Maybe you’re writing a research paper? Perhaps you’re in charge of a scientific study? In any case, you’re trying to differentiate between quantitative versus qualitative data.
Fortunately, you’ve come to the right place. Below, we’re going to discuss both types of data in detail, helping you facilitate proper data analysis. Let’s go!
What is Quantitative Data?
Quantitative data is hard data that includes numbers and statistics. It is meticulously measured and leaves little margin for interpretation.
Quantitative data is collected in a variety of ways. It could come from a survey that was handed out; it could come from testing; it could come from detailed reports and analyses.
You could reasonably describe quantitative data as being rigid. Because it’s so precise, it can’t easily be twisted to serve different agendas. It can only be used at face value.
Examples of Quantitative Data
There are endless examples of quantitative data. Anything that involves a numerical measurement fits the bill.
One example would be weight. Weighing a car and saying that it weighs 4,000 pounds would be an example of quantitative data. Height, width, circumference, and other such measurements would fit this bill as well.
Another example of quantitative data is cost. For instance, saying that a sandwich costs $3.79 would constitute quantitative data.
Descriptive numerical information would also count as quantitative data. This would include things such as a bicycle containing 2 reflectors or a building containing 3 roof planes.
What is Qualitative Data?
Qualitative data is much more abstract than quantitative data. However, that’s not to say it’s not accurate. It’s just that it doesn’t possess the preciseness of quantitative data (because it’s not conveyed in hard numbers).
Generally speaking, you could refer to qualitative data as descriptions. It can convey the way that something looks, the way that something acts, or the way that something is organized.
Whereas quantitative data is extremely rigid, qualitative data can be quite flexible. It’s generally open to interpretation and is often perceived as less credible than quantitative data.
Examples of Qualitative Data
There are endless examples of qualitative data. As was noted, qualitative data is essentially just descriptions.
So, let’s say you’re looking at a car. You might say that the car’s body is made of metal. This would be a piece of qualitative data.
Of course, you might able to notice an issue with it. Namely, saying that a car’s body is made of metal leaves you open to interpretation. After all, there are many different types of metal; the word metal alone describes the car’s body in a cursory way but doesn’t provide as much value as a solid number would.
You could even get more specific and say that the body is made of steel. However, that would then leave the question of the type of steel.
In short, there’s almost always a way to make qualitative data more specific. There are always additional questions to be asked about it. So, while it might help in supporting an experiment or an argument, it’s never going to be as beneficial as quantitative data.
What Can Qualitative Research Be Used For?
Qualitative research may not be as precise as quantitative data. However, it still serves plenty of benefits.
Generally speaking, qualitative data is used at the beginning of the research process. It helps to define the problem that needs to be addressed and is usually obtained through surveys and focus groups.
For instance, a focus group manager might ask participants how they feel about a certain feature on a car. These participants’ feelings would be recorded and then used to facilitate deeper research.
Studies like these are integral in helping businesses to understand customer behavior. They don’t decide the final conclusions of the study but are vital in helping the researchers to get there.
What Can Quantitative Research Be Used For?
Whereas qualitative data helps to move a study along, quantitative data is used to define the conclusion of the study. It’s the cold, hard data that enables a researcher to act without bias.
Let’s stay with our car feature example. The focus group may have shown that consumers would act favorably toward the new feature. However, statistics on the success of similar features may show that such features are, in fact, a bad idea.
You wouldn’t have realized this with just qualitative data to draw from. But with the help of hard numbers, you can see the reality of the situation.
Obtaining Qualitative Data
You can obtain qualitative data through a variety of means. Some of these include the following.
One way to obtain qualitative data is through documents, whether they be text documents, video documents, audio documents, or otherwise. This involves perusing the document and extracting the data that’s needed.
Another way to obtain qualitative data is through interviews. This involves asking questions to an interview subject and then recording his or her answers.
One last way to obtain qualitative data is through observations. In other words, watch something happen and report on it. You could, of course, use someone else’s observations as well.
Obtaining Quantitative Data
Quantitative data is generally collected a little differently than qualitative data. Some quantitative data collection methods include:
Surveys can be used to collect quantitative data. You can have survey participants answer questions, and then tally up the answers to those questions as a means of finding total numbers and percentages.
Whether it’s mixing chemicals, seeing how different individuals respond to different stimuli, or otherwise, experiments can be hugely beneficial in providing you with quantitative data.
You can also carry out analysis on existing trends, and then use metrics from those analyses as quantitative data. For instance, you could find the percentage of people who drive in a specific city.
Knowing the Difference in Quantitative vs. Qualitative Data Is Important
If you’re carrying out research or performing a scientific study, you need to know the differences between quantitative versus qualitative data. These two data types are quite different, and yet both integral to the research and scientific study processes.
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