadvantages of controlled observations
Reduced naturalness of behaviour being studied Artificial setting so less external validity Findings not as readily applied to real life settings
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Observations What are cover observations
Participants behaviour watched and recorded without their knowledge or consent and are unaware of it Must be public setting to be ethical
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Observations Advantages of covert observations
Behaviour should reman natural -reduced participant reactivity Increased validity as usual behaviour
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Observations Disadvantages of covert observations
Ethical issues around informed consent privacy and deception and right to withdraw
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Observations What are overt observations
Participants behaviour is watched and recorded with their knowledge and consent
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Observations Advantages of overt observations
No ethical issues around informed consent deception privacy or right to withdraw
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Observations Disadvantages of overt observations
Know your being watched may alter behaviour so affects validity Demand characteristics as participants guess what expecteing to see Participant reactivity
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Observations What are participant observation
Researcher becomes a member of the group whose behaviour he or she is watching May be hidden in order to join a group
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Observations Advantages of participant observations
Likely to provide special insights int the behaviour from inside Increased validity as no strange observer affecting behaviour
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Observations Disadvantages of participant observations
May affect observers objectivity as line between being researcher and participant May lie on memory as no time to take notes Interferes with group behaviour Replication difficult so validity of data cannot be checked
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Observations Whatare nonparticipant observations
Researcher remains outside of group their watching and recording
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Observations Advantage of nonparticipant observations
More objective Doesn’t interfere with behaviour being observed
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Observations Disadvantages of non participant observations
Cant provide info of how people feel Data less likely to be rich Data less valid May lose valuable insight as far away from participants
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Observations What are the ways to record data
Unstructured Structured
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Observations What does researcher do for unstructured observation
Write down everything they see
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Observations What does unstructured observation produce for data
Accounts of data that are rich in detail
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Observations What is unstructured observation appropriate for
Small scale studies with only a few participants
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Observations What is done in structured observation
Target behaviour simplified into a behavioural checklist which clearly defined behaviour in a predetermined way
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Observations What should the behavioural categories be in a behavioural checklist in a structured observation
Observable and measurable
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Observations What way of recording data observations has use smapling for behaviour
structured observations
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Observations what are the two types of sampling for behaviour
Event or time
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Observations What is event sampling
Observer decides on specific events relevant to the investigation and recorde the behaviours every single tie they occur throughout the observation
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Observations What is time sampling
Recording behaviour within a pre established time frame
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Observations What is interobserver reliability
Degree of agreement between individual observers who rate code or assess the same thing
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Observations Why is it recommended that observers don’t conduct studies alone
May miss important details and only notice events that confirm hypothesis which creates bias
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Observations Strength of having two observers for the data
Makes data recording more objective and unbiased
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Observations What must two observers be for interobserver reliability
Consistent in judgement, recorded the same or very similar, must be trained
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Observations What is the main way to maintain to interobserver reliability
Have atleast two observers
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Observations What are the ways to maintain interobserver reliability
-two observers -observers familiarise themselves with behavioural categories -observe same behaviour in a pilot study but independently -correlate data to see how similar it is - revisit behavioural categories and amend
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Observations Strengths of structured observation
-use of behavioural categories makes recording data easier and more systematic -behavioural categories make data collection objective -data produced likely to be numerical so easier to analyse
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Observations Weaknesses of structural observations
-if not enough categories to incorporate all target behaviours then behaviour may not be recorded -if categories ambiguous or overlap data may be inaccurate
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Observations Strength of unstructured observations
Benefit from richness and depth of detail
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Observations Weakness if unstructured observation
