It is used to quantify attitudes, opinions, behaviors, and other defined variables — and generalize results from a larger sample population. Quantitative Research uses measurable data to formulate facts and uncover patterns in research. Quantitative data collection methods are much more structured than Qualitative data collection methods. Quantitative data collection methods include various forms of surveys — online surveys, paper surveys , mobile surveys and kiosk surveys, face-to-face interviews, telephone interviews, longitudinal studies, website interceptors, online polls, and systematic observations.
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While defining quantitative and qualitative research based on their uses and purposes may be considered a practical approach for researcher, the difference actually lies on their roots: Procedures, designs, concepts, purposes and uses emanate from there. Example on qualitative research referring to quality where problems are answered without generally focusing on quantity, are descriptions in words coming form interviews, discussions or observations.
However when words are translated to quantity in order to describe or to generalize, then the research is now called quantitatitive research. The bottom lines are the questions: Many thanks for giving me clear understanding around the differences between the qualitative and quantative research.
Thanks a millions time. I was struggling to get an idea of how to approach the definitions. In fact I was even hesitating to answer the questions confidently.
Thanks for the distinct comparison between qualitative and quantitative Research, very very helpful. Thank you for making me to understand the difference between qualitative Research and quantitative research. This pin never expires. Select an expiration date. About Us Contact Us. Search Community Search Community. An Overview of Quantitative Research This modules provides a basic overview of quantitative research, including its key characteristics and advantages.
Describe the uses of quantitative research design. Provide examples of when quantitative research methodology should be used. Discuss the strengths and weaknesses of quantitative research. The data collected is numeric, allowing for collection of data from a large sample size. Statistical analysis allows for greater objectivity when reviewing results and therefore, results are independent of the researcher.
Numerical results can be displayed in graphs, charts, tables and other formats that allow for better interpretation. Data analysis is less time-consuming and can often be done using statistical software. Results can be generalized if the data are based on random samples and the sample size was sufficient. Data collection methods can be relatively quick, depending on the type of data being collected.
Numerical quantitative data may be viewed as more credible and reliable, especially to policy makers, decision makers, and administrators. How often do college students between the ages of access Facebook? In participant observation  researchers typically become members of a culture, group, or setting, and adopt roles to conform to that setting.
In doing so, the aim is for the researcher to gain a closer insight into the culture's practices, motivations, and emotions.
It is argued that the researchers' ability to understand the experiences of the culture may be inhibited if they observe without participating. The data that is obtained is streamlined texts of thousands of pages in length to a definite theme or pattern, or representation of a theory or systemic issue or approach.
This step in a theoretical analysis or data analytic technique is further worked on e. An alternative research hypothesis is generated which finally provides the basis of the research statement for continuing work in the fields.
Some distinctive qualitative methods are the use of focus groups and key informant interviews , the latter often identified through sophisticated and sometimes, elitist, snowballing techniques. The focus group technique e. The research then must be "written up" into a report, book chapter, journal paper, thesis or dissertation, using descriptions, quotes from participants, charts and tables to demonstrate the trustworthiness of the study findings.
In qualitative research, the idea of recursivity is expressed in terms of the nature of its research procedures, which may be contrasted with experimental forms of research design. From the experimental perspective, its major stages of research data collection, data analysis, discussion of the data in context of the literature, and drawing conclusions should be each undertaken once or at most a small number of times in a research study.
In qualitative research however, all of the four stages above may be undertaken repeatedly until one or more specific stopping conditions are met, reflecting a nonstatic attitude to the planning and design of research activities. An example of this dynamicism might be when the qualitative researcher unexpectedly changes their research focus or design midway through a research study, based on their 1st interim data analysis, and then makes further unplanned changes again based on a 2nd interim data analysis; this would be a terrible thing to do from the perspective of an predefined experimental study of the same thing.
Qualitative researchers would argue that their recursivity in developing the relevant evidence and reasoning, enables the researcher to be more open to unexpected results, more open to the potential of building new constructs, and the possibility of integrating them with the explanations developed continuously throughout a study.
Qualitative methods are often part of survey methodology, including telephone surveys and consumer satisfaction surveys. In fields that study households, a much debated topic is whether interviews should be conducted individually or collectively e. One traditional and specialized form of qualitative research is called cognitive testing or pilot testing which is used in the development of quantitative survey items. Survey items are piloted on study participants to test the reliability and validity of the items.
This approach is similar to psychological testing using an intelligence test like the WAIS Wechsler Adult Intelligence Survey in which the interviewer records "qualitative" i. Qualitative research is often useful in a sociological lens. Although often ignored, qualitative research is of great value to sociological studies that can shed light on the intricacies in the functionality of society and human interaction. There are several different research approaches, or research designs, that qualitative researchers use.
As a form of qualitative inquiry, students of interpretive inquiry interpretivists often disagree with the idea of theory-free observation or knowledge. Whilst this crucial philosophical realization is also held by researchers in other fields, interpretivists are often the most aggressive in taking this philosophical realization to its logical conclusions.
For example, an interpretivist researcher might believe in the existence of an objective reality 'out there', but argue that the social and educational reality we act on the basis of never allows a single human subject to directly access the reality 'out there' in reality this is a view shared by constructivist philosophies.
