part 2 Flashcards

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1
Q

what is a population?

A

a group of people who are the focus of the researcher’s interest. A sample of people is taken from this

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2
Q

what is a sample?

A

a group of people who take part in a research study (participants). The sample is drawn from the target population
- the findings from the sample is then generalised across the target population

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3
Q

why is it important to make the sample representative of the target population?

A

so the psychologist can generalise the findings from their study to the general population
==> achieve this though using sampling techniques

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4
Q

what are the sampling types?

A

stratified
random
volunteer
systematic
opportunity

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5
Q

what is stratified sampling?

A

sophisticated form of sampling.
- small scale reproduction of the target population which is categorised by categorised into characteristics important to the research.h

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6
Q

how might stratified sampling be conducted?

A
  • identify the strata (sub-group) that make up the population
  • this is proportionate to the overall amount so it is representative and these are calculated

==> eg. if whole population has 18% of people who are make aged 30-40 then the representative sample will have 18% of people who are male aged 30-40

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7
Q

what is random sampling?

A

selecting people in a way that everyone has a fair chance of being selected
==> could be done by pulling names out of hat or using a random number generator

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8
Q

what is volunteer sampling / self selected sampling?

A

people who volunteer / chose to partake when asked or in a response to adverts

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9
Q

what is systematic sampling?

A

Selecting every nth person from a list to make a sample
==> to do this a sampling frame is made which is an organised list of people in the target people. Then researcher has to calculate how many people they need to know which nth term they need.

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10
Q

what is opportunity sampling?

A

selecting those who are most convenient, willing and available to take part there and then.
==> This could he asking people passing in the street for example
(used most by students)

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11
Q

what are the strengths of using stratified sampling techniques?

A
  • the sample is representative of the target population as it is designed to accurately reflect the composition of the population. This means it’s easier to generalise to the wider population.
    ==> also the most representative sampling technique
  • Avoids researcher bias as the selection is based on the sub groups (strata) in society and randomly selected into categories once divided into strata.
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12
Q

what are the limitations of stratified sampling techniques?

A
  • Time consuming in terms of knowing the subgroups and dividing the population into categories, then selecting participants to match these can be very time consuming and lots of effort.
  • Researcher requires knowledge of the subgroups and categories of the population, which may not be available

Because of this, this sampling technique is not commonly used.

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13
Q

what are the strengths of random sampling?

A
  • eliminates researcher bias as they have no influence over who is selected so cannot choose people who they think would support their hypothesis. Therefore more likely to create a representative sample
  • more representative sample means the results are able to be generalised to the target population
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14
Q

what are the limitations of random sampling?

A
  • time consuming and impractical. Not always a possibility to have alll the information on a target population or for all the target population to want to take part in the study. Thus, may end up creating a sample which is like a volunteer sample.
  • may be non-representative as all of one gender could be selected randomly which would not be a true reflection of the target population
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15
Q

what are the strengths of volunteer sampling?

A
  • variety of participants as they are choosing to take part
  • easy and less time consuming as minimum input from the researcher is required.
  • less likely to have people who want to jeopardise the study and its results (screw you / please you effect) as they have asked to take part.
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16
Q

what are the limitations of using volunteer sampling?

A
  • volunteer bias, means the results will not be as generalisable as volunteers are often a certain type of person
  • volunteers may be more subjected to demand characteristics as they are eager to please and they will behave how they think the researcher wants them to.
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17
Q

what are the strengths of using systematic sampling?

A
  • avoids researcher bias so more likely to be a representative sample
    ==> means the results can be generalised to the target population
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18
Q

what are the limitations of using systematic sampling?

A
  • not always truly random as the selection process can interact with a hidden periodic trait
    ( if every 10th person is a 19year old shop worker then they are the entire sample)
  • may be non-representative as all one gender could be selected randomly, which would not be a true reflection of target population.
  • additionally, the strata cannot reflect all the ways people are different which makes complete representation difficult
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19
Q

what are the strengths of opportunity sampling?

A
  • convenient (as it saves time, effort, and money compared to systematic and stratified) and it is a quick and easy way to get information as people are readily available.
  • natural experiments use opportunity sampling as the researcher has no control who is being studied.
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20
Q

what are the limitations of using opportunity sampling?

A
  • cannot generalise as the sample is likely to be unrepresentative
    ==> participants are drawn from one geographical area so not reflective of target population
  • researcher bias as they have complete control over the selection and can choose who they do and don’t want to take part.
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21
Q

what are the types observations

A

naturalistic
controlled
covert
overt
participant
non-participant

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22
Q

what is a covert observation?

A
  • participants are being absorbed without their knowledge
  • researcher may be physically present but pps do not know or don’t realise they’re being observed so observing natural behaviour
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23
Q

what is a strength and limitation of covert observation?

