types of data Flashcards

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1
Q

what is qualitative data?

A

data that is expressed in words and non-numerical (but may be converted to numbers for the purpose of analysis)

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2
Q

what is quantitative data?

A

data that can be counted, usually given as numbers

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3
Q

is qualitative data better than quantitative data?

A
  • no, it depends on the purpose and aims of the research
  • also significant overlap between the two; researchers collecting quantitative data as part of an experiment may often interview participants as a way of gaining more qualitative insight into their experience of the investigation
  • similarly, there are a number of ways in which qualitative information can be converted to numerical data
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4
Q

evaluation of qualitative data: more richness in detail so greater external validity

A
  • much broader in scope
  • gives participant / respondent the opportunity to more fully report their thoughts, feelings and opinions on a given subject
  • greater external validity because it provides the researcher with a more meaningful insight into the participant’s worldviewew
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5
Q

evaluation of qualitative data: difficult to analyse

A
  • tends not to lend itself to being summarised statistically so that patterns and comparisons within and between data may be hard to identify
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6
Q

evaluation of qualitative data: less valid conclusions

A
  • due to the difficulty of analysing qualitative data, conclusions often rely on the subjective interpretations of the researcher
  • these may be subject to bias, particularly if the researcher has preconceptions about what they are expecting to find
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7
Q

evaluation of quantitative data

A

essentially the opposite of qualitative data:

+ relatively simple to analyse so comparisons between groups can easily be drawn
+ data in numerical form tends to be more objective and less open to bias
- narrower in meaning and detail so may fail to represent ‘real life’

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8
Q

what is primary data?

A
  • original data that has been collected specifically for the purpose of the investigation by the researcher
  • arrives first-hand from the participants themselves
  • includes data which is gathered by conducting an experiment, questionnaire, interview or observation
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9
Q

what is secondary data?

A
  • data that has been collected by someone other than the person who is conducting the research
  • it is often the case that secondary data has already been subject to statistical testing so significance is known
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10
Q

where can secondary data come from?

A
  • journal articles
  • books
  • websites
  • information held by the government (eg. census)
  • population records
  • employee absence records within an organisation
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11
Q

what is meta-analysis?

A
  • a form of research method that uses secondary data where a number of studies are identified which have investigated the same aims / hypothesis
  • the results of these studies can be pooled together and a joint conclusion produced
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12
Q

what is the purpose of meta-analysis?

A
  • in the case of experimental research, where the independent variable has been measured in the same way, it is possible to perform a statistical analysis and calculate an effect size (DV of a meta-analysis)
  • this gives an overall statistical measure of difference or relationship between variables across a number of studies
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13
Q

evaluation of meta-analysis: useful

A

allows us to create a larger, more varied sample and results can then be generalised across much larger populations, increasing validity

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14
Q

evaluation of meta-analysis: prone to publication bias

A
  • researcher may not select all relevant studies, choosing to leave out those with negative or non-significant results
  • therefore, conclusions from the meta-analysis will be biased because they only represent some of the relevant data
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15
Q

evaluation of primary data: fits the job

A
  • primary data is authentic data obtained from the participants themselves for the purpose of a particular investigation
  • questionnaires and interviews (eg.) can be designed in such a way that they specially target the information that the researcher requires
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16
Q

evaluation of primary data: requires time and effort from resesarcher

A
  • conducting an experiment, for instance, requires considerable planning, preparation and resources
  • in comparison, secondary data can be accessed within a matter of minutes
17
Q

evaluation of secondary data: inexpensive and easily accessed

A
  • requires minimum effort, unlike primary data
  • when examining secondary data, the researcher may find that the desired information already exists and so there is no need to conduct primary data collection
18
Q

evaluation of secondary data: content of data may not match researcher’s needs

A
  • may be substantial variation in the quality and accuracy of secondary data
  • information might at first appear to be valuable and promising but, on further investigation, may be outdated or incomplete
  • this may challenge the validity of any conclusions
19
Q

what is nominal data?

A
  • numerical value just ‘names’ the attributes
  • discrete data (represents exact figures you can count, such as the numbers of students in a class)
  • categorical
  • separate categories
20
Q

what is ordinal data?

A
  • distance between each unit is unknown
  • data can be ranked
  • rating on a scale
  • subjective
21
Q

what is interval data?

A
  • distance between each unit is equal
  • objective
  • exact, precise score
  • universal measurement
22
Q

what is interval data?

A
  • based on standard unit of measurement
  • no true zero; zero does not indicate nothing (eg. temperature)
  • equal spacing
23
Q

what is ratio data?

A
  • has an absolute zero which cannot go below
  • eg. money earnt?
24
Q

what is parametric data?

A
  • data drawn from a known data distribution
    > ie. we know distribution and we know parameters of distribution
  • often shorthand for real values eg. height of p’s in cm
25
Q

what is non-parametric data?

A
  • data that does not fit a known or well-understood distribution
  • data could be not be real-valued, but is instead ordinal, interval etc.
  • data could also be real-valued but not fit a well understood shape eg. survey conveying consumer preferences ranging from like to dislike