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7 - research methods Flashcards

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1
Q

laboratory experiment key features

A

highly controlled, artificial environment, replicable, random allocation

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2
Q

laboratory experiment strengths

A
  • high control over extraneous variables
  • easy to find cause and effect
  • can be replicated
  • measured accurately
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3
Q

laboratory experiment limitations

A
  • data may lack ecological validity
  • high risk of demand characteristics
  • alter behavior based on experiment
  • experimenter bias
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4
Q

field experiment key features

A

natural setting, some variables cant be controlled, independent variable is changed

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5
Q

field experiment strengths

A
  • high ecological validity
  • less likely to have demand characteristics
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6
Q

field experiment limitations

A
  • less replicable
  • sampled bias
  • lack of control on extraneous variables
  • lack of informed consent (ethical)
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7
Q

natural experiment key features

A

independent variable cant be changed e.g. boys/girls, no random allocation

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8
Q

natural experiment strengths

A
  • high ecological validity
  • low demand of characteristics
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9
Q

natural experiment limitations

A
  • sample bias
  • ethical issues
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10
Q

quasi experiment key features

A

naturally occurring independent variable e.g. age, gender

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11
Q

quasi experiment strengths

A
  • allows comparison between types of people
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12
Q

quasi experiment limitations

A
  • can only be used for naturally occurring iv’s
  • ecological validity may be reduced as task may be fairly artificial
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13
Q

what is the difference between a directional and non directional hypothesis?

A

directional - says which way the hypothesis will go e.g. more than
non-directional - there will be a difference

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14
Q

what does operationalised mean?

A

variables and how they will be measured must be clear in the hypothesis

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15
Q

what is a null hypothesis?

A

states there will be no significant difference/correlation in results

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16
Q

what are the 4 types of extraneous variables?

A

demand characteristics
investigator effects
participant variables
situational variables

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17
Q

wat are demand characteristics?

A

participants may want to be helpful and act differently to fit in with the experiment

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18
Q

what are investigator effects?

A

cues from the investigator that encourage certain behaviors e.g. tone of choice

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19
Q

what are participant variables?

A

the natural differences between people e.g. age or gender

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20
Q

what are situational variables?

A

features of experiment may make people respond differently e.g. temp, noise, tiredness

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21
Q

What are the 6 ethical guidelines for experiments

A

1 - informed consent
2 - deception
3 - right to withdraw
4 - protection form psychological and physical harm
5 - confidentiality
6 - privacy

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22
Q

what are the ways of dealing with ethical issues in the UK?

A

1 - cost-benefit analysis
2 - ethics committee
3 - punishment

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23
Q

How is the Canadian approach to ethics different?

A

It stimulates debate, encourages psychologists to engage deeply with ethical rules rather that just follow guideline

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24
Q

Issues with informed consent?

A

giving away aims may reduce validity
presumptive consent - can other people consent for you?

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25
Q

Issues with deception?

A

Cost-benefit analysis is subjective
Debrief cant always undo harm

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26
Q

Issues with Right to Withdraw

A

participants may feel obligated to continue, especially if there is money

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27
Q

issues with protection from harm

A

harm may not be apparent until after

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28
Q

issues with confidentiality

A

may be identifiable even without names e.g. through schools or organisations

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29
Q

issues with privacy

A

there is no universally accepted definition of a public or private place

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30
Q

what is random sampling
positives and negatives

A
  • when all participants have an equal chance of being selected e.g. names in a hat
    positives - unbiased, all pp’s have equal chances
    negatives - need to have a list of all members, time consuming
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31
Q

opportunity sampling method
positives and negatives

A
  • recruit those who are easiest and most available e.g. people walking past
    positives - easy, not time consuming
    negatives - biased (small population) or only people who don’t work at certain times for example
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32
Q

What is stratified sampling
positives and negatives

A

subgroups are identified and a proportional number of pp’s are taken from each group
positives- more representative
negatives- very time consuming to identify, select, and contact participants

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33
Q

what is systematic sampling
positives and negatives

A

predetermined system to select people e.g. every 3rd person
positives- unbiased and uses an objective system
negatives- not truly random unless selected using a random method

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34
Q

what is volunteer sampling
positives and negatives

A

advertised in newspaper / notice boards / internet
positives - access to a variety of participants e.g. people who read certain papers
negatives- biased as some participants are more motivated (volunteer bias)

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35
Q

what are the benefits of a pilot study?

