Open-ended survey questions are useful for documenting perceptions and attitudes within a defined sample but may lack depth.

Interviews provide richer, more in-depth data through one-on-one interactions, allowing exploration of participants' experiences and stories.

Focus groups gather diverse perspectives in a group setting, facilitating discussion and comparison of views among different stakeholders.

Observations capture real-time behaviors and interactions, offering insight into actual practices rather than self-reported perceptions.

Textual or content analysis examines documents and texts to understand institutional views or individual reflections related to the research topic.

Organize and prepare your data, which could involve transcribing interviews or writing up field notes.

Carefully examine your data to spot patterns or repeated ideas that stand out.

Create a coding system based on your initial observations to help sort and label the data.

Apply codes to your data by reviewing each response or piece of information and tagging it accordingly. You can update your coding system by adding new codes if needed.

Discover common themes by grouping related codes into broader, meaningful categories.

In-depth Understanding: Examine complex issues because it gathers detailed and vivid information about people's feelings, experiences, and social environments

Flexibility: Allows researchers to adapt questions, methods and focus during the study in response to emerge insights

Non-Verbal and Interactive Data: Able to observe non-verbal signals and interact directly with participants, enabling them to ask for clarification and gain a more in-depth understanding

Targeted Sampling: Qualitative methods can focus on specific groups or key points, making data collection efficient and cost-effective

Subjectivity and Bias: The researcher’s interpretations may introduce bias, and sample selection can be biased if participants do not represent diverse views

Dependence on Skilled Researchers: Successful qualitative research depends on experienced interviewers or moderators who can guide conversations effectively and explore topics in depth

Demanding in time and resources: Data collection and analysis require significant time, effort, and expertise

Limited generalizability: Only applicable to specific context studied and not mean to be extended to broader populations

Crinson, I., Leontowitsch, M., & Morgan, G. (2016). Principles of qualitative methods: Exercise 2 answers. Health Knowledge. https://www.healthknowledge.org.uk/public-health-textbook/research-methods/1d-qualitative-methods/principles-qualitative-methods-exercise2answers

MW Editing. (n.d.). Advantages of qualitative research. MW Editing. https://www.mwediting.com/advantages-of-qualitative-research/

Poppulo. (2021, August 5). 10 advantages and disadvantages of qualitative research. Poppulo. https://www.poppulo.com/blog/10-advantages-and-disadvantages-of-qualitative-research

Rahman, M. S. (2017). The advantages and disadvantages of using qualitative and quantitative approaches and methods in language “testing and assessment” research: A literature review. Journal of Education and Learning, 6(1), 102–112. https://doi.org/10.5539/jel.v6n1p102

Learn what qualitative research is and how it differs from quantitative research.

Understand when and why qualitative methods are used.

Study key characteristics: non-numerical data, open-ended questions, and rich descriptions.

Transcribe interviews or notes

Organize and store data systematically

Understand what coding is and how to develop a coding system

Use codes to identify patterns and themes

Learn about thematic analysis and other approaches like content analysis or discourse analysis

Group codes into meaningful themes

Interpret how themes connect to your research questions

Learn what quantitative research is and how it differs from qualitative research.

Understand its goal: to collect numerical data and analyze it using statistical methods.

Learn how to analyze data using the appropriate statistical test.

Interpret results based on significance levels

Understand how to draw conclusions and identify trends.

Objectivity and Reduced Bias: Quantitative research only uses numerical data and standardized methods, minimizing personal biases and subjective interpretations

Large Scale and Generalizability: It can collect data from large samples, allowing findings to be generalized to broader populations making result more impactful

Consistency of results: Standardized procedures and a well-defined methodology allow other researchers to repeat the study to confirm the findings, which enhances the study’s credibility

Statistical Analysis: Helps identify patterns, relationship and test hypotheses by using statistical tools

Insights Opinion. (n.d.). What are the strengths of quantitative research. Insights Opinion. https://insightsopinion.com/quantitative-research/what-are-the-strengths-of-quantitative-research

Lim, W. M. (2024). Quantitative research: What, why, when, how, and which. Asia-Pacific Journal of Business Administration, 16(2), 184–198. https://doi.org/10.1177/14413582241264622

Unimrkt Research. (n.d.). What are the strengths of quantitative research. Unimrkt Research. https://www.unimrkt.com/blog/what-are-the-strengths-of-quantitative-research.php

Limited Depth and Context: Lacks the ability to explore complex human experiences, meanings, and social contexts in depth

Dependence on Predefined Variables: It relies on precise operational definitions and may overlook new themes or unexpected insights that are often revealed through qualitative approaches.

Requires Large Samples for Power: Small sample sizes reduce reliability and generalizability, limiting the usefulness of findings in some contexts

Descriptive analysis - Summary of your data will be provide which includes averages and variability. Graphs, scatter plots and frequency tables can be used to visualize data and check for any trends or outliers.

Inferential statistics - Makes predictions or generalizations based on the researcher's data. Hypothesis testing or use sample data to estimate the population parameter.

References:

Bhandari, P. (2023, June 22). What is quantitative research?: Definition, Uses & Methods. Scribbr. https://www.scribbr.com/methodology/qualitative-research/

Experiment: Alter or regulate an independent variable in order to observe its impact on a dependent variable.

Survey: Conduct interviews or surveys with a group of individuals either face-to-face, via telephone, or through online platforms.

Cross-sectional Survey: Observational in nature and are used when the researcher intends to gather data from a sample of the target population at a single point in time.

Longitudinal surveys: To determine causal relationships between variables and closely resembles true experiments, though there are a few key differences.

Bhandari, P. (2023, June 22). What is quantitative research?: Definition, Uses & Methods. Scribbr. https://www.scribbr.com/methodology/qualitative-research/

Ghanad, A. (2023). An overview of quantitative research methods. International Journal of Management, Research and Analysis, 6(8), 3794–3803. https://doi.org/10.47191/ijmra/v6-i8-52

Define Research Objectives- Built research question and goal setting

Collect Data- Gather numerical data through surveys, experiments and so on

Clean and Prepare Data- Remove errors, duplicates, handle missing data and outliers

Explore the Data- Summarize data and inferential statistical methods

Select and Apply Statistical Techniques- Applying descriptive and inferential statistical methods in the research

Interpret Results- Understand and contextualize statistical results

Visualize and Communicate Findings- Present findings using visual tools and written reports

Validate and Review Analysis- Confirm reliability and accuracy of results

Iterate and Refine- Refine analysis based on feedback or additional data

References:

Karl, T. (2024, May 27). Data analysis for quantitative research. EW Horizons.

https://ewhorizons.com/resources/blog/data-analysis-for-quantitative

Ofem, A. (2025, March 23). Quantitative data analysis: Methods, techniques & examples. Hevo Data. https://hevodata.com/learn/quantitative-data-analysis/