Qualitative and Quantitative Research: What is the Difference?
- Qualitative and Quantitative Research: What is the Difference?
- What Is the Difference between Qualitative and Quantitative Research?
- Qualitative Research
- Quantitative Research?
- What Is the Main Goal of Qualitative vs Quantitative Research
- What Are the Types of Qualitative vs Quantitative Research
- Quantitative Research
- Qualitative Research
- What Are the Qualitative and Quantitative Research Methods?
- Qualitative Research Methods
- Quantitative Research Methods
- Difference in Qualitative and Quantitative Data
- Qualitative vs Quantitative Data Analysis Techniques
- Qualitative data analysis techniques:
- Quantitative data analysis techniques:
- Qualitative vs Quantitative research: How to Choose?
- Final Thoughts
Many spheres require data analysis. By conducting research, you can analyze the current results and make forecasts. Such an option is valuable for business owners, marketing specialists, scientists, etc. There are numerous approaches, but the most common are quantitative and qualitative research.
We are going to describe peculiarities and differences of each research type, provide examples, and specify their pros and cons. It will help you choose whether to conduct qualitative vs quantitative research or both research approaches to fit your project better.
What Is the Difference between Qualitative and Quantitative Research?
The primary difference between quantitative and qualitative research is the kind of data collected. Quantitative research focuses on collection of numerical or statistical data, while qualitative research collects non-numerical data and gives more information about analyzed items in a particular study.
Qualitative research is based on non-numerical data. It is used when the researcher has to dig deeper into the topic. For example, it is required when you want to learn about customers’ preferences and opinions. Qualitative data helps to study from different perspectives. It means that you will analyze various data with quality features rather than numbers.
Examples of qualitative data are gender ratio, name, state of origin statistics, immigration or citizenship dataset.
Quantitative research is based on statistical or numerical data. Researchers apply this method more often than qualitative. The reason is that statistics about different processes, events, prototype items, human behavior is needed more often. The analysis of such data requires accuracy and precision.
Examples of quantitative data collection methods are different forms of surveys (mobile, phone, or paper), phone or face-to-face interviews, website interceptors, systematic observations, and online polls.
What Is the Main Goal of Qualitative vs Quantitative Research
Data analysis is a long process starting from a mass of data to a few meaningful insights. The more researchers know about different data analysis methods, the more chances to choose the most fitting type of research.
What Are the Types of Qualitative vs Quantitative Research
Apart from data collection qualitative and quantitative research differ in types. Check the most commonly used types below.
- Case Study
What Are the Qualitative and Quantitative Research Methods?
There are a few research methods that help the researchers to collect qualitative and quantitative data. We offer you to learn some of them.
Qualitative Research Methods
The most common qualitative research methods that allow to collect non-numerical data are presented below.
- Focus group. Modern business owners and marketing agencies widely use this research method. For example, before starting sales, it is useful to know the prospective customers’ opinion regarding the product. In this case, the researcher has to listen to the audience, ask them additional questions, and record their answers for the analysis of the in-depth results.
- Interview. The researchers conduct interviews to collect qualitative data. The list of questions should be created beforehand to consider all the aspects of the issue.
- Case study. This research method presupposes analysis and investigation of a certain issue in a real-life context.
- Direct observation. When applying this method, subjects are observed without changing their natural environment.
- Survey (open-ended questions). Qualitative research focuses on non-numerical data. Thus, open-ended questions should be used in research. They allow respondents to give extended answers. It gives more wide scope of information.
Quantitative Research Methods
Check the list of methods for collecting accurate statistical data.
- Sampling.It presupposes collecting data from the selected group of people for the research purposes. For instance, collecting the opinion of college students about the quality of food services on the campus. For this purpose, the researcher can survey a sample of 50-70 students.
- Experiment. Experimental research method is based on using two or more sets of variables. For example, to examine the effects of the particular online shop, the researcher should build two or more treatment groups: those recommending medicine and those not recommending it.
- Document review.Document analysis is a popular form of qualitative research when documents are interpreted to assess the chosen topic. This method presupposes coding content into several themes, for example, the analysis of focus group or interview transcripts.
- Interview.A quantitative interview typically asks a participant a series of questions and/or gives a form to fill out. The main purpose is to get questions translated into answers that can be used in research. For example, interview to collect data about the age of participants to assign a numerical value to the participant’s response.
- Surveys and questionnaires. Quantitative surveys and questionnaires are in conformity with the objective of the research question. For example, they may focus on identifying the level of satisfaction of people with their relationships.
Difference in Qualitative and Quantitative Data
Quantitative research methods emphasize data measured consistently along with the statistical, numerical, or mathematical analysis of data collected through questionnaires, polls, surveys, or through manipulation of existing statistical data using different computational techniques. By contrast, qualitative research methods collect and work with non-numerical data to interpret the context.
Qualitative vs Quantitative Data Analysis Techniques
Data analysis is a crucial component of each research, and just a strong analysis will produce accurate results that will make the findings usable. Making a choice regarding your data analysis techniques requires the most attention to ensure getting actionable and insightful findings. There are several commonly used techniques to examine qualitative data and some mathematical techniques to verify and evaluate quantitative data.
Qualitative data analysis techniques:
- Narrative analysis
- Discourse analysis
- Grounded theory
- Content analysis
Quantitative data analysis techniques:
- Conjoint analysis
- SWOT analysis
- TURF analysis
- Cross tabulation
Qualitative vs Quantitative research: How to Choose?
Selecting the proper research method enables answering a research question and testing a hypothesis successfully. Deep knowledge of pros and cons of quantitative vs qualitative research methods will ensure you make the right decision. Both methods, qualitative and quantitative, are effective depending on the research paper. It is crucial to take time and read how to write a research paper. Sometimes, it is more preferable and useful to choose a mixed method approach, especially in dissertations or research studies, to incorporate qualitative and quantitative techniques in different study phases and widen a perspective. The following table will clearly underline the major advantages, disadvantages, and limitations of qualitative vs quantitative research.
Both quantitative and qualitative research types are essential. Type of the research should be chosen based on the data to be analyzed. But, they also work together and allow the researchers to get more specific results, analyze comprehensive data, modify the existing methods, and make excellent decisions.
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