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Qualitative vs. Quantitative Research

To understand the difference between qualitative and quantitative research, you need to define three keywords: quality, quantity, and research. Quality is an uncountable level of excellence or an attribute that differentiates things or people, while quantity is a generic term used fundamentally to refer to the measurement of something. Research refers to the systematic study of or investigation into a source or material to establish facts or draw conclusions. The results of any research can be qualitative, quantitative, or both.

Therefore, qualitative research investigates materials or sources to come up with their attributes or descriptions. Quantitative research, on the other hand, is research done focusing on numbers and mathematical calculations.

What Is the Difference Between Qualitative and Quantitative Research?

There are some key differences between qualitative and quantitative research, mainly because their results are so different. Some fields prefer one type of research to the other, depending on what they were looking for. For example, scientists may prefer quantitative data, while sociologists may prefer qualitative data. Here are seven differences between the two:

  1. Quantitative data is collected and analyzed using statistics, while qualitative data is collected through observation.
  2. Quantitative data yields conclusive results, while qualitative data is more exploratory.
  3. Quantitative data is numerical in form, while qualitative data is more descriptive.
  4. Quantitative data is objective, meaning it's based on facts, while qualitative data is more subjective and is therefore subject to interpretation and influence by feelings or opinions.
  5. Quantitative data is measurable involving lengths, prices, amounts, etc. while qualitative data isn't. Qualitative data uses descriptive words and adjectives to refer to data.
  6. Quantitative data is structured for analysis purposes, while quantitative data is unstructured.
  7. People consider quantitative data to be more reliable and objective than qualitative data.

Here is a tabular summary of qualitative vs. quantitative research based on the data:

Qualitative Data
Quantitative Data

Collected through observation

(Delpit, 2019)

The research methodology is exploratory

The research methodology is conclusive

Data more descriptive

Data in numerical form

Data is subjective

Data is objective

Data isn’t measurable

Data is measurable

Data is unstructured

Data is structured

Data not considered more reliable and objective

Data considered as reliable and objective

What Is Qualitative Research?

As has been highlighted, qualitative research yields more textual data, i.e., that is non-numerical, while quantitative data yields numerical data or data that can be converted into numbers. Qualitative data is useful in the exploratory stages of any project, such as in the pilot stage of a project. It gives rise to the underlying thoughts, opinions, trends, and motivations. The qualitative analysis results can either be considered to be conclusive or serve as the basis for further research.

Qualitative Research Techniques

Qualitative research techniques make use of both structured and unstructured techniques. Some examples of qualitative research methods are individual research interviews, focus group discussions, and participant observation. Iterative study designs can be applied whereby the questions asked and the data collected change depending on what is learned.

Analysis

Because qualitative data is typically presented in words that contain in-depth information, data analysis involves reading numerous amounts of transcripts. The goal of qualitative data analysis is to uncover similarities and differences in the data. This analysis leads to the development of themes from the data and coming up with categories. In the past, qualitative data analysis was a tedious process involving many people and highlighting things in different colors, but more and more software are being coded to aid the process.

Features

Here are the features that make qualitative research what it is:

Approach - The qualitative researcher is concerned with understanding the phenomenon under study through inductive reasoning. Inductive reasoning refers to the derivation of general principles from specific observations.

Goal – Qualitative research focuses on the depth of knowledge (getting in-depth knowledge on a particular subject) and consequently generating a hypothesis.

Setting – Qualitative research is collected in a naturalistic environment.

Sampling – Qualitative research uses purposive sampling. That means the participants are selected because of their ability to illuminate a particular matter.

Data collection – Data is collected using focus groups, observation, and interviews.

Data analysis – Qualitative data analysis is iterative.

Examples of Qualitative Research Topics

Here are some topics that would require qualitative research:

  • What are the effects of underage drinking on the participants in the future?
  • Which branch of the government is more important?
  • What are the results of sleep deprivation on drivers?
  • What is the perfect age a person should be allowed to drink?