-produces qualitative data hard to analyse and record -greater risk of observer bias -difficult to record alll behaviour so might be misses
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Observations Strength of event sampling
Useful when behaviour happens quite infrequently
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Observations Weakness of event sampling
If behaviour too complex may be overlooked important details
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Observations Strength of time sampling
Effective in reducing number of observations needed to be made
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Observations Weaknesses of time sampling
Target behaviour may be missed if occurs between chosen time frame Might be unrepresentative of observation as a whole
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Graphs and tables What are summary tables
When raw scores are converted into descriptive statistics in a table
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Graphs and tables When use a bar chart
Show data in form of categories to be compared to discrete data
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Graphs and tables For a bar chart what’s on the x axis
Categories
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Graphs and tables How should the bars be on a bar chart
Same width separated by spaces to illustrate the data isn’t continuous
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Graphs and tables What goes on y axis for a bar chart
The dependant variable
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Graphs and tables When should a histogram be used
With continuous data
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Graphs and tables What is on the x axis on a histogram
Continuous scores
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Graphs and tables What is on the y axis for histograms
Frequency of data scores
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Graphs and tables How are the bars for a histogram
No spaces between bars as data is continuous and column width should be same for each category
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Graphs and tables What is on the x axis for a line graph or frequency polygon
Continuous data
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Graphs and tables How is a line graph or frequency polygon produced
Drawing line from midpoint top of each bar
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Graphs and tables Advantage of line graph
Two or more frequency distributions can be compared on same graph
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Graphs and tables When is a scattergraph used
With correlation data Two different covariables
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Graphs and tables How is a scatterghraph plotted
One score along x axis and one up y axis
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Graphs and tables What does a scattergrpah show
Relationship between two variables
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Graphs and tables What has to be in the tile of a scattergraph
Relationship between …
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Graphs and tables What are pie charts used to show
Frequency of categories as percentages
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Graphs and tables How do you know which category is which on a pie chart
Sections colour coded and labelled with percentage (could be asked to predict)
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Self report What is self report
Where participant gives information to the researcher and provides details of their own thoughts feeling and behaviour
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Self report What does a questionnaire involve
A pre set list of written questions to which participants responds used to asses thoughts or feelings
300
Self report What might questionnaires be used as in an experiments
To asses the DV
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Self report What are the two types of questions
Open and closed
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Self report What are open questions
Don’t have a fixed range of answers and respondents free to answer in any way
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Self report What type of data do open questions produce
Qualitative data rich in depth and. Detail
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Self report Is data from open questions easy to analyse
May be difficult
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Self report What are closed questions
Offers a fixed number of responses such as yes or no, a 1-10 scale
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Self report What type of data is produces from closed questions
Quantitative which may lack detail sna dos depth
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Self report Is it easy to analyses data from closed questions
Yes
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Self report Strengths of qeistionaires
Cost effective- can gather large amounts of data as distribution to large amounts of people Completed without researcher being present which reduced effort and investigator effects Can be easierly statistically analysed as comparisons made using graphs charts using either qualitative or quantitative data Standardised so easy to replicate
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Self report Questionnaire weaknesses
Demand characteristics Social desirability when participants answer in a way which makes themselves look better Acquiescence bias as peop,e agree with items regardless of the question Misunderstanding questio eg confusing Biased sample as only people willing to complete them which may be a certain type of person so not representative Low response rates can be uneconomical
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Self report What are interviews
Involve face to face interaction between an interviewer and an interviewee
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Self report What are the three types of interviews
Structured, unstructured and semi structured
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Self report What are structured interviews
Made up of pre determines set of questions asked in a fixed order Interviewer asks question and waits for response
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Self report What are unstructured interviews