To researchers outside the qualitative research field, the most common analysis of qualitative data is often perceived to be observer impression. That is, expert or bystander observers examine the data, interpret it via forming an impression and report their impression in a structured and sometimes quantitative form. In general, coding refers to the act of associating meaningful ideas with the data of interest. In the context of qualitative research, interpretative aspects of the coding process are often explicitly recognized, articulated, and celebrated; producing specific words or short phrases believed to be useful abstractions over the data.
As an act of sense making, most coding requires the qualitative analyst to read the data and demarcate segments within it, which may be done at multiple and different times throughout the data analysis process.
In contrast with more quantitative forms of coding, mathematical ideas and forms are usually under-developed in a 'pure' qualitative data analysis.
When coding is complete, the analyst may prepare reports via a mix of: Some qualitative data that is highly structured e. Quantitative analysis based on codes from statistical theory is typically the capstone analytical step for this type of qualitative data. Contemporary qualitative data analyses are often supported by computer programs termed Computer Assisted Qualitative Data Analysis Software used with or without the detailed hand coding and labeling of the past decades.
These programs do not supplant the interpretive nature of coding, but rather are aimed at enhancing analysts' efficiency at applying, retrieving, and storing the codes generated from reading the data. Many programs enhance efficiency in editing and revision of codes, which allow for more effective work sharing, peer review, recursive examination of data, and analysis of large datasets.
A frequent criticism of quantitative coding approaches is against the transformation of qualitative data into predefined nomothetic data structures, underpinned by 'objective properties '; the variety, richness, and individual characteristics of the qualitative data is argued to be largely omitted from such data coding processes, rendering the original collection of qualitative data somewhat pointless.
To defend against the criticism of too much subjective variability in the categories and relationships identified from data, qualitative analysts respond by thoroughly articulating their definitions of codes and linking those codes soundly to the underlying data, thereby preserving some of the richness that might be absent from a mere list of codes, whilst satisfying the need for repeatable procedure held by experimentally oriented researchers.
As defined by Leshan ,  this is a method of qualitative data analysis where qualitative datasets are analyzed without coding. A common method here is recursive abstraction, where datasets are summarized; those summaries are therefore furthered into summary and so on. The end result is a more compact summary that would have been difficult to accurately discern without the preceding steps of distillation.
A frequent criticism of recursive abstraction is that the final conclusions are several times removed from the underlying data.
While it is true that poor initial summaries will certainly yield an inaccurate final report, qualitative analysts can respond to this criticism. They do so, like those using coding method, by documenting the reasoning behind each summary step, citing examples from the data where statements were included and where statements were excluded from the intermediate summary.
Some data analysis techniques, often referred to as the tedious, hard work of research studies similar to field notes, rely on using computers to scan and reduce large sets of qualitative data.
At their most basic level, numerical coding relies on counting words, phrases, or coincidences of tokens within the data; other similar techniques are the analyses of phrases and exchanges in conversational analyses.
Often referred to as content analysis , a basic structural building block to conceptual analysis, the technique utilizes mixed methodology to unpack both small and large corpuses.
Content analysis is frequently used in sociology to explore relationships, such as the change in perceptions of race over time Morning , or the lifestyles of temporal contractors Evans, et al. Mechanical techniques are particularly well-suited for a few scenarios. One such scenario is for datasets that are simply too large for a human to effectively analyze, or where analysis of them would be cost prohibitive relative to the value of information they contain.
Another scenario is when the chief value of a dataset is the extent to which it contains "red flags" e. Many researchers would consider these procedures on their data sets to be misuse of their data collection and purposes. A frequent criticism of mechanical techniques is the absence of a human interpreter; computer analysis is relatively new having arrived in the late s to the university sectors.
And while masters of these methods are able to write sophisticated software to mimic some human decisions, the bulk of the "analysis" is still nonhuman. Analysts respond by proving the value of their methods relative to either a hiring and training a human team to analyze the data or b by letting the data go untouched, leaving any actionable nuggets undiscovered; almost all coding schemes indicate probably studies for further research. Data sets and their analyses must also be written up, reviewed by other researchers, circulated for comments, and finalized for public review.
Numerical coding must be available in the published articles, if the methodology and findings are to be compared across research studies in traditional literature review and recommendation formats. Contemporary qualitative research has been conducted using a large number of paradigms that influence conceptual and metatheoretical concerns of legitimacy, control, data analysis , ontology , and epistemology , among others.
Qualitative research conducted in the twenty-first century has been characterized by a distinct turn toward more interpretive , postmodern , and critical practices. In particular, commensurability involves the extent to which concerns from 2 paradigms e. Likewise, critical, constructivist, and participatory paradigms are commensurable on certain issues e.
Many times those that undertake a research project often find they are not aware of the differences between Qualitative Research and Quantitative Research methods. Many mistakenly think the two terms can be used interchangeably.
Qualitative Methods Quantitative Methods Methods include focus groups, in-depth interviews, and reviews of documents for types of themes.
Research methods are split broadly into quantitative and qualitative methods. Which you choose will depend on your research questions, your underlying philosophy of research, and . Qualitative vs Quantitative Research. Here’s a more detailed point-by-point comparison between the two types of research: 1. Goal or Aim of the Research. The primary aim of a Qualitative Research is to provide a complete, detailed description of the research topic. It is usually more exploratory in nature.
Learn about the differences between qualitative and quantitative research methods and when to take a deductive or an inductive approach to market research. Qualitative Research Definition: Qualitative research is a market research method that focuses on obtaining data through open-ended and conversational communication. This method is not only about “what” people think but also “why” they think so. The qualitative research method allows for in.