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Uses

Qualitative data can be used to come up with themes, similarities, and differences that come up in the data. Sometimes, it's used to generate a hypothesis that will then undergo quantitative research.

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What Is Quantitative Research?

As was mentioned, quantitative research deals with numbers and figures. Quantitative research is used to quantify attitudes, behavior, motivations, opinions, and other variables. The goal of quantitative research is to support or refute a hypothesis. The results can then be contextualized to the broader population.

Quantitative Research Techniques

Quantitative research methods are explicit on what is to be measured and how it is to be measured. For this reason, quantitative data collection is more structured than qualitative data. They typically use surveys, questionnaires, and structured interviews to collect data. The data collected should be generalized to the general population without significant discrepancies. Surveys are classified into two based on time:

  • Cross-sectional studies – These surveys allow the researchers to come up with conclusions on a specific subject at a particular time. The surveys are conducted across the target population at that particular time, so the results match the time. Based on their nature, cross-sectional studies study new people each time they are carried out.
  • Longitudinal studies – These surveys are great for coming up with trends in the research subject. They are conducted over a considerable period. For example, a study of people's behavioral trends during Christmas time would need the researchers to conduct several surveys at Christmas time over several years to be able to project the data better. For consistency, longitudinal studies study the same set of people throughout their study.

Analysis

The data collected from quantitative research is analyzed to formulate facts and uncover patterns that can then be generalized to the broader population. There are many quantitative data analysis methods. Here are five examples:

  1. Cross-tabulation – This is the most widely used method. The data is inputted into a tabular form then analyzed. Information is then inferred from the data, whether it is connected or mutually exclusive.
  2. Trend analysis – This method is excellent for analyzing data from longitudinal studies. It is used to track and note changes in the data over time, particularly when one variable is unchanging.
  3. Gap analysis – This method uses a side-by-side matrix to present quantitative data. An analysis is then done to measure the difference between the actual performance and the expected performance. It measures the gap in the performance and what can be done to bridge this gap. 
  4. Text analysis – This is an advanced data analysis method that can help quantify qualitative data. It uses intelligent tools that make sense of and quantify open-ended and qualitative data into understandable quantitative data.
  5. MaxDiff analysis – This analysis method is used to gauge customer preferences for their products and what parameters rank higher than the others. This method is also called the 'best-worst' method.

Features

Here are the features that make quantitative analysis what it is:

Approach – The researcher is concerned with generalization, prediction, outcomes, and causal relationships. He derives these things from the data using deductive reasoning.

Goal – The goal of quantitative research is to discover the breadth of new knowledge of the subject under study. The other purpose is to test a hypothesis.

Setting – Quantitative research is conducted in a controlled environment, such as a clinical or laboratory setting.

Sampling – Quantitative research typically uses random sampling. It usually has larger sample sizes than qualitative research samples.

Data collection – Quantitative surveys and structured interviews are prevalent in quantitative research.

Data analysis - Statistical tests are done to come up with conclusions in quantitative research.

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Examples of Quantitative Research Topics

Here are examples of issues that would benefit from quantitative research:

research topics

Uses

Quantitative research is used to uncover the relationship between variables. If the data collected is to be used to make decisions, quantitative data forms a more solid basis than qualitative data.

Here is a side by side comparison of the qualitative vs. quantitative research features:

Feature
Qualitative Research
Quantitative Research

Approach

Inductive approach

Deductive approach

Goal

Depth of knowledge
Generate hypothesis

Breadth of knowledge
Test hypothesis

Setting

Natural

Experimental

Sampling

Purposeful sampling

Random sampling

Data collection

Interviews, focus groups, and participant observation, etc.

Surveys and structured interviews

Data analysis

Iterative interpretation

Statistical tests and modeling

Qualitative and Quantitative Research Data Collection Methods

The two methods need different types of data, and therefore their research methods vary. This section will analyze some of the research methods used by each type of research.

