At this point in your doctoral degree program, you have likely already designed the qualitative research study that is the backbone of your dissertation. The next step, after obtaining Institutional Review Board (IRB) approval, is to collect and analyze the data to find patterns, connections and relationships relevant to the study’s objectives.
Data analysis is perhaps the most important part of the research process. Once you have collected your high-quality data, as a researcher you must take all the information and properly analyze it to gain relevant insights.
Collecting Qualitative Data
Qualitative data collection is exploratory and focused on discovery. It involves collecting a robust data set so that one can then do an in-depth analysis focused on discovering insights, reasoning and motivations. Since qualitative data focuses on searching for understanding, meaning and social patterns, researchers prefer to use data collection methods that can reveal those patterns. Some of the various qualitative data collection methods include:
- One-on-one interviews
- Focus groups
- Visual records
Qualitative Data Analysis
Qualitative data is collected through in-person interactions and recorded in the form of words, observations and images. Compared to quantitative research, which collects clear numerical data to draw conclusions, qualitative research is most often used to explore the how and why of people’s emotions, behaviors and perceptions.
Interpreting and analyzing qualitative data can be challenging and time-consuming. It is a process that usually involves reading through many pages of text-based and visual data and notes, and sometimes listening to hours of audio. Therefore, the analysis process in qualitative research typically begins as soon as the data becomes available.
Analyzing your data is vital to the research process, especially since you have likely spent a lot of time and money collecting it. In an effort to conduct the most beneficial analysis, researchers should first understand the two main approaches to qualitative data analysis:1
1. Inductive Approach
This is a thorough and time-consuming approach to qualitative data analysis with no predetermined rules or structure. Researchers may use this approach in order to identify emerging patterns to reflect what can be discovered.
2. Deductive Approach
In this approach, qualitative data is analyzed based on a structure that is predetermined by the researcher, who can then develop and use questions as a guide for analyzing the data. This approach is preferred when the researcher wants to examine particular categories of information in relation to previous studies or theory. It can be combined with an inductive approach.
Preparing Data for Analysis
Because analysis in qualitative research begins as soon as the data is received, data preparation and analysis occur at the same time, following these steps:
1. Become Acquainted With the Data
Most qualitative data is in a written narrative format. Thus, the researcher will read the data multiple times to become familiar with it and begin identifying similarities and patterns.
2. Review Research Objectives
In a qualitative study, the researcher reviews the study’s objectives and gleans questions or hypotheses that can be answered through the collected data. This is the opposite of quantitative research, which collects data to answer pre-determined questions or hypotheses.
3. Creating Data Structure
Variation is common in qualitative data because this form of research elicits a range of information that is typical in discovery-based research. As data is collected, qualitative researchers will often identify and develop codes to the data that helps categorize and structure the mass of information.
4. Discover Patterns and Connections
Once the qualitative data is collected and coded, researchers will begin identifying themes. They can do this by looking for patterns in the responses to questions and analyze how these answer the core questions driving the study.
Qualitative Data Analysis Methods
There are several methods available for analyzing qualitative research data. The method you choose will depend on your research objectives and questions. These are the most common qualitative data analysis methods to help you complete your dissertation:2
- Content analysis: This method is used to analyze documented information from texts, email, media and tangible items. Researchers use this method to analyze responses from large datasets, often thousands of pages of publicly available data, as well as from interviewees.
- Thematic analysis: This method focuses on a ground-up or inductive approach to discovering patterns in the data though a series of coding exercises to develop themes.
- Narrative analysis: This method analyzes story-based content from sources such as interviews. Researchers use this method to find stories and create master narratives based on the data to answer their research questions.
- Phenomenological analysis: This method analyzes the way that participants in the study describe their “lived experiences” using a specific approach that focuses on what is meaningful to the participant.
- Grounded theory: This method uses qualitative data to describe a particular phenomenon and to develop a theory based on extensive observations, interviews and other data collection techniques.
There are many qualitative data analysis methods to choose from, but these are the most common methods that will help you as you finalize your dissertation.
Applying Data Analysis to Your Dissertation
When done appropriately, data analysis can provide a solid foundation for the results and discussion sections of your doctoral dissertation. Therefore, it is imperative to conduct thorough and careful data analysis in order to derive meaningful and insightful findings.
If you are struggling with any portion of data analysis while working on your dissertation, speak with your university advisor or professor; they will be happy to assist you further.
Start your doctoral journey at Grand Canyon University. The College of Doctoral Studies at GCU offers a variety of qualitative programs to support your research goals. To learn more about GCU’s doctoral programs, click on Request More Info at the top of this page.
1QuestionPro, Qualitative Data – Definitions, Types, Analysis and Examples in May 2021
2GradCoach, Qualitative Data Analysis Methods 101 in May 2021
The views and opinions expressed in this article are those of the author’s and do not necessarily reflect the official policy or position of Grand Canyon University. Any sources cited were accurate as of the publish date.