Quantitative Research

Quantitative research focuses on collecting and analysing numerical data to quantify behaviours, opinions, or variables and generalise findings from a larger population. It is structured and objective, often used to test hypotheses or examine relationships.

Key Characteristics of Quantitative Research:

Data Type: Numerical (e.g., percentages, frequencies, etc.).

Purpose: To measure phenomena, test theories, and identify statistical relationships.

Methods: Surveys with closed-ended questions, experiments, and statistical modelling.

Sample Size: Typically large and randomly selected.

Analysis: Uses statistical tools like regression and hypothesis testing.

Outcome: Produces quantifiable and generalizable findings.

Qualitative Research

Qualitative research is exploratory and seeks to understand the meaning behind human behaviour and social phenomena. It focuses on depth and context, typically used when knowledge of a topic is limited.

Key Characteristics of Qualitative Research:

Data Type: Non-numerical (e.g., narratives, observations).

Purpose: To explore how and why certain behaviours or experiences occur.

Methods: In-depth interviews, focus groups, and case studies.

Sample Size: Smaller and purposively selected.

Analysis: Involves thematic or content analysis.

Outcome: Provides deep, contextual insights.

Choosing Between the Two:

Quantitative research is ideal for measuring variables and generalising findings. Qualitative research is best for understanding complex processes and lived experiences.

Note: Researchers often use a mixed-methods approach to combine the strengths of both types.

Quantitative Research and Qualitative Research are two fundamental scientific approaches to investigation, differing in data type, methodology, and objectives.

1). Quantitative Research: Quantitative research involves measuring and counting. Think of it as the detective who loves hard evidence, numbers, stats, and graphs are its best friends. It’s perfect for answering “how many?” or “how much?” questions.

Example: Imagine a company wants to know if their new app boosts user engagement. They run a survey with 1,000 users, asking them to rate their experience on a scale of 1-10. The result? A tidy 8.5 average score, with 70% of users logging in daily. But the problem is that qualitative research might miss the why behind the numbers. Why did 30% of users skip the app?

2). Qualitative Research: Qualitative research is the curious friend who wants to know “why?” and “how?”. It dives deep into experiences, feelings, and motivations, using words, images, videos, etc.

Example: Suppose the same company sits down with 10 users for a heart-to-heart interview (conversation). One user says, “The app’s fun, but the notifications feel spammy.”Another shares, “I love the design. It’s like a digital hug!” These stories reveal why users engage (or don’t).

Head-to-Head: Quick Comparison:

Qualitative Research

• Focus: Exploring ideas or formulating hypotheses/theories
• Analysis: Summarizing, categorizing, interpreting
• Expressed in: Words
• Sample: Few respondents
• 'Questions: Open-ended
• 'Characterized by: Understanding, context, complexity, subjectivity

Quantitative Research

• Focus: Testing hypotheses or theories
• Analysis: Math and statistical analysis
• Expressed in: Numbers, graphs, tables, fewer words
• Sample: Many respondents
• Questions: Close-ended or multiple choice
• Characterized by: Testing, measurement, objectivity, replicability

This question has been asked a number of times here, so I suggest that you do a search in the "Questions" menu at the top of the page. That way, you should find more thoughtful answers, rather than uncredited reprints from an AI.

Quantitative research relies on structured questionnaires, producing metric data that can be analyzed statistically for hypothesis testing.

In contrast, qualitative research uses unstructured questionnaires or interviews, yielding non-metric data that is interpreted through thematic or content analysis.

An anecdote (which i was told by the involved researcher 20 years ago, but I will not name them since I likely bungled many of the impotant details, but the example still works even if allegorical.)

A foreign researcher moved to the US in the 80s with an interest in studying orgnanized crime using qualitative (in this case ethnographic) methods. He was fortunate enough to find renowned sociologist&criminologist to serve as his adviser who was very well versed in classical criminological theory but especially in age effect, cohort studies and the like. so more quantitatively oriented.

ethnographic work in particular (but lots of qualitiative methods, all the good ones I might say) work on the basis of "saturation" - you aren't looking to compare groups of individuals, rather you're looking for unique or interesting phenomena, behavior, narratives, whatever, until you reach a point where you justifiably believe that you aren't really finding out much that is "new" to you, when you're comfortable in thinking that just more one interview or one more day in the field isn't likely to radically change your interpretations. ethnographers almost never say in the beginning how many field visits they would like to do unless they are forced, because you never know how many you will need to understand what is going on.

in this case, the advisor continued to talk about and evaluate the project in quantiative terms, referring to set numbers of "observations" and suggesting that more were needed to make the analysis significant etc. the researcher continued fieldwork for (at least) 3 years, hanging out with gangsters mostly in bars and listening to their stories about crime and everyday life and everything in between, all the while being told by his advisor "you need more cases" in order to "compare" - of course the researcher wasn't trying to statistically compare anything, he was looking to see how people involved in criminal organizations made sense of their activities, how (semi)formal hierarchies were expressed in everyday interactions, how criminal agents who were publicly known as "gang members" interacted with members of the public, things like that.

one day, the advisor gets a call from the FBI, who has been covertly monitoring the organized crime group and is very aware of - and concerned about - the research hanging around with some of its members. they ask the advisor how much longer the researcher will need to be there, and he says "until he has collected enough observations to be able to analyze the data correctly." The FBI says "he has enough data, now he needs to start writing his dissertation."

So this is what I've told my students is a major difference between quantitative / positivistic research and qualitative / inteprerative research - in quantitative work, you arbitrarily decide in advance how much data you need and only look at it when you're gotten all the results. in qualitative work, you keep going over and learning from data throughout, learning to ask better questions, observe better, understand more, right up until the point where the FBI forbids you to collect more data.