A
  • identifies potential issues early
  • tests effectiveness and can make improvements
  • more likely to get meaningful results
  • reduces wasted time and money
  • able to reduce demand characteristics
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36
Q

methods for quantitative data

A
  • experimental methods with a quantitative dependent variable
  • closed questions
  • tally of behaviours
  • content analysis of descriptive material
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37
Q

methods for qualitative data

A
  • open questions and interviews
  • description of behaviour
  • descriptive material
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38
Q

strengths of quantitative data

A
  • easy to analyse
  • usually objective
  • conclusions can be drawn
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39
Q

weaknesses of quantitative data

A
  • over simplifies complex behaviour
  • closed questions force answers
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40
Q

strengths of qualitative data

A
  • reflects complexities and different experiences
  • encourages description
  • shows feelings
  • data isn’t restricted
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41
Q

weaknesses of qualitative data

A
  • subjective so it’s difficult to draw conclusions
  • hard to analyse
  • not as easy to compare results
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42
Q

what is primary data?

A

data collected first hand directly by the researcher

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43
Q

strengths of primary data?

A

researcher has control over the data
very specific so meets the aims of study

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44
Q

limitations of primary data

A
  • long time to carry out
  • involves a lot of expenses: designing, recruiting, conducting, and analysis
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45
Q

what is secondary data

A

data collected for a different purpose but is utilised and reused by someone
e.g. from government data

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46
Q

strengths of secondary data

A
  • takes less time, equipment and money to access
  • already been analysed so statistics have been decided
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47
Q

limitations of secondary data

A
  • previous studies and data may not fit the aims of the study
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48
Q

what is a meta-analysis

A

a review of similar studies and combines results to form new results

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49
Q

strengths of a meta analysis

A
  • increases validity of findings as there is a wide range of participants
  • if some conclusions are very off, they can be controlled
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50
Q

limitations of a meta analysis

A
  • research design may vary between studies involved, can’t be truly compared
  • effect size may not be appropriate
  • invalid conclusions
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51
Q

what are independent groups?

A

each condition has it’s own group of participants. The scores (DV measurements) for each group are compared.

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52
Q

problem with independent groups and how to control it

A
  • natural variations between individuals in each group may affect the DV measurements, making it look as if the IV has had an effect when it actually hasn’t

control
- after the pp’s have been recruited, they should be randomly assigned to their groups
- they should ensure the groups are similar on average

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53
Q

what are repeated measures

A

only one group of participants is used.
The group completes both conditions and participant
scores in each condition are compared.

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54
Q

problems with repeated measures and how to control them

A

problems
Doing both conditions may
(1)give PPs practice on the task;
(2) make them bored or tired;
(3) allow them to work out the aim of the study, all of which might affect the DV measurement.
(4) Reuse of stimulus material is not possible

Control:
Divide the PPs into two groups.
Half does condition A first, then condition B. The rest do condition B then condition A.
DV measurements for the conditions A
and B are then compared
(counterbalancing).

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55
Q

what are matched pairs?

A

pairs of participants are selected, who are as similar as possible.
One member from each pair completes each condition.
The scores for the pairs of participants are compared.

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56
Q

problems with matched pairs and how to control them

A

Problem:
(1) time consuming;
(2) an exact match is rarely possible;
(3) if one PP drops out you lose 2 PPs’ data.

Control:
Members of each pair should be randomly assigned to conditions.
However, this does not solve all these problems.

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57
Q

what is a non-experimental research technique

A
  • watching and recording behaviour
  • natural behaviour in people’s natural environment
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58
Q

why use observations?

A
  • study a particular behaviour
  • study natural behaviour
  • study behaviour where it would be unethical to manipulate the IV
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59
Q

what are controlled observations?

