What's the difference, you ask? Easy: the weight of a potato versus its color. Doesn't make sense? Of course it doesn't. But it will, shortly.
There are a several differences between quantitative research and qualitative research, ranging from what they mean to how you can best use them. Continue reading to learn it all.
- Quantitative data deals with numbers and can be measured, and will tell you who and what
- Qualitative data deals with descriptions and can not be measured, and will tell you why
Sounds simple, right? To make this difference even simpler, let's take a look at the following examples:
Red potato Quantitative data
- Weight: 173 g
- Total calories: 154 Cal
- Total carbohydrates: 34 g
- Color: red
- Texture: wavy, creamy
- Flavor: subtly sweet
As you can see, the quantitative data is all kinds of data that can be measured, whereas the qualitative data is data that needs to be described. If we were to give a similar example for a sample of a certain population, it might look as follows:
| Red potato Quantitative data
- Size: 250
- Average age: 23
- Average height: 183 cm
- Site: SuperSimpleSurvey.com
- Looks: good
- Humor: outstanding
When To Use Quantitative Research and When To Use Qualitative Research
Just like there's a difference between what kind of data they contain, there is also a difference in when you would use each of them. In general, qualitative research would be used when the researchers don't really know what to expect or when they don't really know how to define or approach a certain case. In other words, it is more exploratory. It can also be used to go deeper into an already-known issue where the subject itself might not be completely new, but where that specific sub subject is. Using this method can give you insights into upcoming trends and opinions.
Quantitative research, on the other hand, is more conclusive, and you would use it to quantify a problem or generalize a result from a sample. This can provide you with good insights as well, but is of better use if you know where you need to look or what it is exactly you are looking for.
How To Do Quantitative and Qualitative Research
We provide you with numerous free question types to collect all your necessary data. Now that we know what the difference is between quantitative and qualitative data, we can look at how we can survey each of them.
Good question types to survey quantitatively are basically all question types that are close-ended. To get a good response it will help to specifically ask your respondents for a frequency or percentage or amount. For example: how often do you eat potatoes a month? How frequently do you eat meat for dinner? How many meals a day do you consume? You can put these types of questions in Radio Buttons, Checkboxes, Multliple Choice, Drop Down Menus, Likert Scales, Scales, or as an NPS. When using any of these, it is important to make the range of answers fully exhaustive. This means that every possible answer should be included as an option. Let's take a look at the following example:
This question is wrong for two reasons. The first reason is that it is not fully exhaustive - what would you answer if you are 63? The second reason is that there is overlap - what would you answer if you are 30?
A better and more complete way of providing answer options to this question would be:
This way, whatever your age is, you would have no problem deciding which answer you should go for. A different option would be to put Other as an answer, but that would be a better fit if, for example, you were to ask what they had for breakfast - Pancakes, Toast, Oatmeal, Other. That way you single out the main ones, but also make the question fully exhaustive. However, it is advisable to try to always go for well-designed questions and only use the Other answer option sparingly.
Good question types to survey qualitatively are the open-ended question types: text boxes and paragraphs. These are great if you want to dive deeper into a certain subject for exploratory reasons, but some caution is advised here: if you use them too often, it can cause survey fatigue, and you wouldn't want to exhaust your respondent before collecting your valuable insights.
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Photo credit: Greg Turner (thanks, Greg)
Dec 10, 2013