Collecting data
At the most basic level, data are considered quantitative if they are numbers and qualitative if they are words. Qualitative data may also include photos, videos, audio recordings and other non-text data. Those who favor quantitative data claim that their data are hard, rigorous, credible and scientific. Those in the qualitative camp counter that their data are sensitive, detailed, nuanced and contextual. Quantitative data best explain the what, who and when of a phenomenon while qualitative data best explain the why and how. Different techniques are used to collect quantitative and qualitative data:
Quantitative methods | How to Collect Data? |
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Surveys/Questionnaires | This most common method can either be self-administered or administered by someone else and can be face-to-face, telephone, mail, or web-based. |
Pre/post Tests | Surveys or measures are collected prior to an intervention among a target population and then an intervention is implemented for a period of time before recollecting the same survey or measurement data after the intervention is complete. The before and after data is compared to detect changes that may be attributed to the intervention. |
Existing Databases | This kind of secondary data is often used in conjunction with survey data. It includes census data, knowledge/attitude/behavior (KAB) studies, criminal justice statistics, performance data, non-confidential client information, agency progress reports, etc. |
Qualitative methods | How to Collect Data? |
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Observations |
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In-Depth Interviews |
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Focus Groups |
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Qualitative studies often utilise a mix of the above mentioned data collection approaches in order to make results more reliable. The use of multiple data collection approaches to improve reliability is known as data triangulation.
In general, researchers agree that qualitative and quantitative data and methods have different strengths, weaknesses, and requirements that affect decisions about which methodologies are appropriate for which purposes.
Now you know how to collect data, but how do you analyze it? Learn more about this in the following.