Why is it important for a student researcher to know the characteristics of quantitative research How are these different from the qualitative method?

Qualitative research studies can provide you with details about human behavior, emotion, and personality characteristics that quantitative studies cannot match.

Data from qualitative studies describes the qualities or characteristics of something. You cannot easily reduce these descriptions to numbers—as you can the findings from quantitative research; though you can achieve this through an encoding process. Qualitative research studies can provide you with details about human behavior, emotion, and personality characteristics that quantitative studies cannot match. Qualitative data includes information about user behaviors, needs, desires, routines, use cases, and a variety of other information that is essential in designing a product that will actually fit into a user’s life.

Table of Contents Show

Using Quantitative and Qualitative Research Together
Quantitative Research
Sources of Quantitative Data
Analysing Quantitative Data
Qualitative Research
Sources of Qualitative Data
Analysing Qualitative Data
It’s your research…

While quantitative research requires the standardization of data collection to allow statistical comparison, qualitative research requires flexibility, allowing you to respond to user data as it emerges during a session. Thus, qualitative research usually takes the form of either some form of naturalistic observation such as ethnography or structured interviews. In this case, a researcher must observe and document behaviors, opinions, patterns, needs, pain points, and other types of information without yet fully understanding what data will be meaningful.

Following data collection, rather than performing a statistical analysis, researchers look for trends in the data. When it comes to identifying trends, researchers look for statements that are identical across different research participants. The rule of thumb is that hearing a statement from just one participant is an anecdote; from two, a coincidence; and hearing it from three makes it a trend. The trends that you identify can then guide product development, business decisions, and marketing strategies.

Because you cannot subject these trends to statistical analysis, you cannot validate trends by calculating a p-value or an effect size—as you could validate quantitative data—so you must employ them with care. Plus, you should continually verify such data through an ongoing qualitative research program.

With enough time and budget, you can engage in an activity called behavioral coding, which involves assigning numeric identifiers to qualitative behavior, thus transforming them into quantitative data that you can then subject to statistical analysis. In addition to the analyses we described earlier, behavioral coding lets you perform a variety of additional analyses such as lag sequential analysis, a statistical test that identifies sequences of behavior—for example, those for Web site navigation or task workflows.?However, applying behavioral coding to your observations is extremely time consuming and expensive. Plus, typically, only very highly trained researchers are qualified to encode behavior. Thus, this approach tends to be cost prohibitive.

Additionally, because it is not possible to automate qualitative-data collection as effectively as you can automate quantitative-data collection, it is usually extremely time consuming and expensive to gather large amounts of data, as would be typical for quantitative research studies. Therefore, it is usual to perform qualitative research with only 6 to 12 participants, while for quantitative research, it’s common for there to be hundreds or even thousands of participants. As a result, qualitative research tends to have less statistical power than quantitative research when it comes to discovering and verifying trends.

Using Quantitative and Qualitative Research Together

While quantitative and qualitative research approaches each have their strengths and weaknesses, they can be extremely effective in combination with one another.

While quantitative and qualitative research approaches each have their strengths and weaknesses, they can be extremely effective in combination with one another. You can use qualitative research to identify the factors that affect the areas under investigation, then use that information to devise quantitative research that assesses how these factors would affect user preferences. To continue our earlier example regarding display preferences: if qualitative research had identified display type—such as TV, computer monitor, or mobile phone display—the researchers could have used that information to construct quantitative research that would let them determine how these variables might affect user preferences. At the same time, you can build trends that you’ve identified through quantitative research into qualitative data-collection methods and, thus verify the trends.

While this might sound contrary to what we’ve described above, the approach is actually quite straightforward. An example of a qualitative trend might be that younger users prefer autostereoscopic displays only on mobile devices, while older users prefer traditional displays on all devices. You may have discovered this by asking an open-ended, qualitative question along these lines: “What do you think of 3D displays?” This question would have opened up a discussion about 3D displays that uncovered a difference between stereoscopic displays, autostereoscopic displays, and traditional displays. In a subsequent quantitative study, you could address these factors through a series of questions such as: “Rate your level of preference for a traditional 3D display—which requires your using 3D glasses—on a mobile device,” with options ranging from strongly prefer to strongly dislike. An automated system assigns a numeric value to whatever option a participant chooses, allowing a researcher to quickly gather and analyze large amounts of data.

Conclusion

When setting out to perform user research, … it is important to understand the different applications of these two approaches to research.

When setting out to perform user research—whether performing the research yourself or assigning it to an employee or a consultant—it is important to understand the different applications of these two approaches to research. This understanding can help you to choose the appropriate research approach yourself, understand why a researcher has chosen a particular approach, or communicate with researchers or stakeholders about a research approach and your overarching research strategy. The examples we’ve provided here provide just a small sampling of the many ways in which can analyze and employ qualitative and quantitative data. In what other ways do you use and combine qualitative and quantitative research?