A
  • pp’s are likely to know they’re being studied
  • some variables are manipulated by researcher
  • may take place in a lab
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60
Q

what are naturalistic observations?

A
  • observing people in their natural environment
  • people behave freely and are less likely to know they’re being observed
  • researcher doesn’t interfere
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61
Q

what is the difference between a participant and non-participant observation

A

participant - observer acts as part of the group being watched
non-participant - observer isn’t part of the group being observed

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62
Q

what is the difference between overt and covert

A

overt - ‘open’ observations where pp’s know they are being observed and why
covert - pp’s don’t know they’re being observed, observer is ‘under cover’

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63
Q

general strengths for ‘observations’

A
  • have high validity: record how people actually behave rather than how they say they behave
  • capture spontaneous and unexpected behaviour
  • can be used to measure the DV in an experiment, so are a key method of gathering data
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64
Q

general limitations of ‘observations’

A
  • observer bias is likely as it is difficult to be objective
  • only observable info is recorded so doesn’t provide insight about how people think or feel
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65
Q

what needs to be taken into consideration about clarity when it comes to questionnaires?

A
  • the reader must be able to understand what is being asked
  • no ambiguity
  • double negative questions reduce clarity
  • double barreled questions are bad e.g. do you experience pain AND headaches
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66
Q

what needs to be taken into consideration about bias when it comes to questionnaires?

A
  • may leaf respondent to be more likely to give a particular answer
  • hard to stop changing answers for social desirability bias
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67
Q

what needs to be taken into consideration about analysis when it comes to questionnaires?

A
  • it is best to use closed questions with quantative data
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68
Q

what are 4 good extra things to add into a questionnaire?

A
  1. filler questions
  2. sequence for questions
  3. sampling technique
  4. pilot study
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69
Q

4 strengths of questionnaires

A
  • once you’ve designed a questionnaire, you can use them for a lot of people, cheaply and quickly
  • may be more likely to share personal info rather than if they are being interviewed
  • reduces experimenter bias
  • no special training needed to conduct
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70
Q

what is experimenter bias?

A

where the participant changes their answers due to the unintentional influence of the experimenter

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71
Q

4 limitations of using questionnaires?

A
  • can take lots of time to design
  • can only be filled by people who can read and write
  • biased due to those willing to fill it in
  • social desirability bias - not wholly truthful
72
Q

what are features of structured interviews?

A
  • predetermined questions
  • no deviation from schedule or questions
  • conducted in real time
73
Q

2 strengths of structured interviews

A
  • it can be easily repeated as the questions are standardised - so easier to compare
  • easier to analyse than an unstructured interview as answers are more predictable
74
Q

2 limitations of structured interviews

A
  • if the same interviewer behaves differently on different occasions, there is low reliability and harder to compare
  • interviewer’s may influence the answer given (interviewer bias)
75
Q

features of an unstructured interview

A
  • questions are developed during the course of the interview based on the answers given
  • may start with predetermined questions
  • sometimes linked to clinical interviews such as a doctors appointment
76
Q

strength of unstructured interviews

A
  • more detailed info can be obtained as the interviewer tailors further questions to the specific response
77
Q

2 limitations of unstructured interviews

A
  • requires interviewers with more skill as they have to develop on the spot. So more expensive to train
  • in depth questions may lack objectivity because of their instantaneous nature
78
Q

what are often effects of the interviewer?

A

the amount of interest and the presence of an interviewer may increase the amount of information provided

79
Q

non verbal communication from interviewer

A
  • arms crossed, frowning, yawning etc may discourage respondent from speaking freely
  • nodding and smiling would encourage
80
Q

features of correlations

A
  • looking for a relationship between 2 sets of data
  • most be continuous
  • uses co-variables rather than IV/DV
  • numbers relate to behaviour
  • coefficient is between -1 and 1
81
Q

what is a directional hypothesis?
correlation

A

a hypothesis that predicts the directions of the relationship or difference

82
Q

what is a non-directional hypothesis?
correlation

A

two tailed hypothesis that doesn’t predict the direction of the difference/correlation

83
Q

what is a null hypothesis?

A

a hypothesis that states there will be no correlation and the statistics are independant

84
Q

strengths of correlations?

