3 substantive responses initial post W r i t i n g
3 substantive responses Initial post and two classmates.
Data is all around us, in both our professional and personal experiences. During our discussion topic this week, we will be exploring different types of data that you encounter in your everyday lives, whether it’s at home or on the job.
Respond to the following in a minimum of 175 words:
- Discuss the differences between quantitative and qualitative data, as well as the advantages and disadvantages of each. As a part of your response, describe one type of quantitative data and one type of qualitative data that you encounter in your professional or personal life.
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We have been discussing the differences between quantitative and qualitative data, as well as the advantages and disadvantages of each. But the issue we may also like to examine is why do we need to classify data into these different types. We will find that the nature of the data, depending on whether it is qualitative or quantitative and if quantitative whether it is discrete or continuous allows us to apply appropriate statistical techniques while analyzing such data. Remember that statistics primarily helps us to analyze data in presence of uncertainty using rules of probability. Now, those probability computations depend on the nature of the data. So, it is vital to determine the nature of the data so that we can apply the appropriate probability rules while accounting for the uncertainty present in the data. So, another question that arises is why is uncertainty present while analyzing any data?
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Quantitative data is data that is more defined than qualitative data. This data is much more rigid and typically is measured in numbers and values, which makes it a great candidate for data analysis. Typically quantitative data can be used to ask questions such as “how much” or “how many”. This data can be found through tests, experiments, surveys or market reports. An advantage to this is type of data is the ease in which is can be organized and searched. Because this data is so structured, it is a good option for data analysis.
Qualitative data on the other hand is non-statistical, and usually is less structured than quantitative data. This data is often used to ask the question “why”. It is much more open-ended than quantitative data. This data can be found through texts or documents, images or symbols, focus groups, observations and notes. One advantage to qualitative data is the information that is found within it. It often is much less structured thus providing a lot of information that may not be readily available. However, with that comes its drawback. Qualitative data can be much more time-consuming and expensive to process.
An example of qualitative data versus quantitative data is the different information analyzed when buying a house. Quantitative data may tell you what the square footage of the house is, or how many bedrooms and bathrooms it has. Conversely, qualitative data might tell you what the house is made out of or what it looks like