research methods Flashcards

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1
Q

what is the first stage of planning an experiment?

A

aim

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2
Q

what is involved in the aim?

A
  • focus of our research to produce an aim
  • aims are developed from theories and based on many more hours of research
  • aims are general statements that describe the purpose of an investigation
  • example of an aim would be something like:
    to investigate whether drinking energy drinks makes people more talkative
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3
Q

what is the second stage of an experiment?

A

hypothesis

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4
Q

what is a hypothesis?

A

a hypothesis is a statement made at the beginning of an experiment to clearly state the relationship between variables

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5
Q

what is a directional hypothesis?

A
  • the researcher makes clear the sort of difference that is anticipated between two conditions or two groups of people
  • for this reason, directional hypotheses include words like “more”, “less”, “higher” or “lower”
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6
Q

what a non directional hypothesis?

A
  • the researcher simply states that there will be a difference between conditions or groups of people but the nature of the difference is not specified
    -e.g people who drink HELL differ in terms of talkativeness compared with people who don’t drink hell
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7
Q

when is a directional hypothesis used?

A

when the findings of previous research suggests a particular outcome

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8
Q

when is a non directional hypothesis used?

A

when there is no previous research, or findings from previous studies are contradictory, they will use a non-directional hypothesis instead

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9
Q

what is the IV?

A

what in the experiment that the researcher manipulates

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10
Q

what is the DV?

A

what in the experiment that the researcher records and measures the effect of this change on the dependent variable

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11
Q

what is the levels of IV ?

A

If an experiment compares an experimental treatment with a control treatment, then the independent variable (type of treatment) has two levels: experimental and control.

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12
Q

what is operationalisation of variables?

A
  • many aspects of human behaviour that psychologists study can be complex in construct e.g cognitive thinking, social behaviour
  • one of the main tasks for the researcher is to ensure that the variables being investigated are as clear and measurable as possible
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13
Q

what does statistical testing do?

A

a statistical test tells us which hypothesis is “true” and thus whether we should accept the null hypothesis or accept the alternative hypothesis

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14
Q

what is the first stage of statistical testing?

A

researchers begin by creating either a directional or non directional hypothesis
either is referred to as an alternative hypothesis (H1 for short) because it is alternative to the null hypothesis ( or H0)

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15
Q

what can the researcher do if the levels meet?

A

the researcher can reject the null hypothesis and accept the alternative hypothesis

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16
Q

what is the usual level of significance?

A
  • 0.05 ( or 5%)
  • this is properly written as p <_ 0.05
  • this means the probability that the observed effect (the result) occurred when there is no effect in the population is equal to, or less than, 5%
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17
Q

when is the usual level of significance dropped ?

A

0.05 is the accepted level, but if there is a greater risk to human cost, it is reduced to 0.01

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18
Q

what happens once a statistical test has been completed?

A
  • the result is a number, the calculated value (sometimes referred to as the observed value)
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19
Q

how do we check for statistical significance?

A

the calculated value must be compared with a critical value, the calculated value must be greater than or equal to, or less than or equal to

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20
Q

what is the criteria for statistical tables?

A
  • one - tailed or two - tailed test? directional = one tailed , non directional = two tailed
  • the number of participants in the study - usually appears as N. For some tests, degrees of freedom are calculated instead
  • the level of significance- 0.05 is the standard level in psychological research. In some studies, 0.01 might be used if there is a greater risk to human cost e.g drug trials
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21
Q

what is the sign test and what is the criteria that must be met?

A
  • a simple statistical test to calculate whether a difference found is significant
    three criteria must be met:
    -we need to be looking for a difference, rather than an association
    - we need to have a repeated measures design
    - we need data that is organised into categories, or nominal data
    -data must be converted before the sign test is completed
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22
Q

what are the stages of the sign test?

A
  • Calculate the + and – sign for the given distribution. Put a + sign for a value greater than the mean value, and put a – sign for a value less than the mean value. Put 0 as the value is equal to the mean value; pairs with 0 as the mean value are considered ties.
  • Denote the total number of signs by ‘n’ (ignore the zero sign) and the number of less frequent signs by ‘S.’
  • Obtain the critical value (K) at .05 of the significance level
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23
Q

why do we use a statistical test?

A
  • they work out the probability of whether a particular set of data could have occurred by chance
  • we may have found a difference between our two samples but
  • we want to know if this differences is big enough to be of significance
  • this helps us to know if we can reject the null hypothesis
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24
Q

what are the 3 D’s ?

A
  • levels of Data e.g nominal, ordinal or interval
  • Design e.g related (repeated) or unrelated (independent)
  • Test of Difference or correlation ( difference shows more specific results, correlation is a general relationship)
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25
Q

what is nominal data

A
  • named categories
    -no true mathematical values
    -basic form of data
    -presented in bar charges ( do not touch as data is separate)
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26
Q

what are some examples of nominal data

A

male/ female
tall / small
happy/ upset

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27
Q

what is ordinal data?

A
  • ordered data
  • understand relationships between places
  • no true mathematical values
  • typically scales
    -represented in bar charts
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28
Q

what is an example of ordinal data ?