A
  • procedure can usually be repeated easily and if findings are similar, research is likely reliable
  • correlations usually have high ecological validity as data comes from natural settings and real life
  • correlations can investigate trends/patterns in data
  • do not require manipulation of any variables so less likely to cause ethical issues
85
Q

limitations of correlations

A
  • correlation does not show causation
  • they only show linear relationships not curvilinear
  • if a casual relationship is shown, it may be due to intervening variables which are unknown variables that can explain why the covariables are links (ice cream sales and crime)
86
Q

characteristics of observations

A
  • has a hypothesis
  • IV isn’t manipulated
  • operationaalise variables
  • has a plan
87
Q

advantages of unstructured observations

A
  1. provides a great deal of rich, qualitative data
  2. can be useful as a pilot study for a more structured observation
88
Q

disadvantages of unstructured observations

A
  1. can be difficult to analyse
  2. can be a tendency for observers to notice the most eye-catching behaviours which may not be most relevant
89
Q

what are features of a structured observation?

A
  • design a type of coding system (behavioural categories) to record pp’s behaviour
  • often made to record how often a type of human behaviours appears
  • data collected is quantitative
90
Q

what is the difference between event sampling and time sampling?

A

event sampling - recording every time a particular behaviour occurs

time sampling - recording observations at specific time intervals e.g. recording identified behaviours every 30 seconds (not including any behaviours outside the interval)

91
Q

how to make an observation more consistent and reliable

A
  • have another person doing the same observation at the same time then comparing data and results after
  • +0.8 correlation = degree of reliability
    inter-observer
92
Q

what is intra-observation

A

same observer does the observation two or more times

93
Q

how to improve the reliability of observations

A
  • clearly operationalise categories
  • train observers correctly
  • pilot studies before
94
Q

features of a positive skew?

A
  • long tail on the positive side of the peak
  • the mean is higher than the mode and median
95
Q

features of a negative skew

A
  • mean is lower than the mode and median
  • long tail on negative side of the peak
96
Q

what is nominal data?

A
  • quantitative value
  • represents discontinuous data
  • no overlap between categories
    e.g.
    eye colour, house, marmite opinion

most useful = mode

97
Q

what is ordinal data?

A
  • shows order of values, but the difference between the values isn’t fixed
    e.g.
    the difference between 1st and 2nd position isn’t the same as 2nd and 3rd

most useful = mode and median

98
Q

what is interval data?

A
  • numeric, we know the order and exact differences between the values
    e.g.
    time in seconds, or distance in cm

mode, median, or mean can all be used

99
Q

what are advantages and limitations of using a mean

A

advantages
- takes into account the exact distances between all the values of the data

limitations
- can’t be used with nominal data
- can be easily distorted by one or a few extreme values

100
Q

what are advantages and limitations of using a median

A

advantages
- not affected by extreme scores
- appropriate for ordinal data
- easier to calculate than the mean

limitations
- not as ‘sensitive’ as the exact values are not reflected in final calculation

101
Q

what are advantages and limitations of using a mode

A

advantages
- unaffected by extreme values
- useful for discrete data
- can be used for category data

limitations
- not useful when there are several modes
- tells us nothing about the other values

102
Q

what is peer review?

A
  • an assessment of scientific work by others wo are experts in the same field
  • judge the scientific quality of research
  • enable poor scientific practice, or fraudulent work to be identified and prevented from being published
103
Q

what are parts of the scientific process?

A
  • assess the appropriateness
  • check the researches validity
  • to judge the significance of the research
  • check if the research is original
  • provide or suggest recommendations
  • publish
104
Q

why are peer reviews needed?

A
  1. ensure it is high quality research
  2. helps allocate research funding
  3. contributes to the research rating of university departments
  4. spot out fraudulent work
105
Q

2 examples of badly reviewed work

A

claim that MMR vaccine leads to autism

Cyril Burt claimed that intelligence is inherited

106
Q

why was Cyril Burt’s work said to be fraudulant?

