ANALYSIS + INTERPRETATION OF
QUALITATIVE DATA
KEY POINTS –
Qualitative researchers believe that traditional quantitative methods
do not produce results that are applicable to everyday life.
Qualitative methods emphasise subjectiveness because they aim to
represent the world as seen by the individual.
In order to produce subjective information the qualitative researcher
asks open questions, or uses observation.
The data sets produced in qualitative research tend to be very large,
although the samples might be quite small compared to those used
in quantitative approaches.
If a researcher is trying to produce numbers then they probably
haven’t used qualitative data analysis.
QUALITATIVE ANALYSIS
SUMMARISING QUALITATIVE DATA –
Qualitative data is difficult to summarise.
Whereas quantitative data can be easily summarised with measures
of central tendency, measures of dispersion + with the use of
graphs.
None of these options are possible with purely descriptive findings.
Instead, qualitative data is summarised by identifying repeated
themes.
INDUCTIVE –
Most qualitative analysis aims to be inductive (bottom-up)
→ the categories/themes that emerge are based in the data.
The categories/themes may lead to new theories.
A less common approach to the analysis of qualitative data is the
deductive (top-down) approach
→ the researcher starts with present categories/themes.
These categories are likely to be generated by previous
studies/theories.
The researcher would aim to see if the data is consistent with the
previous theoretical viewpoint.
AN ITERATIVE PROCESS –
Qualitative analysis is a very lengthy process because the data is
gone through repeatedly.
QUALITATIVE DATA
KEY POINTS –
Qualitative researchers believe that traditional quantitative methods
do not produce results that are applicable to everyday life.
Qualitative methods emphasise subjectiveness because they aim to
represent the world as seen by the individual.
In order to produce subjective information the qualitative researcher
asks open questions, or uses observation.
The data sets produced in qualitative research tend to be very large,
although the samples might be quite small compared to those used
in quantitative approaches.
If a researcher is trying to produce numbers then they probably
haven’t used qualitative data analysis.
QUALITATIVE ANALYSIS
SUMMARISING QUALITATIVE DATA –
Qualitative data is difficult to summarise.
Whereas quantitative data can be easily summarised with measures
of central tendency, measures of dispersion + with the use of
graphs.
None of these options are possible with purely descriptive findings.
Instead, qualitative data is summarised by identifying repeated
themes.
INDUCTIVE –
Most qualitative analysis aims to be inductive (bottom-up)
→ the categories/themes that emerge are based in the data.
The categories/themes may lead to new theories.
A less common approach to the analysis of qualitative data is the
deductive (top-down) approach
→ the researcher starts with present categories/themes.
These categories are likely to be generated by previous
studies/theories.
The researcher would aim to see if the data is consistent with the
previous theoretical viewpoint.
AN ITERATIVE PROCESS –
Qualitative analysis is a very lengthy process because the data is
gone through repeatedly.