A

place in a race (1st, 2nd, 3rd) (ranked data)

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29
Q

what is interval data?

A
  • true mathematical values
    -relationships between data
  • can go below 0
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30
Q

what is an example of interval data?

A
  • temperature
  • gap between numbers (-2 → -4 is the same as 34 → 36)
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31
Q

what is ratio data?

A
  • true value of 0
  • cant go below 0
  • true mathematical values
  • relationship between data known
32
Q

what is an example of ratio data?

A

height

33
Q

what tests are considered parametric tests?

A

the related t- test (repeated) , unrelated t - test (independent) and pearson’s r are collectively known as the parametric tests

34
Q

what is the 3 criteria for parametric tests

A
  • data must be interval level - parametric tests use the actual scores rather than ranked data
  • The data should be drawn from a population which would be expected to show a normal distribution for the variable being measured. variables that would produce a skewed distribution are not appropriate for parametric tests
  • there should be homogeneity of variance - the set of scores in each condition should have a similar spread. One way of determining variance is by comparing the standard deviations in each condition. if they are similar, a parametric test may be used. in a repeated measure design it is generally assumed that the two groups of scored have a similar spread
35
Q

what test should you use if the data is nominal and it is a repeated measure’s design ?

A

sign test

36
Q

what test should you use if the data is ordinal and it is a repeated measure’s design ?

A

Wilcoxon

37
Q

what test should you use if the data is interval and it is a repeated measure’s design ?

A

related t - test

38
Q

what test should you use if the data is nominal and it is a independent measure’s design ?

A

chi - squared test

39
Q

what test should you use if the data is ordinal and it is a independent measure’s design ?

A

mann whitney

40
Q

what test should you use if the data is interval and it is a independent measure’s design ?

A

unrelated t - test

41
Q

what test should you use if the data is ordinal and it is correlational ?

A

spearman’s

42
Q

what test should you use if the data is interval and it is correlational ?

A

pearsons

43
Q

what is coding?

A

coding: the process of placing quantitative or qualitative data into categories

44
Q

what is the process of content analysis?

A
  1. data is collected
  2. researcher reads through or examines the data, making themselves familiar with it
  3. the researcher identifies coding units
  4. the data is analysed by applying the coding units
  5. a tally is made of the number of times that a coding unit appears
45
Q

what are the things that the researcher has to make design decisions about (as in observational studies)

A

sampling method
coding the data
methods of representing the data

46
Q

what is involved in sampling the data?

A

the researcher has to look at how they will analyse the data, for example do they select randomly or by a certain characteristic

47
Q

what is involved in coding the data?

A

they must decide how they will analyse the data, will they do it every other_____ or when a certain behaviour is shown

48
Q

what is involved in methods of representing the data?

A

First you identify the behavioural categories ( e.g abstract, landscape etc). Then you record instances in each category.
you can count instances = a quantitative analysis
you can describe examples in each category = a qualitative analysis.

49
Q

what is the problem with qualitative data?

A

it’s difficult to summarise, whereas quantitative data can be used to find central tendencies and create visual graphs

50
Q

what are the main intentions of thematic analysis ?

A
  • to impose some kind of order on the data
  • to ensure the “order represents the participants’ perspective
    to ensure that this “order” emerges from the data rather than any preconceived ideas
  • to summarise the data so that hundred of pages of text or hours of video tape can be reduced
  • to enable themes to be identified and general conclusions drawn
51
Q

what are the strengths of content analysis?

A
  • content analysis tends to have high ecological validity because it is based on observation of what people actually do - real communications that are current and relevant, such as recent newspapers or the books that people read
  • when sources can be retained or accessed by others (e.g back copies of magazines or videos of people giving speeches) the content analysis can be replicated and therefore the observations can be tested for reliability
52
Q

what are the weaknesses of content analysis?

A

observer bias reduces the objectivity and validity of findings because different observers may interpret the meaning of the behavioural categories differently. Content analysis is likely to be culture biased because interpretations of verbal or written content will be affected by the language and culture of the observer and the behavioural categories used

53
Q

what are some reasons why researchers may use case studies?

A

to look at unusual behaviours
to look in greater detail at any kind of behaviour

54
Q

what are some strengths of case studies?

A
  • rich and detailed qualitative data
  • validity and ecological validity (naturally occurring events)
    avoids practical and ethical issues (it’s already happened we are just studying it)
  • triangulation ( able to get information from a variety of sources, getting a more accurate picture)
55
Q

what are some weaknesses of case studies?

A
  • subjectivity (why are we looking at certain people more than others)
    -difficult to generalise
  • lack of replication
  • time consuming
56
Q

what are co variables?

A

the variables investigated within a correlation e.g height and weight. They are not called the IV or DV because a correlation looks for an association between variables rather than a cause and effect relationship where one variable depends on the other. Theory are plotted against each other on a scatter graph to show how one associates with the other

57
Q

what does a correlation closer to 1 indicate?

A

stronger positive correlation

58
Q

what does a correlation further from 1 indicate?

