How To Choose Your Methodology
The Methodology Wars: Qualitative vs Quantitative vs Mixed Methods
By: Derek Jansen (MBA). Expert Reviewed By: Dr Eunice Rautenbach | June 2021
In this post, we’ll explain the three overarching types of research – qualitative, quantitative and mixed methods – and how you can go about choosing the best methodological approach for your research.
1. Understanding the options
Before we jump into the question of how to choose a research methodology, it’s useful to take a step back to understand the three overarching types of research – qualitative, quantitative and mixed methods-based research. Each of these options takes a different methodological approach.
Qualitative research utilises data that is not numbers-based. In other words, qualitative research focuses on words, descriptions, concepts or ideas – while quantitative research makes use of numbers and statistics. Qualitative research investigates the “softer side” of things to explore and describe, while quantitative research focuses on the “hard numbers”, to measure differences between variables and the relationships between them.
Importantly, qualitative research methods are typically used to explore and gain a deeper understanding of the complexity of a situation – to draw a rich picture. In contrast to this, quantitative methods are usually used to confirm or test hypotheses. In other words, they have distinctly different purposes. The table below highlights a few of the key differences between qualitative and quantitative research – you can learn more about the differences here.
- Uses an inductive approach
- Is used to build theories
- Takes a subjective approach
- Adopts an open and flexible approach
- The researcher is close to the respondents
- Interviews and focus groups are oftentimes used to collect word-based data.
- Generally, draws on small sample sizes
- Uses qualitative data analysis techniques (e.g. content analysis, thematic analysis, etc)
- Uses a deductive approach
- Is used to test theories
- Takes an objective approach
- Adopts a closed, highly planned approach
- The research is disconnected from respondents
- Surveys or laboratory equipment are often used to collect number-based data.
- Generally, requires large sample sizes
- Uses statistical analysis techniques to make sense of the data
Mixed methods-based research, as you’d expect, attempts to bring these two types of research together, drawing on both qualitative and quantitative data. Quite often, mixed methods-based studies will use qualitative research to explore a situation and develop a potential model of understanding (this is called a conceptual framework), and then go on to use quantitative methods to test that model empirically.
In other words, while qualitative and quantitative methods (and the philosophies that underpin them) are completely different, they are not at odds with each other. It’s not a competition of qualitative vs quantitative. On the contrary, they can be used together to develop a high-quality piece of research. Of course, this is easier said than done, so we usually recommend that first-time researchers stick to a single approach, unless the nature of their study truly warrants a mixed-methods approach.
The key takeaway here, and the reason we started by looking at the three options, is that it’s important to understand that each methodological approach has a different purpose – for example, to explore and understand situations (qualitative), to test and measure (quantitative) or to do both. They’re not simply alternative tools for the same job.
Right – now that we’ve got that out of the way, let’s look at how you can go about choosing the right methodology for your research.

2. How to choose a research methodology
To choose the right research methodology for your dissertation or thesis, you need to consider three important factors. Based on these three factors, you can decide on your overarching approach – qualitative, quantitative or mixed methods. Once you’ve made that decision, you can flesh out the finer details of your methodology, such as the sampling, data collection methods and analysis techniques (we discuss these separately in other posts).
The three factors you need to consider are:
- The nature of your research aims, objectives and research questions
- The methodological approaches taken in the existing literature
- Practicalities and constraints
Let’s take a look at each of these.
Factor #1: The nature of your research
As I mentioned earlier, each type of research (and therefore, research methodology), whether qualitative, quantitative or mixed, has a different purpose and helps solve a different type of question. So, it’s logical that the key deciding factor in terms of which research methodology you adopt is the nature of your research aims, objectives and research questions.
But, what types of research exist?
Broadly speaking, research can fall into one of three categories:
- Exploratory – getting a better understanding of an issue and potentially developing a theory regarding it
- Confirmatory – confirming a potential theory or hypothesis by testing it empirically
- A mix of both – building a potential theory or hypothesis and then testing it
As a rule of thumb, exploratory research tends to adopt a qualitative approach, whereas confirmatory research tends to use quantitative methods. This isn’t set in stone, but it’s a very useful heuristic. Naturally then, research that combines a mix of both, or is seeking to develop a theory from the ground up and then test that theory, would utilize a mixed-methods approach.

