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For comparison, quantitative data, in this case, could be the frequency of workers to belong to those ethnicities and races. Statistical significance is captured through a ‘p-value’, which evaluate the probability that your discovering for the data are reliable results, not a coincidence. The lower the p-value, the more confident you can be that your findings are reliable. Experimental methods limit how research participants react to and express appropriate social behavior. The analysis is used to understand why a certain phenomenon occurs. Typical data include color, gender, nationality, religion and many more.

They have different philosophies, different data, and different outputs. The insights gained from qualitative research can extend to other groups with proper attention to specific historical and social contexts. This article discusses what qualitative and quantitative research are, how they are different, and how they are used in psychology research. So, to answer the initial question, the approach you use is up to you. However, when deciding on the right approach, you should consider the specific research project, the data you’ll gather, and what you want to achieve.

As noted above, statistics do not tell us about personal, individual experiences and meanings. While surveys can give a general idea, respondents have to choose between only a few responses. This can make it difficult to understand the subtleties of different experiences. Whether you measure the size of the sun 2000 years ago or now, it will always be the same. Qualitative research is about speaking to people directly and hearing their words.

Interesting topics

The goals of quantitative research are to test causal relationships between variables, make predictions, and generalize results to wider populations. Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives. Typical data include measurable quantities such as length, size, weight, mass and many more. Qualitative data is more difficult to analyse than quantitative data.

Where quantitative methods can help answer questions about what is happening in a group and to what degree, qualitative methods can dig deeper into the reasons behind why it is happening. By using both strategies, psychology researchers can learn more about human thought and behavior. The next step in our post for the difference between qualitative and quantitative data is to see what qualitative data analysis involves. Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

The approach to collecting and analysing data differs quite a bit between qualitative and quantitative research. In this post, I’ll explain the qualitative vs quantitative choice in straightforward, plain language with loads of examples. This won’t make you an expert in either, but it should give you a good enough “big picture” understanding so that you can make the right methodological decision for your research. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

The main difference between quantitative and qualitative research is the type of data they collect and analyze. The flexibility of qualitative research allows researchers to adapt their methods based on emerging insights, fostering a more organic and holistic exploration of the research topic. This is a widely used method in social sciences, psychology and market research.

Quantitative Research Methods

Learn the key differences between qualitative and quantitative research from our recent blog. Lastly what is quantitative and qualitative analysis – sometimes, not always, quantitative research may ensure a greater level of anonymity, which is an important ethical consideration. A survey may seem less personally invasive than an interview, for instance, and this could potentially also lead to greater honesty.

1. The scales of measurement are very important because they determine the types of data analysis that can be performed.
2. Quantitative and qualitative research use different research methods to collect and analyse data, and they allow you to answer different kinds of research questions.
3. Tutorials Point is a leading Ed Tech company striving to provide the best learning material on technical and non-technical subjects.
4. You conduct interviews to find out how satisfied students are with their studies.
5. Qualitative researchers must be aware of several different methods and know each thoroughly enough to produce valuable research.

Quantitative research approach

Your research will then, for example, show that 40% of the audience reads fiction and, of that 40%, 60% prefer romance novels. Intellspot.com is one hub for everyone involved in the data space – from data scientists to marketers and business managers. Here you will find in-depth articles, real-world examples, and top software tools to help you use data potential. Silvia Valcheva is a digital marketer with over a decade of experience creating content for the tech industry. She has a strong passion for writing about emerging software and technologies such as big data, AI (Artificial Intelligence), IoT (Internet of Things), process automation, etc.

Statistics

When you want to dig deep into the data at hand, it is advisable that you go with both qualitative and quantitative data analysis. Quantitative and qualitative data analysis when used together can help you generate deeper insights. More often than not, quantitative and qualitative data can be collected from the same data unit as you can see below. So, it’s time to decide what type of research approach you’re going to use – qualitative or quantitative. And, chances are, you want to choose the one that fills you with the least amount of dread. The engineers may be keen on quantitative methods because they loathe interacting with human beings and dealing with the “soft” stuff and are far more comfortable with numbers and algorithms.

With one method, you can ask voters open-ended questions that encourage them to share how they feel, what issues matter to them and the reasons they will vote in a specific way. With the other, you can ask closed-ended questions, giving respondents a list of options. You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale. Based on the answers you get you can ask follow-up questions to clarify things.

By using both quantitative and qualitative data, researchers have a more holistic, well-rounded understanding of a particular topic or phenomenon. As you see when it comes to quantitative data analysis, there are many techniques and methods you can use. There are also a bunch of practical pros to qualitative research. A small sample size means that the researcher can be more selective about who they are approaching. We discuss the many analysis options other blog posts, so I won’t bore you with the details here. So, compared to qualitative research, data collection for quantitative research involves large sample sizes but relatively basic data.

For example, a psychologist wanting to develop a new survey instrument about sexuality might and ask a few dozen people questions about their sexual experiences (this is qualitative research). This gives the researcher some information to begin developing questions for their survey (which is a quantitative method). Analyzing qualitative data is more complex than quantitative data.