More conversation like and no set of wqiestions General aim or topic to be discussed Interviewee encourage to explained and elaborate answers
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Self report What are semi structured interviews
List of question worked out in advance but interviewers free to follow up with qiuestions where appropriate
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Self report Advantages of interviews
Less misunderstanding as can be explained or adapted to understand Replication- structured interviews can be easily replicated Unstructured interviews allows follow up of point to gain more insights
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Self report Disadvantages of interviews
Interviewer effects - unconsciously biogas answers Demand characteristics and social desirability bias Lot of skill needed for unstructured interviews Ethics if participants don’t know true purpose Analysis of data from unstructured interview isn’t easy and drawing conclusions from vast amounts of data may not be possible
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Self report What is social desirability bias
tendency for respondents to answer questions in such a way that presents themselves in a better light which lowers validity
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Self report design When designing a questionnaire what can closed questions be further divided into
Likert scales Rating scales Fixed choice options
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Self report design What are likert scales
Respondent indicates their agreement or other wise with a state sent using a scale of usually 5 points ranging from strongly agree to strongly disagree (each number attached with a statement)
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Self report design What are rating scales
Respondent identify a value that represents their strength of feeling about the topics
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Self report design What a fixed choice option
Includes list of possible options and respondents are required to indicate those which apply to them
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Self report design What a interview schedules
List of questions the interviewer intends to ask
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Self report design Why is the interview schedule standardised
To reduce interviewer bias
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Self report design What should a interview be began with
Neutral questions making participant feel relaxed/ comfortable and establish rapport
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Self report design What should participants be reminded of
Confidentiality or right to withdraw
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Self report design What should be avoided when writing questions
Overuse of technical terms which lead to confusion and frustration Emotive language and leading questions Double barrelled questions Double negatives
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Content analysis What is it
Techniques for analysing qualitative data of various kinds
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Content analysis What is it a method for
Quantifying qualitative data by placing the categories and counting their occurrence
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Content analysis What is it a type of
Observational research in which people are studied indirectly via communications they have produced
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Content analysis What is the process
Familiarise yourself with data Identify important categories Give examples Repeatedly read through/ watch/ listen Count and tally behaviours
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Content analysis What are the strengths (short-list)
Ease of applications Complement other method Reliability Avoids ethical issues Type of data produces
332
Content analysis Why is ease of application a strength
Easy to perform Inexpensive research method Noninvasive as doesn’t require participants
333
Content analysis Why is complementing other methods a strength
Can verify results from other research methods and is especially useful as a longitudinal tool
334
Content analysis Why is reliability a strength
Easy to replicate using same materials
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Content analysis How is avoiding ethical issues a strength
Much of the material such as adverts or newspapers are already in public domain so no issues with permission
336
Content analysis Weaknesses (short-list)
Descriptive Flowed results Lack of causality Lack of objectivity
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Content analysis Why is descitipitve a weakness
Doesn’t reveal underlying reasons for behaviour or attitudes
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Content analysis Why is flawed result a weakness
Limited by availability of material so observed trends may not reflect reality eg negative events receive more coverage then positive ones
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Content analysis Why is lack of causality a weakness
Not performed under controlled conditions
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Content analysis What is thematic analysis
Qualitative analytic method involves analysing data to identify patterns and themes within it Organises describes and interprets data Themes become categories for analysis
341
Content analysis Stagesfor thematic analysis
Familiarisation with data Coding Searching for themes Reviewing themes Defining and naming themes Writing up
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Content analysis What is familiarisation with data for thematic
Intensively reading data to become immersed in its content
343
Content analysis What is coding for thematic
Generating codes that identify features of the data important to answering the research question
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Content analysis What’s searching for themes in thematic
Examining codes and dara to identify patterns of meaning
345
Content analysis What is reviewing themes in thematic
Checking potential themes to see if they explains the data and answer the research question themes are then refined
346
Content analysis What is defining and naming themes for thematic
Detailed analysis of each theme creating an informative name for each one
347
Content analysis What is writing up in thematic
Combining all information gained from the analysis
