Understand Qualitative vs Quantitative Research | SurveyMonkey (2024)

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Understand Qualitative vs Quantitative Research | SurveyMonkey? ›

Qualitative data provides details and context to better understand individual responses, while quantitative data can supply the cumulative results you need to prove the general ideas or hypotheses of your research.

While both share the primary aim of knowledge acquisition, quantitative research is numeric and objective, seeking to answer questions like when or where. On the other hand, qualitative research is concerned with subjective phenomena that can't be numerically measured, like how different people experience grief.

Basically, quantitive data will tell you what your respondents are doing, while qualitative data offers deeper insight into why.

In general, quantitative studies are easier to conduct, but require more participants than qualitative studies. Specifically, data collection in quantitative studies tend to require less time commitment from participants, and the data analysis can be conducted relatively quickly.

Quantitative data, as the name already implies, is the data that is quantifiable or, in other words, that is countable. The data is expressed in numerical figures, making it easier for analysts to understand.

Quantitative studies rely on numerical or measurable data. In contrast, qualitative studies rely on personal accounts or documents that illustrate in detail how people think or respond within society.

Quantitative research is very well suited to establishing cause-and-effect relationships, to testing hypotheses and to determining the opinions, attitudes and practices of a large population, whereas qualitative research lends itself very well to developing hypotheses and theories and to describing processes such as ...

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.

Quantitative data is analyzed using statistical analysis, while qualitative data is analyzed by grouping it in terms of meaningful categories or themes.

Let's look at a few examples of quantitative research question types. Question 1: How much fast food do Americans consume per week? Question 2: How often do students between the ages of 15 – 18 use Facebook weekly? Question 3: How often do male and female university students use a food delivery app monthly?

What are 3 differences between quantitative and qualitative research? ›

Simply put, Qualitative Research is about understanding User Behavior from smaller sample size, and data is collected and synthesized in Textual Form. In contrast, Quantitative Research collects Information from larger sample size of users in numeric form , and data is analysed in numeric form as well.

Quantitative surveys ask close-ended or multiple choice questions for easy analysis. Qualitative surveys ask open-ended questions in which respondents write in their answers, which makes analysis more difficult. Most surveys use both methods.

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers. Some common approaches to analyzing qualitative data include: Qualitative content analysis: Tracking the occurrence, position and meaning of words or phrases.

Limitations of Qualitative Research

Rigor is more difficult to maintain, assess, and demonstrate. The volume of data makes analysis and interpretation time consuming. The researcher's presence during data gathering, which is often unavoidable in qualitative research, can affect the subjects' responses.

Lack of numerical precision: Quantitative data can often be more precise and actionable than qualitative data. Issues with data collection: Collecting a representative sample of data can be difficult when conducting qualitative data analysis.

Analyzing quantitative data is easier and requires less effort than qualitative data. Answers are turned into numbers and statistics that you can use to fuel your business strategy. The first question will yield quantitative data.

2 Challenges of quantitative research

Quantitative research often requires a large sample size, a rigorous design, and a high level of expertise and resources. It can also be difficult to access or collect relevant and accurate data, especially in sensitive or dynamic contexts.

Complexity: The methods and models used in quantitative analysis can be very complex, requiring a high level of expertise to develop, interpret, and act upon. This complexity can also make it difficult to communicate findings to individuals who lack a quantitative background.

One limitation is that it may not provide a deep understanding of users' experiences, emotions, or motivations. Quantitative methods often rely on self-reported data, which may be subject to biases such as social desirability or memory errors.

Qualitative research is very important in educational research as it addresses the “how” and “why” research questions and enables deeper understanding of experiences, phenomena and context. Qualitative research allows you to ask questions that cannot be easily put into numbers to understand human experience.

Why is quantitative research better? ›

Quantitative studies are often fast, focused, scientific and relatable. The speed and efficiency of the quantitative method are attractive to many researchers. Data computing equipment makes it possible to process and analyze data quickly, even with large sample sizes.

However, quantitative research would not be appropriate if/when measurable variables are not known and/or cannot be measured for statistical analysis, such as to determine possible correlations.

In practice, most researchers agree that combining quantitative and qualitative techniques (sometimes called “mixed method” research) produces a richer and more comprehensive understanding of a research area.

Examples of quantitative observation include age, weight, height, length, population, size and other numerical values while examples of qualitative observation are color, smell, taste, touch or feeling, typology, and shapes.

Quantitative research involves analyzing and gathering numerical data to uncover trends, calculate averages, evaluate relationships, and derive overarching insights. It's used in various fields, including the natural and social sciences.

Qualitative research is concerned with participants' own experiences of a life event, and the aim is to interpret what participants have said in order to explain why they have said it. Thus, methods should be chosen that enable participants to express themselves openly and without constraint.

Qualitative data focuses on descriptive variables that cannot be measured or assigned a numeric value. An example of this is the color of fruit, or the feelings of a person to a specific stimulus. Quantitative variables are measurable. They include variables such as height, weight, or speed.

Qualitative research seeks to gain insights and understand people's experiences and perspectives by studying social organizations and human behavior. Data in qualitative studies focuses on people's beliefs and emotional responses.