A
  • he made up lab assistants who didn’t actually exist
  • made up data
107
Q

AO3 of scientific processes
peer review
Limitation
Already published research

A

P - there are some issues with peer review
E - Although it is very important to prevent false information, it can’t solve the issue of already published research.
Once it has been published, the results remain in the public view, even if it were found to be fraudulent
- therefore, it doesn’t ensure information we are exposed to is valid for example Cybil Burt
L - this emphasises the importance of the general public to be more critical about research claims and no always to accept them

108
Q

AO3 of peer review
preserving the status quo

A

P - peer review results in a preference for research that goes with existing theory rather than dissenting or unconventional work
E - Richard Horton made the following comment ‘the mistake is to have thought that peer review was any more than a crude means of discovering the acceptability - not the validity - of a new finding
E - Journals should be aware of the damaging effects of such bias

109
Q

AO3 of peer review
finding an expert

A

P - it isn’t always possible to find an appropriate expert to review a research proposal or report
E - This means poor research may be passed on if the reviewer didn’t really understand it. Also, reviewers may be bias towards the prestigious researchers rather than the less well known names
E - Emphasis the need for rigorous approaches

110
Q

AO3 of peer review
Anonymity

A

P - reviewers may have their identity kept a secret
E - This aim lets them to be completely honest and objective
But, reviewers may use the veil to settle old scores or bury rivals
E - to avoid this, some journals favour open reviewing

111
Q

How can you apply psychology to the economy to psychopathology?

A

McCrone report estimated the direct costs of mental health in England is £22.5 billion per year
Using drugs rather than psychotherapies provides more economic gain as it helps patients to return back to work sooner

112
Q

How can you apply psychology to the economy to memory?

A

Eye witness testimony research improves crime detection and reduces expenses spent on wrongful arrests

113
Q

How can you apply psychology to the economy to social influence?

A

Campaign to reduce drink driving or smoking discussed where attitudes and behaviour was changed making people aware
Leads to potential to bring about positive change so people fit into the norm

Tax forms

114
Q

How can you apply psychology to the economy to attachment?

A

Bowlby’s theory on attachment showed the importance of emotional care in early child development. Continuing and ensuring the healthy development of children to become more productive members of society and thus improving world economy.

115
Q

Why is statistical testing used in psychological research?

A
  • to infer differences or relationships between 2 or more groups
  • helps draw conclusions
  • test if a difference is significant
116
Q

What is the probability level on psychological research unless otherwise stated?

A

0.05 (5%) chance that the result will occur if the null hypothesis is true
Use 0.01 in more life impacting research

117
Q

What is N on the critical values table?

A

Number of scores or participants

118
Q

What is the p level on a critical values table?

A

probability level

119
Q

what is a one tailed hypothesis?

A

A directional hypothesis

120
Q

What is a two tailed hypothesis?

A

A non-directional hypothesis

121
Q

What are the 3 D’s when deciding and justifying the choice of inferential statistical tests?

A

Data (what level of data? nominal, ordinal, interval?)
Difference (difference or relationship?)
Design (what experimental design?)

122
Q

What D’s do you use when using the sign test?

A

Data = nominal
Difference = difference
Design = repeated measures or matched pairs

123
Q

What are the 5 steps of the sign test?

A
  1. Work out the ‘sign’ - whether the score has gone up or down
  2. calculate the value of ‘s’ - add up pluses and minuses and select the smaller value. This is the calculated value
  3. Calculate the value of N - the total number of scores excluding any nil scores
  4. find critical value of S - using critical values table
  5. determine whether results are significant - if the calculated value of S is less than or equal to the critical value of S, it is significant
124
Q

What are descriptive and inferential tests?

A

descriptive - measures of central tendency (mean, median, mode) and dispersion (range, standard deviation)

inferential - used when comparing results with probabilities to decide if results are significant. They can accept or reject null hypothesis

125
Q

What is the parametric criteria?

A
  1. level of data must be interval
  2. data population with a normal distribution (can’t be skewed)
  3. similar range and standard deviation (variance of 1 sample should not be more than 4 times the variance of the other
126
Q

what is content analysis?

A
  • quantifying qualitative information through the use of coding units
  • used to statistically analyse verbal or written or visual material
127
Q

what are the steps involved in content analysis?

