Tag Archives: Qualitative data

Analyzing Qualitative Data

Analyzing qualitative data is not an easy task. Instead of punching script into a statistical programming and receiving results, you become the computer who needs to analyze the data. For this reason alone, the analysis of qualitative data is difficult as different people will have vastly different interpretations of data.

This post will look at the following

  • The basic characteristics of qualitative data analysis
  • Exploring and coding data

Basic Characteristics

Qualitative data analysis has the following traits

  • Inductive form
  • Analyzing data while still collecting data
  • Interpretative

Qualitative analysis is inductive by nature. This indicates that a researcher goes from specific examples to the generation of broad concepts or themes. In many ways, the researcher is trying to organize and summarize what they found in their research coherently in nice neat categories and themes.

Qualitative analysis also involves analyzing while still collecting data.You begin to process the data while still accumulating data. This is an iterative process that involves moving back and forth between analysis and collection of data. This is a strong contrast to quantitative research which is usually linear in nature.

Lastly, qualitative analysis is highly subjective. Everyone who views the data will have a different perspective on the results of a study. This means that people will all see different ideas and concepts that are important in qualitative research.

Exploring and Coding

Coding data in qualitative research can be done with text, images, and or observations. In coding, a researcher determines which information to share through the development of segments, codes, categories, themes. Below is the process for developing codes and categories

1. Read the text

Reading the text means to get familiar with it and now what is discussed.

2. Pick segments of quotes to include in the article

After reading the text, you begin to pick quotes from the interview that will be used for further inductive processing

3, Develop codes from segments

After picking many different segments, you need to organize them into codes. All segments in one code have something in common that unites them as a code.

4. Develop categories from codes

The next level of abstract is developing categories from codes. The same process in step 3 is performed here.

5. Develop themes from categories

This final step involves further summarizing the results of the categories development into themes. The process is the same as steps 3 and 4.

Please keep in mind that as you move from step 1 to 5 the number of concepts decreases. For example, you may start with 50 segments that are reduced to 10 codes then reduce to 5 categories and finally 3 themes.


Qualitative data analysis is not agreed upon. There are many different ways to approach this. In general, the best approach possible is one that is consistent in terms of its treatment of the data. The example provided here is just one approach to organizing data in qualitative research.

Qualitative Data Collection

Qualitative data collection involves normally collecting non-numerical information about a phenomenon. The data collected can be text, pictures, and numerical observation at times. This post will examine differences between qualitative and quantitative research as well as the steps of qualitative data collection

Qualitative vs. Quantitative Research

There are several major difference between qualitative and quantitative data collection.

  • Qualitative relies on a much smaller sample size using purposeful sampling while quantitative involves larger samples selected through random/non-random sampling.
  • Qualitative uses open-ended questions while quantitative uses closed questions when interviewing
  • Qualitative researchers almost always develop their own instruments while quantitative researchers use other people’s instruments.
  • Qualitative research involves personal contact with the respondents while quantitative research does not necessarily require this.
  • Qualitative research tries to help us understand a central phenomenon better while quantitative research seeks to test theories.

Steps of Qualitative Data Collection

Anything that involves qualitative research is rarely linear in nature. This means that the steps mention below does not necessarily happen in the order present. Qualitative research is often iterative and involves repeating steps, moving back and forth as well. In general, it is common to see the following steps happen in qualitative research.

  1. Determine participants-This involves deciding who you will collect data from by identifying a population and appropriate sampling strategy.
  2. Ethical concerns-This relates to obtaining the needed permissions to contact the sample population.
  3. Decide what to collect-You need to determine what information that the participants supply is needed to answer your research questions.
  4. Develop instrument-Design interview protocol
  5. Administer instrument-Conduct the data collection

Again, the process is often never this simple and straightforward. Regardless of the order in which these steps take place, all of the steps need to happen at one time or another when conducting qualitatively.


Qualitative research provides an alternative view to understanding the world. By relying on text and images, qualitative research provides a research description of reality in comparison to quantitative research. In general, there are five steps to qualitative research. The order of the completion of these steps vary but all should be completed when conducting qualitative research.

Qualitative Research Part II

In a previous post, we looked at the first three steps of the process of qualitative research. The steps of this process are below as a review.

  1. Explore a problem to understand the phenomenon
  2. Minor literature review
  3. State purpose and research questions in a general way
  4. Collect data normally from a small sample relying on words instead of numbers
  5. Analyze the data using text analysis to find themes and descriptions
  6. Write up

In this post, we will look at the last three steps of the qualitative research process.

Data Collection

Data collection allows a researcher to learn about the participants of a study. Usually, a protocol or a form for collecting data is created. The protocol can be a list of questions to ask during an interview or a place to record behavior that the researcher observes during the course of data collection. For example, if we are looking at the experience of African students in Thai government schools, we may use an interview protocol, or a list of questions, when collecting data from the students.

The most common forms of data collection include interviews, observation, and document analysis. Interviews is a question and answer session with another individual(s). Observation is the act of watching others. Lastly, document analysis is evaluating written or other objects in the sure for useful information.

Whatever is collected, whether text from interviews, imagines, or other sources becomes a database. Words become a text database. Imagines become an image database. These databases of information are used for the data analysis.

Data Analysis

Data is analyzed in qualitative research in a number of ways. Text segments are the dividing of sentences from the text database into groups. These various groups are used to explain the central phenomenon of the study.

Themes and categories is another analysis technique. In this approach, the researcher looks for commonalities among the data and attempts to organize these themes in order to explain the central phenomenon. For example, if during the course of the interviews with the African students in Thai schools the student mention rejection and humiliation consistently in several interviews, this could be a theme or category of information about the central phenomenon of the experience of these students in Thai schools.

Write Up

The format for qualitative research is similar to quantitative. There is a problem, purpose, literature review, methodology, results, and conclusion. However, this format is much looser in qualitative research and is not strictly followed. Some qualitative studies begin with a long narrative that serves as providing the background of a study as an example.

Qualitative studies have an extensive write up of the data collection which shares the themes and categories as well as the relationship among them. The researcher must also share their biases, values, and assumptions in order to indicate why results were interpreted a certain way. For example, as an African American, I am familiar with the discrimination of Africans in Thailand from my own experience. Therefore, if I were to interview African students about their experience in Thai schools, there would be a temptation to attempt to confirm my own experience as I speak to the students. By sharing this in the write up it informs readers of my own biases about living in Thailand.


Qualitative research is about explaining a central phenomenon. Data collection is for the purpose of gathering information about the topic of the study. The analysis is for the purpose of explaining the results. Lastly, the write up is about conveying the results in a way that is clear for the public.

Types of Data

There are two basic types of data and they are qualitative and quantitative. Qualitative data is data that is often put into categories not based on numbers but often some other form of commonality. For example, if a person conduct interviews about student satisfaction, certain concepts, such as good teaching, may be repeated several times by different students. These statements are combined into one category of student satisfaction, which would be good teaching. There is no continuum of data in qualitative it is strictly the development of categories based on a criteria developed by the researcher.

Quantitative data is numerical data that is often based on a continuum. Example of quantitative data is such things as height, weight, and age.  You can treat quantitative data like qualitative by developing categories but this is a discussion for the future.

When to collect qualitative and quantitative data depends on the research questions of the researcher. Neither is superior to the other and it is the context that determines what is best.