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Advantages
- Can be considered to be reductionist as it converts complex qualitative data down to simple numbers so is able to make predictions about the frequency of specific behaviours.
- Higher in reliability as it uses a standardised coding schemes to record behaviour so is reliable to check if data is a consistent example of behaviour.
- Allows for the collection of large volumes of data from various sources which can be easily be compared and analysed.
- Reduces 'researcher bias' as specific instances of behaviours/ categories can be objectively measured to ensure validity.
- Findings can be reviewed by other researchers to check for consistency, thus ensuring reliability (inter researcher reliability).
- Can be used as a method to triangulate findings from other sources.
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Disadvantages
- Lower in validity as it is open to researcher bias so may only record behaviours that support their hypothesises so is not a true measure of behaviour.
- Lower in reliability as the qualitative data may be interpreted differently by different researchers making the data less consistent as an explanation of behaviour.
- It is limited to pre-existing material, which may mean it lowers the validity as you may not be able to investigate your aim.
- Possibility of 'researcher bias' as researchers decide in advance what they are looking for in their defined categories, as the content needs to be interpreted, which may limit the internal validity.
- Difficult to generalise findings to everyone as the data comes from specific sources which may not reflect all possible sources.
- Categories can be identified, however it does not give the reasons for these.
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