348
Content analysis What is the difference between content analysis and thematic analysis
Thematic goes beyond just counting words or phrases it involved identifying ideas within data and analysing and interpreting
349
Implications of psychological research on the economy What are implications
How what we learn from they findings of psychological research influences affects benefits or devalues the economy
350
Implications of psychological research on the economy What does psychology create and why
Practical applications used in everyday life hopefully for betterment of society throng conducting research
351
Implications of psychological research on the economy What is an example of the practical application
Creating effective therapies
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Implications of psychological research on the economy What do these practical applications allow for and how impact economy
Developed through research allowing many people to go to work and contribute to the economy, earn ,money, pay taxes, not incur long term financial costs upon health service, business don’t pay sick pay and recruite employees to cover absence
353
Implications of psychological research on the economy What are the 4 questions needed to answer the question
What has this research told us, what specifically discovered? What has this led to? What are the consequences for the individual concerned ? What are the implications for businesses or the wider economy
354
Implications of psychological research on the economy What are the sentence prompts to use
Psychological research into … has told us that… This has led to… (practical application) The consequences for the individual are … Implications for businesses or wider economy are…
355
Choosing a statistical test Table
LEARN BLURT
356
Choosing a statistical test What is the pneumonic for it
Carrots should come mashed with swede under roast potatoes
357
Choosing a statistical test What three factors do you need to decide
Whether researcher is looking for difference or correlation Which experimental design is being used Level of measurement
358
Peer review What is peer review
Assessment of scientific work by others who are experts in the same field
359
Peer review Why is it used
Major method used by scientific community to evaluate research and decide what is suitable for publication
360
Peer review What does it ensure
That any research conducted and published is of high quality and accurate in terms of methodology, data analysis etc
361
Peer review What does it evaluate
Research in terms of aims and value and reduces chances of flawed or unscientific research being accepted as fact
362
Peer review How is peer review used for grants
Research is paid for by various government and charitable bodies and has a duty to spend its money responsibly therefore reviews are needed to hep decide which research is likely to be worthwhile
363
Peer review What does journal do and how do they link to peer review
Journals provide scientists with opportunity to share results of their research and peer review is a means of preventing incorrect or faulty data entering the public domain
364
Peer review What is the process of peer review
Several expert reviewers would be sent copies of a researchers work by a journal editor who then report back to editor highlighting weaknesses or problem areas and suggestions for improvement
365
Peer review What might the reviewers recommend
A) The work is accepted unconditionally B) the work is accepted as long as it is improved in certain ways C) work is rejected but suggest revisions D) research should be rejected outright
366
Peer review What is a single blind review
Involves the reviewers names not being reviewed to the researcher and idea that reviewer anonymity allows for an unbiased review free from interference by researcher
367
Peer review What is a double blind review
Involves both reviewer and researcher being anonymous and idea that bias based on researcher will not occur and research will be peer reviewed fairly
368
Peer review What is an open review
Where researcher and reviewed are known top each other to try to reduce risk of personal comments and plagiarism and tries to encourage honest open peer reviewing
369
Peer review Who makes the final decision
The journal editors as to whether to accept or reject the research report based on reviewers comments
370
Peer review 4 criticisms
Finding an expert Anonymity Burying ground breaking research Publication bias
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Peer review What is the criticism for finding an expert
Isn’t always possible to find an appropriate expert with sufficient knowledge to review a researchers proposal or repot if topic is obscure
372
Peer review What does problems finding experts mean
Poor research may be passed because reviewer didn’t really understand it
373
Peer review What are the problems with anonymity
Researcher is conducted in a social world where people compete for grants and jobs so social relationships inevitably effect objectivity to reviewers may use the veil of anonymity to settle old scores or bury rival reseacrh
374
Peer review What is there a danger of with anonymity
Anonymous reviewers may delay the review process to allow them to publish similar research first (even plagiarising the research ) or hide hide behind their anonymity to be underservedly harsh
375
Peer review Why is anonymity hard to establish
Likely would still be identifiable from the writing or research style or topic etc
376
Peer review Who controls the ability to pubshish research problems and who is this limiting
Elites Therefore may be resistance to revolutionary ideas that go against the elite prevailing views
377
Peer review How can peer review go against dissenting or unconventional work
Preference for research that goes with existing theory
378
Peer review How can peer review act as an element that slows rate of change
Science is generally resistant to large a shift in opinion and change tales a long time and requires revolution in the way people think
379
Peer review What publication bias is there
Journals tend to prefer to publish Positve results possible because editors want research that has important implications in order to increase the standing of their journal
380
Peer review What does this result in
Bias in published research leading to misinterpretation of true facts
381
Peer review What can journals avoid publications
Straight replications of a study which is an important part of research validation