A

stronger negative correlation

59
Q

what is reliability?

A
  • the extent to which a test produces consistent findings every time it is done
    -psychologists tend to not measure concrete things, but more abstract concepts
  • we should be able to measure something time and time again and get similar or same results
  • any two measurements of the same thing should be consistent with each other
60
Q

what factors can reduce reliability?

A

a researcher’s own bias (observer bias)
differences in sample (extraneous variables)

61
Q

how do we use test - retest to test for reliability?

A
  • most simple way of checking for reliability
  • involves giving the same questionnaire ( for example) to the same people on different occasions
  • the results should be as close to the same as possible to have good reliability
  • there must be sufficient time between taking the test and retest so the participant can’t recall their initial answers, but not so long their answer or attitude might have actually changed
  • the two scores would be correlated; if there is a strong positive correlation (exceed +0.80) the measuring instrument is assumed to be good
62
Q

how do we use inter-rater reliability to test for reliability?

A
  • one observer’s interpretation of events may differ from another’s: subjectivity, bias and unreliability go into the data collection process
  • would- be observers should not go-it-alone, but instead conduct their observations in groups of at least two
    -a pilot study man be conducted before the real experiment to test for inter observer reliability
  • similar to a test-retest, observers watch an event and score separately; if the score are positively correlated ( should exceed +0.80) they have good inter-observer reliability
63
Q

what is the split half method?

A

This involves splitting a test into two halves and having the same participant doing both halves of the test. if the two halves of the test provide similar results, this would suggest that the test has internal reliability

64
Q

how do we improve the reliability for questionnaires?

A
  • questionnaires must be completed with a test - retest method and comparing two sets of data should give you a high correlation
  • a questionnaire with low reliability may need to be re written or have some of the items “deselected”
  • certain questions may be ambiguous or be interpreted differently
    it may also be considered to replace open questions with more closed ones
65
Q

how do we improve the reliability of interviews?

A
  • to ensure reliability, you must use the same interviewer each time
    if not, they must all be trained in the same way to ensure that one is not considered different from the others
  • this is more easily avoided in structured interviews where the interviewers behaviour is more controlled by fixed questions and are therefore less likely to be reliable
66
Q

what is validity?

A

This is a measure of the truth, does the test/experiment measure what it says it is measuring.

67
Q

what is internal validity ?

A

How much do the findings of the dependent variable have to do with the independent variable and not other factors.

68
Q

what is external validity?

A

This is all about whether our results can be generalised beyond the study e.g. other settings, other populations of people or even other eras in time.

69
Q

what are the two main types of external validity?

A

Population validity - can the results be generalised to the general population.

Ecological validity - can the results be generalised to the real world.

70
Q

what is temporal validity?

A

This is the idea that the findings of a study or concepts of a particular theory hold true over time.

E.g. Asch’s research on conformity was originally tested in a very
conformist time in American history so lacks temporal validity.

71
Q

what is ecological validity?

A
  • Refers to being able to generalise findings from one study to other situations e.g. to ‘everyday life’
  • The term ‘natural’ in natural experiment leads people to believe such studies must be high in ecological validity
  • Lab experiments, where conditions are controlled are thought to be low in ecological validity

The issue of ‘naturalness’ is slightly more subtle…

72
Q

what happens in face validity?

A

is the simplest technique to test for validity. This is when
an independent expert looks at the measure being used and assesses whether it will measure what it has set out to measure. It looks like its testing what it should be at face value.

73
Q

what is concurrent validity?

A

comparing the new procedure with a similar
procedure that has been done before, where validity has already been established. If the scores correlate as a strong positive correlation (+0.8), then the test is probably valid.

74
Q

how can we improve the validity of experimental research?

A

Using a control group gives the experimenter
something to compare the changes in the dependent
variable due to the effects of the independent variable.

Also the procedures may be standardised to minimise
the effects of pps and investigator effects. Also the use
of single blind (pps do not know the aim) and double
blind (neither pps nor experimenter know the aims of
the study) procedures also have the same effect to
reduce demand characteristics.

75
Q

how can we improve the validity of questionnaires?

A

Many questionnaires include a lie scale within the
questions in order to assess the consistency of pps
responses. This also reduces the effects of social
desirability bias.

Validity will be further enhanced by ensuring that all pps
responses are anonymous.

76
Q

how can we increase the validity of observations?

A

Observations with minimal input from the observer
increases the validity – maybe even better if the
observer is actually covert – meaning that the pps
behaviour is more likely to be natural and authentic.

Ensure also that behavioural categories are not too
broad, not overlapping or ambiguous to increase
validity.

77
Q

how can we increase the validity of qualitative methods ?

A

Qualitative methods also seem to be more valid than
quantitative methods because the depth and details
associated with case studies and interviews better reflects
the pps reality.

Researchers may also have to demonstrate the interpretive
validity – the interpretation of events matches those of their
pps.

Validity is further enhanced by triangulation – the use of
number different sources as evidence e.g. data compiled
through interviews with family, friends, personal diaries,
observations etc.