A
  1. decide on sample used
  2. read source, identify any themes, break it down into a coding system
  3. read again and tally number of times coding unit occurs
  4. assess and improve reliability
  5. analyse findings through quantitative means e.g. descriptive statistics
128
Q

strengths of using content analysis

A
  • replicable method as coding units aren’t open to interpretation
  • easily obtained materials, no pp’s needed
  • high ecological validity as it observes people in real life settings or communications
  • allows statistical analysis to be conducted
129
Q

limitations of using content analysis

A
  • observer bias if coding categories are ambiguous
  • time consuming if carried out correctly
  • cultural bias where content is interpreted differently
  • causation can’t be established, it only reports data
130
Q

what is thematic analysis?

A

qualitative way of describing and interpreting data through the use of themes

131
Q

what are the intentions of thematic analysis

A
  • impose some kind of order on the data
  • ensure order represents the pp’s perspective
  • ensure order emerges from data rather than any preconceptions
  • summaries data so hundreds of pages/ hours can be reduced
  • enables themes to be identified and general conclusions to be drawn
132
Q

when is thematic analysis useful?

A

when finding out people’s views, knowledge, experiences, values

133
Q

what are the stages of thematic analysis?

A
  1. familiarisation ( get to know the data)
  2. coding (look for/ break down data into useful units and codes)
  3. reviewing themes ( return to data and compare themes against it to ensure they are a good representation of the data)
    is anything missing? are these themes really visible?
  4. defining and naming themes (formulate exactly what is meant by each theme)
134
Q

strengths of thematic analysis

A
  • shows key themes
  • can extend analysis
  • high ecological validity
  • no pp’s needed, no problem with availability
  • replicable
135
Q

limitations of thematic analysis

A
  • subjective nature so open to bias from researcher
  • time consuming
136
Q

what is a case study?

A
  • in depth study of individual, group, event, or institution
  • involves input from family, and others with contact
  • findings are organised to represent the individuals’ thoughts emotions, experiments and abilities
  • longitudinal
137
Q

strengths of case studies

A
  • rich and detailed qualitative data as it focuses on individual throughout a long time
  • validity and ecological validity - high for that one individual or group as the research is carried out in their real life setting
  • avoids practical/ ethical issues - case studies can shed light on aspects of behaviour that couldn’t be set up as research
138
Q

limitations of case studies

A
  • subjectivity - researcher’s interpretation of findings may be different to one another
  • generalisability - hard to generalise to a wider group
  • time consuming - often longitudinal studies which are carried out over a long period of time
  • lack of replication - results can’t be validated by other studies since they are so personal and unique
139
Q

what is reliability?

A

the extent to which a test produces consistent findings every time it is done

140
Q

what are the 2 methods of testing reliablitiy?

A
  1. interobserver reliability - getting another observer to do the same thing and compare the correlation between results (must be over 0.8 to be significant)
  2. test-retest - repeat the test with the same pp’s at a different time
141
Q

how can reliability be improved in lab experiments?

A

standardise procedures

142
Q

how can reliability be improved in observations?

A
  • operationalise behavioural categories more clearly
  • practice using categories so observers can respond more quickly
143
Q

how can reliability be improved in questionnaires?

A
  • reexamine questions and avoid/remove and ambiguity
144
Q

how can reliability be improved in interviews?

A
  • interviewer should be trained to avoid asking leading questions
  • reexamine questions asked
145
Q

What is validity?

A

Refers to whether the study or measuring test is measuring what it claims to measure

146
Q

What are the 2 types of validity?

A

internal - questions whether the results are due to the IV

external - questions whether the results can be generalised

147
Q

what are the ways which internal validity can be affected?

A

Demand characteristics - cues that communicate the aims of the study to participants

Investigator effects - anything the investigator does that impacts the pp’s e.g. encouraging them to try harder

confounding variables - a variable that changes alongside the IV so it is hard to tell what impacts the DV

Social desirability bias - pp’s not being completely to show themselves in a more socially acceptable way

148
Q

what are the examples of external validity?