Qualitative Data Collection Methods

Qualitative data must be richly detailed so that you have information to work with, to analyze. Some qualitative data collection methods include:

  • Open-ended survey questions – When a question is open-ended, it means that the respondent's response is not limited to a set of options. Instead, after the question is a text box that allows the respondent to give their answers based on what they know, feel, or understand.
  • Expert opinions – This kind of research method involves selecting your sample from a specialized group of people in the field both within and out of the organization. Because the respondents are experts, the information is deemed to be of high quality.
  • Interviews – An interview is a one-on-one conversation between the researcher and the respondents. They can be face to face, meet virtually, or communicate through mobile, but the researcher has to correspond directly with the subject. These types of surveys are great because the researcher can seek further information that was not in the set questions, but that would provide better insight into the subject.
  • Case studies – This is an in-depth study of a group, an organization, or an individual generally over some time. Usually, several methods are combined in the study, and several sources are used to find information.
  • Focus group discussions – When conducting a focus group discussion (FGD), you bring together a group of people who have similar experiences or backgrounds to discuss a specific topic. They are guided by a moderator who will introduce the topic, encourage participation, and guide the discussion. The goal is to uncover the opinions and ideas of these people and how they vary.
  • Observational research – This research method has the researchers observe the subjects' behavior in their natural environment. It comes in response to findings that some people lie during interviews and surveys for various reasons, including to make them look good to the researchers. There are three types of observational research. They are:

 1) Controlled observation – The subjects under study are observed from within a controlled environment, such as a psych lab. In a controlled environment, the researchers can control some variables such as which participants will take place in the study, the place, time, and circumstances surrounding the research.

 2) Naturalistic observation – Here, the participant's behavior is studied in their natural environment.

 3) Participant observation – This is similar to the naturalistic observation in that the participants are observed in their natural environment. The difference is that the researchers insert themselves into the participants' environment.

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Quantitative Data Collection Methods

For quantitative data, certain variables have to be measured and later analyzed. For this reason, some data collection methods may be the same but be conducted differently. Three essential quantitative data collection methods are:

  • Using closed-ended questions – unlike open-ended questions, participants' responses on closed-ended surveys and interviews are limited.

They can measure degree with responses such as:

  • Extremely likely
  • Very likely
  • Somewhat likely
  • Not so likely
  • Not at all likely

Closed-ended questions can measure time using options such as:

  • Always
  • Most of the time
  • About half the time
  • Once in a while
  • Never

A closed-ended survey can also have options such as yes, no, and maybe.

The point of closed-ended questions is to be able to quantify the responses quickly.

  • Observations – Quantitative data can be derived from observation, mainly controlled observation. However, even other types of observation methods can be used. The difference between qualitative research and quantitative research is that the researchers in quantitative research may be recording the number of times participants make a particular decision or perform a specific action to have quantitative data.
  • Experiments – In experiments, some variables are controlled or altered. The main goal with experiments is to establish cause and effect relationships.

Mixed Methods

Mixed methods are becoming more common as time goes by. This is because researchers understand that by selecting one type of research over the other, they miss out on the valuable insights they would gain from the method they did not use. They, therefore, use both research methods for their projects and have reports that incorporate both types of data.

When to Use Qualitative vs. Quantitative Research

The type of research you chose depends on a few factors. The table below, put together by the experts from our professional paper writing service, highlights the factors and what kind of research to do in each case:

Factor
Type of Research

Generate a hypothesis or understand something

Qualitative

Test or confirm a hypothesis

Quantitative

Open-ended questions

Qualitative data

Closed-ended questions

Quantitative data

Experimental research

Quantitative data

Correlational research

Quantitative data

Descriptive research

Qualitative data


Other factors that determine what type of research to conduct include the sample size, how much money and time you have, and the availability of data, among others.

To Sum Up

When you are researching to learn something, you have to determine what type of research will yield the best results for you. This means you have to understand the difference between qualitative and quantitative research and how they are conducted. The results you want will also help you decide what method to go to. If you have the resources, mixed research will give you the best of both worlds.

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