Let’s look at an example in action.
If your research aims were to understand the perspectives of war veterans regarding certain political matters, you’d likely adopt a qualitative methodology, making use of interviews to collect data and one or more qualitative data analysis methods to make sense of the data.
If, on the other hand, your research aims involved testing a set of hypotheses regarding the link between political leaning and income levels, you’d likely adopt a quantitative methodology, using numbers-based data from a survey to measure the links between variables and/or constructs.
So, the first (and most important thing) thing you need to consider when deciding which methodological approach to use for your research project is the nature of your research aims, objectives and research questions. Specifically, you need to assess whether your research leans in an exploratory or confirmatory direction or involves a mix of both.
The importance of achieving solid alignment between these three factors and your methodology can’t be overstated. If they’re misaligned, you’re going to be forcing a square peg into a round hole. In other words, you’ll be using the wrong tool for the job, and your research will become a disjointed mess.
If your research is a mix of both exploratory and confirmatory, but you have a tight word count limit, you may need to consider trimming down the scope a little and focusing on one or the other. One methodology executed well has a far better chance of earning marks than a poorly executed mixed methods approach. So, don’t try to be a hero, unless there is a very strong underpinning logic.
Factor #2: The disciplinary norms
Choosing the right methodology for your research also involves looking at the approaches used by other researchers in the field, and studies with similar research aims and objectives to yours. Oftentimes, within a discipline, there is a common methodological approach (or set of approaches) used in studies. While this doesn’t mean you should follow the herd “just because”, you should at least consider these approaches and evaluate their merit within your context.
A major benefit of reviewing the research methodologies used by similar studies in your field is that you can often piggyback on the data collection techniques that other (more experienced) researchers have developed. For example, if you’re undertaking a quantitative study, you can often find tried and tested survey scales with high Cronbach’s alphas. These are usually included in the appendices of journal articles, so you don’t even have to contact the original authors. By using these, you’ll save a lot of time and ensure that your study stands on the proverbial “shoulders of giants” by using high-quality measurement instruments.
Of course, when reviewing existing literature, keep point #1 front of mind. In other words, your methodology needs to align with your research aims, objectives and questions. Don’t fall into the trap of adopting the methodological “norm” of other studies just because it’s popular. Only adopt that which is relevant to your research.
Factor #3: Practicalities
When choosing a research methodology, there will always be a tension between doing what’s theoretically best (i.e., the most scientifically rigorous research design) and doing what’s practical, given your constraints. This is the nature of doing research and there are always trade-offs, as with anything else.
But what constraints, you ask?
When you’re evaluating your methodological options, you need to consider the following constraints:
- Data access
- Time
- Money
- Equipment and software
- Your knowledge and skills
Let’s look at each of these.
Constraint #1: Data access
The first practical constraint you need to consider is your access to data. If you’re going to be undertaking primary research, you need to think critically about the sample of respondents you realistically have access to. For example, if you plan to use in-person interviews, you need to ask yourself how many people you’ll need to interview, whether they’ll be agreeable to being interviewed, where they’re located, and so on.
If you’re wanting to undertake a quantitative approach using surveys to collect data, you’ll need to consider how many responses you’ll require to achieve statistically significant results. For many statistical tests, a sample of a few hundred respondents is typically needed to develop convincing conclusions.
So, think carefully about what data you’ll need access to, how much data you’ll need and how you’ll collect it. The last thing you want is to spend a huge amount of time on your research only to find that you can’t get access to the required data.
I didn’t know if I was good enough.
See how Kelsee went from lost and confused to conquering her PhD.Constraint #2: Time
The next constraint is time. If you’re undertaking research as part of a PhD, you may have a fairly open-ended time limit, but this is unlikely to be the case for undergrad and Masters-level projects. So, pay attention to your timeline, as the data collection and analysis components of different methodologies have a major impact on time requirements. Also, keep in mind that these stages of the research often take a lot longer than originally anticipated.
