Why quantitative vs qualitative

Qualitative research does not simply help to collect data. It gives a chance to understand the trends and meanings of natural actions. Qualitative research focuses on the qualities of users—the actions that drive the numbers.

It's descriptive research. The qualitative approach is subjective, too. Quantitative data is numbers-based, countable, or measurable. Qualitative data is interpretation-based, descriptive, and relating to language. Quantitative data tells us how many, how much, or how often in calculations. Qualitative data can help us to understand why, how, or what happened behind certain behaviors. Quantitative data is fixed and universal. Qualitative data is subjective and unique. Quantitative research methods are measuring and counting.

Qualitative research methods are interviewing and observing. Quantitative data is analyzed using statistical analysis. Qualitative data is analyzed by grouping the data into categories and themes. As you can see, both provide immense value for any data collection and are key to truly finding answers and patterns.

Take a deeper dive into what quantitative data is, how it works, how to analyze it, collect it, use it, and more. When you collect quantitative data, the type of results will tell you which statistical tests are appropriate to use. As a result, interpreting your data and presenting those findings is straightforward and less open to error and subjectivity.

Another advantage is that you can replicate it. Replicating a study is possible because your data collection is measurable and tangible for further applications. Quantitative research can be limited, which can lead to overlooking broader themes and relationships. By focusing solely on numbers, there is a risk of missing larger focus information that can be beneficial. They both have their advantages and disadvantages and, in a way, they complement each other.

Qualitative research methods are more flexible and utilize open-ended questions. Quantitative data collection methods focus on highly controlled approaches and numerical information.

The data collection toolkit of a qualitative researcher is quite versatile, ranging from completely unstructured to semi-structured techniques. Typically, qualitative research focuses on individual cases and their subjective impressions. This requires an iterative study design — data collection and research questions are adjusted according to what is learned.

Often, qualitative projects are done with few respondents and are supposed to provide insights into the setting of a problem, serving as a source of inspiration to generate hypotheses for subsequent quantitative projects.

Top of Page. Simply put, quantitative research is all about numbers and figures. It is used to quantify opinions, attitudes, behaviors, and other defined variables with the goal to support or refute hypotheses about a specific phenomenon, and potentially contextualize the results from the study sample in a wider population or specific groups. As quantitative research explicitly specifies what is measured and how it is measured in order to uncover patterns in — for example — behavior, motivation, emotion, and cognition, quantitative data collection is considered to be much more structured than qualitative methods.

Quantitative techniques typically comprise various forms of questionnaires and surveys , structured interviews as well as a behavioral observation based on explicit coding and categorization schemes. All of these quantify the behavioral processes in such a way that numerical results can be obtained — for example, fixation duration from eye tracking representing the amount of visual attention , the number of GSR peaks indicating the amount of physiological arousal or the power of a specific EEG band.

After data collection, quantitative analysis techniques and statistics can be applied, such as t-tests and ANOVAs, to non-parametric methods. This often necessitates much bigger sample sizes compared to qualitative research but allows you to make more solid conclusions, that are backed up with data. You can allow all cookies or manage them using the settings below. Cookie Box Settings.

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Anything that is qualitative can be assigned meaningful numerical values. These values can be manipulated to achieve greater insight into the meaning of the data and examine specific hypotheses. Many surveys have one or more short open-ended questions that ask the respondent to supply text responses. The simplest example is probably the "Please add any additional comments" question that is often tacked onto a short survey.

The immediate responses are text-based and qualitative, but we usually perform some type of simple classification of the text responses. We can sort the responses into simple categories. Often, we'll give each category a short label that represents the theme in the response.

The quantitative coding gives us additional useful information that makes it possible to do analyses which we could not do otherwise.