But how do you know what types of data to use and where to use it in order to back up the claims you are making? To be honest, it may not be as difficult as you think. If you know the difference between qualitative and quantitative data, as well as primary and secondary data, you’re well on your way to incorporating data into your dissertation that is sure to make a big impact.
Qualitative data is any type of data that cannot be measured. In other words, it’s information that can be discovered through observation and evaluation. Oftentimes, qualitative data is recorded through things like participant observations, questionnaires, interviews, and focus groups. And when you use qualitative data to support your claims, you basically use contextual information to create meaning. In essence, the results are based on an individual’s experience rather than a scientific fact.
Examples of qualitative data include:
● Audio recordings
● Case studies
● Concept maps
● Diary entries
● Photographs
● Surveys
● Video recordings
Quantitative data, on the other hand, is any type of data that can be measured. It’s recorded in numbers, and it’s often obtained through things like experiments, surveys, polls, and databases. The purpose of incorporating quantitative data to support your claims is to analyse statistics from the past and forecast future trends. In other words, you’re analysing numeric results.
Examples of quantitative data include:
● Distance
● Height
● Price
● Revenue
● Temperature
● Time
● Weight
Depending on the direction you wish to take with your dissertation, you can incorporate qualitative data, quantitative data, or a combination of both. In many instances, the topic you’ve selected will help you determine what types of data complement your argument. Once you’ve made this determination, the best approach is to include data throughout your dissertation—specifically in the areas that make the most sense. Remember, you’re using data to back up certain claims you’re making so that you appear knowledgeable and trustworthy. So, it only makes sense to place the data as close to the claim as possible, basically weaving it into the text.
For example, if you’re stating that past results indicate an increasing trend that will likely continue, you’ll want to include the data you’ve collected by your claim. You wouldn’t want to leave it until pages later when you’re discussing an entirely different claim because that would not make any sense to your reader. In many cases, you may also choose to include a results chapter before you discuss the relevance of the data to your claim. This helps you present all of the data you’ve collected in an objective way.
Just be sure to disclose when you’re using primary data—data you’ve collected yourself—and secondary data—data that was previously collected by others.