Quantitative Research

Quantitative research is perhaps the simpler to define and identify.

The data produced are always numerical, and they are analysed using mathematical and statistical methods. If there are no numbers involved, then it’s not quantitative research.

Some phenomena obviously lend themselves to quantitative analysis because they are already available as numbers. Examples include changes in achievement at various stages of education, or the increase in number of senior managers holding management degrees. However, even phenomena that are not obviously numerical in nature can be examined using quantitative methods.

Example: turning opinions into numbers

If you wish to carry out statistical analysis of the opinions of a group of people about a particular issue or element of their lives, you can ask them to express their relative agreement with statements and answer on a five- or seven-point scale, where 1 is strongly disagree, 2 is disagree, 3 is neutral, 4 is agree and 5 is strongly agree (the seven-point scale also has slightly agree/disagree).

Such scales are called Likert scales, and enable statements of opinion to be directly translated into numerical data.

The development of Likert scales and similar techniques mean that most phenomena can be studied using quantitative techniques.

This is particularly useful if you are in an environment where numbers are highly valued and numerical data is considered the ‘gold standard’.

However, it is important to note that quantitative methods are not necessarily the most suitable methods for investigation. They are unlikely to be very helpful when you want to understand the detailed reasons for particular behaviour in depth. It is also possible that assigning numbers to fairly abstract constructs such as personal opinions risks making them spuriously precise.

Sources of Quantitative Data

The most common sources of quantitative data include:

Surveys, whether conducted online, by phone or in person. These rely on the same questions being asked in the same way to a large number of people;
Observations, which may either involve counting the number of times that a particular phenomenon occurs, such as how often a particular word is used in interviews, or coding observational data to translate it into numbers; and
Secondary data, such as company accounts.

Our pages on Survey Design and Observational Research provide more information about these techniques.

Analysing Quantitative Data

There are a wide range of statistical techniques available to analyse quantitative data, from simple graphs to show the data through tests of correlations between two or more items, to statistical significance. Other techniques include cluster analysis, useful for identifying relationships between groups of subjects where there is no obvious hypothesis, and hypothesis testing, to identify whether there are genuine differences between groups.

Our page Statistical Analysis provides more information about some of the simpler statistical techniques.

Qualitative Research

It often involves words or language, but may also use pictures or photographs and observations.

Almost any phenomenon can be examined in a qualitative way, and it is often the preferred method of investigation in the UK and the rest of Europe; US studies tend to use quantitative methods, although this distinction is by no means absolute.

Qualitative analysis results in rich data that gives an in-depth picture and it is particularly useful for exploring how and why things have happened.

However, there are some pitfalls to qualitative research, such as:

If respondents do not see a value for them in the research, they may provide inaccurate or false information. They may also say what they think the researcher wishes to hear. Qualitative researchers therefore need to take the time to build relationships with their research subjects and always be aware of this potential.
Although ethics are an issue for any type of research, there may be particular difficulties with qualitative research because the researcher may be party to confidential information. It is important always to bear in mind that you must do no harm to your research subjects.
It is generally harder for qualitative researchers to remain apart from their work. By the nature of their study, they are involved with people. It is therefore helpful to develop habits of reflecting on your part in the work and how this may affect the research. See our page on Reflective Practice for more.

Sources of Qualitative Data

Although qualitative data is much more general than quantitative, there are still a number of common techniques for gathering it. These include:

Interviews, which may be structured, semi-structured or unstructured;
Focus groups, which involve multiple participants discussing an issue;
‘Postcards’, or small-scale written questionnaires that ask, for example, three or four focused questions of participants but allow them space to write in their own words;
Secondary data, including diaries, written accounts of past events, and company reports; and
Observations, which may be on site, or under ‘laboratory conditions’, for example, where participants are asked to role-play a situation to show what they might do.

Our pages on Interviews for Research, Focus Groups and Observational Research provide more information about these techniques.

Analysing Qualitative Data

Because qualitative data are drawn from a wide variety of sources, they can be radically different in scope.

There are, therefore, a wide variety of methods for analysing them, many of which involve structuring and coding the data into groups and themes. There are also a variety of computer packages to support qualitative data analysis. The best way to work out which ones are right for your research is to discuss it with academic colleagues and your supervisor.

Our page Analysing Qualitative Data provides more information about some of the most common methods.

It’s your research…

Finally, it is important to say that there is no right and wrong answer to which methods you choose.

Sometimes you may wish to use one single method, whether quantitative or qualitative, and sometimes you may want to use several, whether all one type or a mixture. It is your research and only you can decide which methods will suit both your research questions and your skills, even though you may wish to seek advice from others.