Another practical implication of time limits is that it will directly impact which time horizon you can use – i.e. longitudinal vs cross-sectional. For example, if you’ve got a 6-month limit for your entire research project, it’s quite unlikely that you’ll be able to adopt a longitudinal time horizon.
Constraint #3: Money
As with so many things, money is another important constraint you’ll need to consider when deciding on your research methodology. While some research designs will cost near zero to execute, others may require a substantial budget.
Some of the costs that may arise include:
- Software costs – e.g. survey hosting services, analysis software, etc.
- Promotion costs – e.g. advertising a survey to attract respondents
- Incentive costs – e.g. providing a prize or cash payment incentive to attract respondents
- Equipment rental costs – e.g. recording equipment, lab equipment, etc.
- Travel costs
- Food & beverages
These are just a handful of costs that can creep into your research budget. Like most projects, the actual costs tend to be higher than the estimates, so be sure to err on the conservative side and expect the unexpected. It’s critically important that you’re honest with yourself about these costs, or you could end up getting stuck midway through your project because you’ve run out of money.

Constraint #4: Equipment & software
Another practical consideration is the hardware and/or software you’ll need in order to undertake your research. Of course, this variable will depend on the type of data you’re collecting and analysing. For example, you may need lab equipment to analyse substances, or you may need specific analysis software to analyse statistical data. So, be sure to think about what hardware and/or software you’ll need for each potential methodological approach, and whether you have access to these.
Constraint #5: Your knowledge and skillset
The final practical constraint is a big one. Naturally, the research process involves a lot of learning and development along the way, so you will accrue knowledge and skills as you progress. However, when considering your methodological options, you should still consider your current position on the ladder.
Some of the questions you should ask yourself are:
- Am I more of a “numbers person” or a “words person”?
- How much do I know about the analysis methods I’ll potentially use (e.g. statistical analysis)?
- How much do I know about the software and/or hardware that I’ll potentially use?
- How excited am I to learn new research skills and gain new knowledge?
- How much time do I have to learn the things I need to learn?
Answering these questions honestly will provide you with another set of criteria against which you can evaluate the research methodology options you’ve shortlisted.
So, as you can see, there is a wide range of practicalities and constraints that you need to take into account when you’re deciding on a research methodology. These practicalities create a tension between the “ideal” methodology and the methodology that you can realistically pull off. This is perfectly normal, and it’s your job to find the option that presents the best set of trade-offs.
Recap: Choosing a methodology
In this post, we’ve discussed how to go about choosing a research methodology. The three major deciding factors we looked at were:
- Nature of the research
- Research area norms
- Practicalities
If you have any questions, feel free to leave a comment below. If you’d like a helping hand with your research methodology, check out our 1-on-1 research coaching service.
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Very useful and informative especially for beginners
Nice article! I’m a beginner in the field of cybersecurity research. I am a Telecom and Network Engineer and Also aiming for PhD scholarship.
I find the article very informative especially for my decitation it has been helpful and an eye opener.
Hi I am Anna ,
I am a PHD candidate in the area of cyber security, maybe we can link up
The Examples shows by you, for sure they are really direct me and others to knows and practices the Research Design and prepration.
I found the post very informative and practical.
I struggle so much with designs of the research for sure!
I’m the process of constructing my research design and I want to know if the data analysis I plan to present in my thesis defense proposal possibly change especially after I gathered the data already.
Thank you so much this site is such a life saver. How I wish 1-1 coaching is available in our country but sadly it’s not.
Thank you very much for this inspiring and eye-opening post. I have a model for research methodology–CEC = Confirmatory, Explanatory, and Combination.
Please, I am working on a research topic, “Impact of PhET Simulations on the Performance and Interest of Junior Secondary School in Elementary Algebra: A case study of XYZ School.”
Please, I have decided to use a Quasi-Experimental Design and hoping to use mixed method for data analysis. Is this a correct decision.
I want to sincerely thank you for the invaluable guidance you provided in helping me choose the right research method. Your insights made a significant difference in my understanding and confidence moving forward. I truly appreciate your support!
Can you provide the bibliography for this article?