A

strength
- higher levels of validity as pps are unaware they’re being observed so eliminates demand characteristics

limitation
- unethical as doesn’t have participants informed consent

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24
Q

what is an overt observation?

A
  • participants know they’re being observed
  • can see the researcher observing them and are aware their behaviour is being observed an recorded for an observational study
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25
Q

evaluate overt observations?

A

strength
- ethical as participants have given informed consent to be observed

limitations:
- social desirability is likely as they know they’re being observed
- demand characteristics, known as the observer-effect, are more likely which impacts the validity of results

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26
Q

what is a participant observation?

A
  • the researcher joins the group being observed and becomes involved with them
  • the group being observed may not realise this has occurred
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27
Q

evaluate participant observations

A

strength
- researcher is able to build a rapport with pps meaning they are more likely to have open conversations and act in a natural way (gives validity to the findings and mean they can be generalised)

limitation
- ethical considerations such as deception and right to withdraw because the pps may not know they are being observed despite the researcher’s participation

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28
Q

what are non-participant observations?

A
  • the researcher is separate from the participants
  • researcher observes and records the participants without taking part in activities or conversations
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29
Q

evaluate non-participant observations

A

strength
- more likely to remain objective whilst observing and recording behaviour as they cannot get too involved

limitation
- researcher is unable to build rapport and so are less likely to open up completely or enough to show the full natural behaviours (concerns of social desirability?)

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30
Q

what is a naturalistic observation?

A
  • carried out in everyday setting
  • observer doesn’t interfere or change any variables so observing natural behaviour
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31
Q

what is a controlled experiment?

A

certain variables have been controlled by the observer
- the more controlled an experiment, the higher the replicability but the lower the generalisability

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32
Q

what does the term observation design mean?

A

the choice of behaviour to record and how they are measured

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33
Q

what are behaviour categories?

A

target behaviours which are operationalised and what the observers will be looking for.
- They are operationalised to make sure they are specific and that it cannot be confused with anything else other than what the target behaviours are.

==> for example, instead of aggressive behaviour, create specific categories from it such as punching, kicking, biting etc

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34
Q

why must the behaviours be clearly defined in an observational design?

A

there is often more than one researcher, so these categories are clearly defined so they are identifying the same thing.
==> the benefit of having more than one observer because one may miss some important details and may end up with biased observations

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35
Q

evaluate the use of behavioural categories

A

strength:
makes data more structured and objective

limitations:
isn’t always easy to make measurable and as clear as possible ==> still possible to categories that were unexpected and therefore missed off

categories need to be distinctive and not overlap in any way to avoid confusion
eg- grinning vs smiling

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36
Q

why are observers trained beforehand?

A
  • it is important that data is recorded objectively and in an unbiased nature
  • the training ensures they have inter-rater reliability
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37
Q

what is inter-rater reliability

A

level of consistency between 2 or more trained observers when they conduct the same observation

38
Q

what is involved in testing inter-rater reliability?

A
  • agree on list of behaviour categories and how they are going to record them before it begins
  • conduct a pilot study to check categories are appropriate/ clearly defined / not missing anything
  • observation is conducted separately by each observer
  • compare two independent data sets and test the correlations
    ==> if the researchers get a correlation co-efficient of 0.8 or above then (inter-rater) reliability is established
39
Q

why is inter-rater reliability important?

A
  • means that it is less likely to have observer bias and thus is a more valid representation of behaviour
40
Q

what types of sampling procedures are there?

A

time sampling
event sampling
continuous recording

41
Q

what is continuous recording?

A

feature of unstructured observations where detailed notes are recorded
== however, very difficult and rarely practical

42
Q

what is time sampling?

A

researcher records all behaviours for a set time Fram, at a same point

43
Q

evaluate time sampling

A

strength:
allows the researcher flexibility to record behaviour and has the opportunity to record unexpected behaviours
==> reduces the number of observations that need to be done

limitation:
can miss behaviours that do not happen within the set time but may be prevalent to other times in the day (resulting in unrepresentative data)

44
Q

what is event sampling?

A

researcher counts the number of times a certain behaviour happens on target individuals
==> gives quantitative results

45
Q

evaluate event sampling

A

strength:
useful if the behaviourr doesn’t occur very often as unlikely to miss it

limitation:
behaviours that are mot on the list are not recorded which means relevant behaviours could be missed and ignored. (giving unrepresentative date)

46
Q

evaluate structured observations

A

strengths:
- recording of data is more systematic and easier
- the date produced is quantitative (number form) which makes data easier to analyse and compare

limitation:
the observation can lose meaning if all that is produced is numbers

47
Q

evaluate unstructured observations

A

strength:
produced qualitative data (word form) such as descriptions of behaviour. This data is rich and detailed

limitations:
qualitative data is harder to record and analyse

lack of behavioural categories mean that some important behaviours may be missed and they only record the ones which ‘catch their eye’ which aren’t necessarily the most important for the study.
(questions the generalisability)

48
Q

what are self reporting techniques?