A

Ecological validity - being able to generalise findings to everyday life and making sure the conclusions would be made in a real life situation

Temporal validity - ability to generalise a research effect beyond the particular time period of the study

Population validity - ability to generalise findings to a wider group of people

149
Q

What are the 2 ways that validity can be tested?

A

Face Validity - looking at something and assessing the extent to which a test or measure appears, on the service, to assess the intended construct

Concurrent validity - comparing new procedure with a similar one that has already been done. If scores correlate as a strong positive (0.8+) the test is probably valid

150
Q

How to improve validity in experimental methods

A

Use a double blind procedure to reduce demand characteristics

151
Q

How to improve validity in observations

A

Non-participant and covert observations should be used so the observed behaviour would be more natural and valid

152
Q

How to improve validity in questionnaires

A
  • questions should be revised so they are related more obviously to the topic
  • If concurrent validity is low, remove irrelevant questions
  • Ensure anonymity
  • Use filler questions to avoid DC
153
Q

How to improve validity in interviews

A

use the same interviewer to reduce investigator effects

154
Q

What is empiricism?

A

Data collected through direct observation or experiments

155
Q

what is objectivity?

A

researchers should not be influenced by personal feelings, opinions, experiences
Remains unbiased
High levels of control
Not open to interpretation

156
Q

what is replicability?

A
  • the ability to repeat a method
  • relies on standardised procedures
  • helps determine validity
157
Q

what is falsibility?

A
  • can’t be scientific unless it admits the possibility of it being found false
  • not necessarily true if it hasn’t been found false
  • ‘fine tunes’ theories to make gradual changes
158
Q

What did Popper say about falsibility?

A

It is not possible to confirm a theory, it is only possible to disconfirm it

159
Q

what is a paradigm

A

An unidentified set of assumptions and agreed methods within a theory e.g. theory of evolution

160
Q

what is a paradigm shift?

A

Gradually disconfirming evidence accumulates and the dominant theory is overthrown
‘scientific revolution’

161
Q

what is theory construction?

A

A theory needs to be a logically organized set of propositions that defines events, describes relationships among events, and explains and predicts the occurrence of events. A scientific theory should also guide research by offering testable hypotheses that can be rigorously tested.

162
Q

what is the difference between inductive and deductive theories?

A

deductive - theory proposed before hypothesis testing

inductive - theory proposed after hypothesis testing
- important in entirely new research

163
Q

What should be included in an abstract?

A

approximately 150 words of a summary / snapshot of what is covered in the work

164
Q

what should be included in the introduction of a psychological report?

A

literature of previous studies which are relevant

165
Q

What is the funnel technique?

A

narrowing down evidence / relevant studies

166
Q

what should the introduction of a psychological report end with?

A

aim and hypothesis
summary of which evidence will be used to back up and why

167
Q

how is an aim different to a hypothesis?

A

aim depicts what they plan in an experiment to do and a hypothesis states a prediction of the results

168
Q

what should the method section of a psychological report include?

A
  1. design
  2. participants
  3. material
  4. procedure
  5. ethics
169
Q

what should the discussion part of a psychological report include?

A
  1. summary of findings
  2. compare results
  3. any limitations and possible suggestions
  4. implications in real life
170
Q

how should book references be written?

A

Author A.A. (year of publication) title of work. Location : puublisher

171
Q

how should journal references be written?

A

Author A.A. and Author B.B. (date of publication) title of article. Title of journal, volume number, page range

172
Q

how should a website reference be written?

A

retrieved from ‘full website address’

173
Q

what should be attached in the appendix?

A

all the research and data collected e.g. consent form, debrief form, questionnaire, diagrams, statistical calculations, raw data

174
Q

What is concurrent validity?

A

the extent to which the results of a particular test or measurement correspond to those of a previously established measurement for the same construct

175
Q

what is probability?

A

the likelihood that a particular event or outcome will occur

176
Q

what is a type I error?

A

when we accept the experimental hypothesis even though the results were actually due to chance (false positive)

177
Q

what is a type II error?

A

when we reject the experimental hypothesis when the results were actually significant (false negative)

Psychology (12 decks)

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