Qualitative and quantitative research

One of the main categories used to classify information is whether it is quantitative or qualitative. In many situations, researchers combine the two methods to arrive at ‘mixed-methods research’. In the discussion below, we look at the differences between the two types of data and the situations in which these two types of data can be usefully sourced.

What is qualitative data?

Qualitative data involves a descriptive judgment using concept words instead of numbers. Gender, country name, animal species, emotional state, feelings, and opinions are examples of qualitative information.

What is quantitative data?

Quantitative data involves a measurable quantity, that is numbers are used. Some examples are temperature, time, the amount spent, number of units bought and hours spent on the computer.

Table 2: Differences between qualitative and quantitative research

Which type of data to collect?

Generally, the choice of data is directly linked to the research question being investigated. Below are some general guidelines on the kind of information produced with the help of different methods:

Qualitative research: is mostly used to understand a phenomenon, such as customers’ experiences at a retail outlet. For example, a researcher may choose to interview a number of shoppers by asking them open text questions, e.g. “Did you face any problems in this store today?” or “Did you enjoy shopping here?”  Such questions may encourage customers to chat freely and highlight any issues (e.g., parking issues, rude employees, or poor ventilation) which at times cannot be identified through a quantitative survey alone.

Quantitative research: is useful in estimating overall frequencies or numbers. For example, how many people visited the restaurant this evening? It is also used to test or confirm a hypothesis – that is, a manager’s educated guess. For example, a teacher may survey his class, asking them, “On a scale of 1-5, how bored are you in this class? (with 1 = not at all bored and 5 = very bored)” By analysing the numerical responses, the teacher may conclude that his guess is accurate about student boredom as the average class score is 4.5.

Mixed method: as the name suggests makes use of both qualitative and quantitative research. A researcher may use qualitative research to better understand a phenomenon, and then use quantitative research to statistically test it. For instance, while interviewing customers a manager may find that some of them are complaining about parking issues. In order to understand how widespread this complaint is the manager may initiate a quick, short survey to find out how many customers require parking at the store’s premises.

Alternatively, a researcher may stumble upon an unexpected finding via a survey (such as very low scores for customer service in a Sydney store). Interviews can be conducted to find out the reason for customer dissatisfaction. The store manager may find it useful to initiate conversations with customers to better understand the poor scores.

Limitations of qualitative research

• Subjectivity: Qualitative data is written or spoken and requires careful interpretation. In some situations, the researcher may not be familiar with the participants’ language. Analysing the data may require time and help from someone who is from the community and fluent at conversing in the relevant language. Even when language is not an issue, interpretation of textual content can be done differently by different researchers.
• A smaller number of participants: Interviews and focus groups can only be conducted with a smaller group of participants. While surveys can be sent out and completed by hundreds (or thousands) of people, it is simply not possible to undertake interviews with the same number of informants. Thus, any findings from qualitative research need to be generalized with care.
• Bias: The researcher or analyst plays a much bigger role in the interpretation of qualitative information than simply running a statistical test. At times, the interviewee may make a very important point but mention it only once – and that too, casually. While it is easy for a novice researcher to completely miss such information, a more experienced researcher would make a note of it.

Limitations of quantitative research

• Large sample size: In order for quantitative research to be statistically valid, a large number of respondents must be included in the survey. While there is no exact figure which is seen as being accurate, the larger the sample size the greater would be the confidence in the findings. This requires a large number of resources in terms of skills at designing the research project, time, and money.
• Pre-determined questions: When a large survey has to be undertaken, all questions in the survey need to be pre-determined. In case the researcher wants to include any additional questions, it is not possible to do it in a short period of time.