A

when the participant reveals personal information about themselves when answering a series of questions
==> usually questionnaire or interviews

49
Q

what are questionnaires?

A

a self report technique which have a mixture of open and closed questions

50
Q

what open questions and what do they provide?

A

allow the participant to write down their own answer and are often seen as having more validity
==> gives qualitative date which can make analysis difficult but provides depth and a true insight into answers that the research not not otherwise get.

51
Q

what are closed questions and what do they provide?

A

provide the participant with a selection of answers to choose from or a yes/no response which can seem less valid as it pre-determines the response
==> this gives quantitative data which is easier to analyse and spot patterns but sacrifices the level of depth and detail associated with open questions

52
Q

what are interviews?

A

direct verbal questioning which can vary in the amount of structure they have

53
Q

what are the types of interviews?

A

structured
unstructured
semi-structured

54
Q

what is a structured interview?

A

interviewer has a series of closed questions which are pre-determined and aren’t changed or elaborated on
==> produces quantitative data which are easy to analyse and compare

55
Q

what is an unstructured interview?

A

the interviewer has a topic of interest they discuss and they are able to adapt questions and develops the depending on the responses given
==> they are able to build rapport which means they are able to get responses which they wouldn’t be able to get in structured
==> produces qualitative data which is more difficult to analyse but provides rich and detailled information

56
Q

what are semi-structured interviews ?

A

the interviewer combines both techniques (structured and unstructured) allowing them to have set questions to ask the pps but are also able to elaborate on some answers
==> produces both quantitative and qualitative data

57
Q

what are principles that make a good questionnaire?

A
  • clear questions that are not ambiguous or worded in a confusing way and are relevant to the aim
  • questions shouldn’t be biased, emotive, or leading to the pps instead should be neutral and not lead them to answer in a particular way
  • usually conduct a pilot study to make sure it’s clear and give more time to refine and improve before conducting actual study
  • don’t use double negatives
58
Q

what are principles that make a good interview?

A
  • use an interview schedule (even in less structured) which is the list of questions that will be asked. Should be standardised
  • avoid interviewer bias
  • decide whether it’ll be a group interview or a one-to-one interview
  • start with neutral questions in order to build rapport
  • remember the ethical issues for example, ensure they know they have the right to withdraw at any point in the study
59
Q

what are the strengths of questionnaires?

A
  • cost effective as large amounts of data can be gathered quickly on a very large scale
  • can be completed without researcher present which reduces time and effort involved
  • straightforward to analyse if closed questions are used because they are fixed choice answers so can be easily compared
  • easy to replicate because a standard set of questions are used
60
Q

what are limitations of questionnaires?

A
  • answers may not always be truthful and be subjected to social desirability to make themselves be seen in a more positive light (thus lie)
  • produce response bias
    ==> respondent tends to answer in a similar for example always ticking yes.
61
Q

evaluate structured interviews

A

Strengths
- easy to replicate because standard set of questions and so easily compared
- interview does not need to have intensive training to ask the questions

Limitations
- interviewer cannot deviate from the questions so only a limited amount of detail can be obtained
- predetermined questions may not provide relevant data required

62
Q

evaluate unstructured interviews?

A

strengths
- interviewer is able to build a rapport which is more likely to allow for honest answers and thus increasing validity
- interesting answers can be followed up and developed for more information as there’s not a prescribed list of questions (more flexible and gain insight)
- produces qualitative Fata which is rich and detailed

Limitations
- analysis of data is difficult and time consuming as every interview will be different making comparisons difficult
- interviewer has to be responsive to the participant and ready to come up with questions on the spot with questions which aren’t leading or showing bias

COUNTER
- risk of social desirability bias however, the interview should be trained enough ti build rapport and therefore get honest responses

63
Q

evaluate semi-structured interviews

A

strengths:
- more flexible than structured as it allows for some exploration and elaboration of answers which builds more rapport and in turn gains more honest insights

limitations
- can be difficult to analyse due to the range of questions included
- interviewer would need specific training to avoid asking leading questions or biased questions
- interviewer has to be responsive and ready to come up with suitable questions on the spot when elaboration is required

64
Q

what is a correlation?

A

illustrates the direction and strength of a relationship between two or more co-variables.

65
Q

what is a co-variable?

A

something being measured to test the relationship with another variable

66
Q

what happens to the variables in correlational research?

A

they are not manipulated but instead measured and compared to look for a relationship

67
Q

what is an appropriate graph to represent correlations?

A

scattergraph

68
Q

what outcome will scattergraphs show?

A

positive correlation
negative correlation
no correlation

69
Q

what is a positive correlation?