382
Inferential testing Why do we do statistical testing
Provides a way of determining whether the null hypothesis should be accepted or rejected In psychology tell us whether differences or relationships between variables are statistically significant or have probably occurred by chance
383
Inferential testing What is the accepted significance levels in psychology
0.05
384
Inferential testing What is a significance levels
Level at which the researcher decides to accept the research hypothesis or not If the experimental hypothesis is accepted this means there is less than 5% probability that the results have occurred by chance and atleast (95% certain that the difference found was because the manipulation of IV affected the DV
385
Inferential testing When may a different significance levels be see and what is it
If new drugs are being trialled at 0.01 sl
386
Inferential testing What does the calculated value need to be compared with
Critical value in a table to decide whether the results are significant or not
387
Inferential testing What do you need to kw to find critical value
Significance levels (0.05 unless stated) Number of participants (N) of df Whether one tailed or two tailed
388
Inferential testing How do you compare critical value to calculated value
Will be told in exam
389
Inferential testing How do you find critical value
On table
390
Inferential testing Which tests use degrees of freedom over N
Chi squared or t tests
391
Inferential testing How do you workout df from t test
Number of participants - 1
392
Inferential testing How do you work out degrees of freedom from chi squared
(Rows - 1)( comulms - 1)
393
Inferential testing What does it mean if the results are significant at the 5% level
There is a less than 5% likelihood that the difference would occur by chance and 95% confidence that the difference is genuine
394
Inferential testing What two errors can be made
Type l error Type ll error
395
Inferential testing What is a type l error
Optimistic error
396
Inferential testing What does a type l error mean
Alternative hypothesis is accepted but null hypothesis is correct so the difference or relationship is wrongly accepted as a real one
397
Inferential testing What is a type ll error
Pessimistic error
398
Inferential testing What does a type ll error mean
Null hypothesis is accepted but alternative hypothesis is correct and a differecne or relationship is wrong let’s accepted as being insignificant
399
Inferential testing Why is a 5% signinfance levvel the accepted level
Strikes difference between making a type i error and type ll error
400
Inferential testing What kind of type can be asked to do in exam
Sign test
401
Inferential testing How do you find the observed s value for sign test
Use a plus or minus sign to indicate the direction of difference for each participant To calculate s add up number of time the less frequency sign occurs
402
Inferential testing How do you find if s value significant or not
Get the critical value of s from a critical value table and dev code if one or two tailed then compare to s value
403
Inferential testing What is important about N when doing a sign test
Need the number of participants omitting any with no sign /change
404
Validity and reliability What is validity
Whether an observed effect is a genuine one
405
Validity and reliability What are the two types
Internal external
406
Validity and reliability What is internal validity
Concerns what goes on inside the experiment Did the IV produce the change in the DV or was it caused by something else
407
Validity and reliability What threatens internal validity
Confounding variables as participant variables Confounding variables as situational variables Demand characteristics Social desirability bias
408
Validity and reliability What are participant variables
Age intelligence motivation experience gender
409
Validity and reliability What are situational variables
Time of day temperature noise order effects investigator effects
410
Validity and reliability What are demand characteristics
Please or screw you effect
411
Validity and reliability What is social desirability bias
Participants present themselves in the best way possible or what is socially acceptable
412
Validity and reliability What is internal validity mostly about
Control
413
Validity and reliability What is external validity
Relates to generalising being able to apply or generalise the findings beyond the research setting
414
Validity and reliability What are the types of external validity
Ecological validity Population validity Temporal validity
415
Validity and reliability What is ecological validity
Can we generalise to different places or settings
416
Validity and reliability What is population validity
Can we generalise to different people or populations
417
Validity and reliability What is temporal validity
Can we generalise to different times
418
Validity and reliability What are the two parts of ecological validity
Mundane realism Generalisability
419
Validity and reliability Whay is mundane realism
Whether a study mirrors real world or everyday experiences
420
Validity and reliability What is generalisability
Extent to which findings from one study conducted in a unique way can be generalised to other setting including the real world
421
Validity and reliability Hat are the 4 ways validity can be assessed
Lie scale Face validity Concurrent validity Predictive validity
422
Validity and reliability What is lie scale
Including questions that act as truth detectors respondents who lie on a high proportion of lie scale items may not be giving truthful answers elsewhere in stduy
423
Validity and reliability What is face validity
Extent to which items look like what a test claims to measure
424
Validity and reliability What is concurrent validity
Assesses validity by correlating scores on a test with another test known to be valid
425
Validity and reliability What is predictive validity
Assesses validity bu predicting how well a test predicts future behaviour
426
Validity and reliability How can validity be improved in experimental validity
Using a control group to assess whether changes to DV were due to IV Standardise procedure to minimise impact of participants reactivity and investigator effects Single and double blind procedures to reduce effects of demand characteristics and investigator effects Field experiments
427
Validity and reliability How do you improve validity for qualitative methods