A

one co-variable increases as does the other (not necessarily at the same rate so not directly proportional)

70
Q

what is a negative correlation?

A

one co-variable increases while the other decreases
(not necessarily at the same rate)

71
Q

what is no correlation?

A

there is no relationship between the variables whatsoever

72
Q

what is another method other than a scattergraph to analyse the relationship between correlations?

A

calculating the correlation coefficient which is expressed as a numerical value

73
Q

describe the correlation coefficient

A

a number between -1 (perfect negative correlation) and +1 (perfect positive correlation) which tells us how closely the co-variables are related
==> no relationship is expressed as 0
==> + and - indicates whether it is a positive or negative correlation

74
Q

what are intervening variables?

A
  • can be known as third variables which aren’t studied but may come between and affect the ones being studied
75
Q

what are causal relationships?

A
  • studies when there is an IV and a DV (experiments).
    ==> correlations aren’t a causal relationship
76
Q

what is the difference between correlations and experiments

A

experiments involve deliberate manipulation to IV to measure the impact of DV which means a cause and effect can be established. WHEREAS, there is no deliberate manipulation so a causal relationship cannot be established even if there is a strong positive correlation. Instead, the variables have a relationship and affect each other.

77
Q

what are the strengths of correlational analysis?

A
  • a useful starting point for research that gives a precise and quantifiable measure of the relationships between co-variables.
    ==> can be used to assess possible patterns prior to an experimental study
  • the data may be easily available for researchers to quickly analyse which means unlikely to be any ethical issues
  • quick and economical to perform as no manipulation is required and it can involve using secondary data
  • can be used when it would be unethical or impractical to manipulate in a lab setting and can make use of existing data
  • can be repeated again over large samples which allow to check reliable results
78
Q

what are the limitations of correlational analysis?

A
  • no manipulation so only see how co-variables are related and therefore cannot establish cause and effect
  • may be other unknown intervening (3rd) variable or extraneous which may be affecting the outcome and that can explain why the co-variables are linked
  • useful for linear relationships such as height and shoe size however less successful she dealing with non-linear such as number of hours worked and level of happiness
79
Q

what is quantitative data?

A

data in the form of numbers
==> useful for ,ensuring the strength of relationships between factors

80
Q

what are advantages of quantitative data?

A
  • allows for broader study, involving a greater number of subjects and enhancing the generalisability
  • using standards so the research can be replicated and then analysed ad compared with similar studies (easily)
  • personal bias can be avoided by researchers keeping a distance from participating subjects and employing those unknown to them
81
Q

what are disadvantages of quantitative data?

A
  • results are limited as they provide numerical descriptions rather than rich and detailed one generally because they provide less elaborate accounts of human behaviour
  • pre-set sanswers will not necessarily reflect how people truly feel about a subject and in some cases might just be the closest match
82
Q

what is qualitative data?

A

data not in the form of numbers
==> often provides rich and detailed information of social life and behaviour

83
Q

what are the advantages of qualitative data?

A
  • provides depth and detail as it entails recording attitudes, feelings, and behaviours and so gives a detailed picture about WHY people act in certain ways
  • creates openness and rapport so encourages people to expand on their responses truthfully and think about things not initially considered
84
Q

what are the disadvantages of qualitative data?

A
  • usually fewer people studied as to get this data it requires more time and therefore unless time, stand and budget allows, it is necessary o include a smaller sample size
  • less easy to generalise because fewer people are studied so cannot generalise to all of the population
  • dependant on the skills of the researcher particularly in the case of conducting interviews and observations
85
Q

what is primary data?

A

information that wasn’t present before the research began. It has been generated by the researcher for example, from questionnaires, interviews and observations

86
Q

evaluate primary data?

A

strength:
can conduct research in the way specifically required for the topic being studied

limitation:
can take time to produce and usually only small amounts studied which makes generalisation difficult

87
Q

what is secondary data?

A

refers to data which already exists
for example from historical records, official statistics, newspapers, films, and recorded music

88
Q

evaluate secondary data

A

strength:
qualitative secondary sources are very useful at providing rich, detailed data which can be cheap and easy to access

limitation
needs to be approached with caution as there can be issues with authenticity, credibility, and representativeness

89
Q

what is a meta-analysis?
- what type of data is it
- how can qualitative and quantitative be used?

A

a meta-analysis is when a large number of studies that have all investigated the same research topic, using the same methods, are combined
- secondary data
- qualitative = discuss findings and conclusions
- quantitative = perform a statistical analysis of combined data

90
Q

evaluate meta-analysis

A

strength
- allow us to vie data with more confidence as findings can be applied across wider populations

limitation
- publication bias due to the file-drawer problem. This means that only studies that support the hypothesis are looked at and the rest are excluded
==> for example, Van Ijendoor + kroonenburg
- cultural variations in attachment type from the strange situation