Usually thought of having higher ecological validity Depth and detail in case studies reflects participants reality Researcher demonstrate interpretive validity of their conclusions demonstrated by direct quotes within report Can also be improved though triangultion using number of different sources as evidence
428
Validity and reliability How can validity be improved in questionnaires
Assure respondents of anonymity Revise items on questionaire after a pilot study
429
Validity and reliability How can validity be improved for observations
Covert observations result in behaviour more natural and authentic Naturalistic observation have higher ecological validity as there may be minimal intervention by researcher Behavioural categories made shoudlnt be too broad overlapping or amibiguous as may have negative impact of validity of data
430
Validity and reliability What is reliability
Measure of consistency
431
Validity and reliability How can validity and reliability linked
Is results are unreliable cannot be valid Can be reliable but not valid
432
Validity and reliability What are the two types of reliability
Internal reliability External reliability
433
Validity and reliability What is internal reliability
Extent to which a measure is consistent within itself
434
Validity and reliability What is external reliability
Extent to which a measure is consistent over time
435
Validity and reliability How is internal reliability assessed
Split half method
436
Validity and reliability How is split half method done
Split a test in two same participants does both halves If both halves provide similar results the test has internal reliability
437
Validity and reliability How is external reliability assessed
Test retest method Inter observer reliability
438
Validity and reliability How is test retest method done
Give same test to same participant on two occasions If same result is obtained reliability established
439
Validity and reliability How is interobserver reliability done
Asses whether observers are viewing and rating behaviour in the same way Achieved by conducting correlations of all observers scores Improved by developing clearly defined and separate categories of observational criteria
440
Validity and reliability How can reliability be improved in questionnaires
Some items may need to be taken out or rewritten and may be interpreted differently by same person on separate occasion Replacing open questions with closed fix choice alternative may be less ambiguous
441
Validity and reliability How can reliability of experiments be improved
Lab experiments more reliable as more control Precise replication of a method ensures all participants are tested under same conditions
442
Validity and reliability How can reliability of interviews be improved
Use same interviewer All interviews must be properly trained to avoid leading/ ambiguous questions Structured interviews investigator behaviour more controlled by fixed questions Unstructured interviews are likely yo be more unreliable
443
Validity and reliability How can reliability be improved for observations
Make sure behavioural categories properly operationalised measurable and self evident Categories shouldn’t overlap All possible behaviours covered to prevent observers having to make own judgements leading to inconsistent results Controlled observations more reliable than naturalistic
444
Reporting psychological investigations What do psychologists do when they write up their research for publication in journal articles
Use a conventional format
445
Reporting psychological investigations What is the conventional format
Title Abstract Introduction Aims and hypotheses Method Results Discussion Conclusion References Appendices
446
447
Reporting psychological investigations What is title
Clear relevant and fully informative
448
Reporting psychological investigations What is abstract
Summary of research (150-200) words Includes aims hypotheses method procedure results conclusions suggestions for future research
449
Reporting psychological investigations What is introduction
Why study was conducted theoretical background previous research beginning broadly then narrowing to aims and hypotheses
450
Reporting psychological investigations What is aims and hypotheses
Includes alternative ands null hypotheses one or two tailed and level of significance
451
Reporting psychological investigations What is method
In enough detail so others could replicate it includes design sample apparatus materials procedures and ethics
452
Reporting psychological investigations What is results
Descriptive statistics eg tab;les graphs measures of central tendency and dispersion Inferential statistics eg choice of statistical test calculated and critical values and which hypothesis was accepted
453
Reporting psychological investigations What is discussion
Explanation of findings relationship to background research limitations and possible improvements to research implications and suggestions for future research
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Reporting psychological investigations What is conclusion
Concise paragraphs to summarise key conclusions drawn from study
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Reporting psychological investigations What are references
Full detail of any material researcher drew upon or cited
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Reporting psychological investigations Why are references needed
So studies used can be further looked into by readers Reduce plagiarism
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Reporting psychological investigations What is appendices
Contains standardised instructions given to participants raw data and calculations plus other stimulus materials usd
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Reporting psychological investigations How do you reference from journal articles
Author surname, initial year of publication title of article title of journal volume number page number
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Reporting psychological investigations How do you defences from author
Author surname initial eds if editors year of publication title of book place of publication publisher
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Reporting psychological investigations How do you references from chapters in booms
Combines aspects of the procedure for journal articles and books by giovning the author of ther chapter their chapter title followed by book
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