Differences Between Qualitative and Quantative Research

Running head: QUALITATIVE VERSUS QUANTATIVE 1

Differences between qualitative and quantative research

Lorraine Perez

West Virginia University

Integrated Marketing Communications

Audience Insight - IMC 612

Professor Bennett

QUALITATIVE VERSUS QUANTATIVE 2

Differences between Qualitative and Quantative Research

You may have heard the world is made up of atoms and molecules, but it's really made

up of stories. When you sit with an individual that's been here, you can give quantitative data a

qualitative overlay. ~William Turner

In the above quote, Turner relates the stories of atoms and molecules to that of

quantitative data and qualitative overlay. The need to choose between quantitative data and

qualitative data is as common, although not as controversial, as deciding between democrat and

republican or evolution and creationism. However, before anyone can make an educated decision

as to which side is the most logical between the two it is vital to ensure that both sides are clearly

explained. In the following essay the author will attempt to define both quantative and qualitative

data as well as provide contrasts and similarities to the two. In addition, a discussion of how each

of these can be useful and benefit both the industrial and academic arenas will take place. It is

also important to discuss which methodology, in the author’s opinion, is the best option.

Quantative data, simply stated, is information or data that can be gathered numerically. It

is more accurately defined, according to Babbie (2007) as “quantitative analysis, or the

techniques by which researchers convert data to a numerical form and subject it to statistical

analysis” (p.405). Babbie continues to tell us that researchers convert data such as social sciences

into “machine-readable forms. It is then statistical data analysis software such as SPSS or

“Statistical Packages for the Social Sciences” which converts it to useable data (Gates &

McDaniel, 2006). The data that must be converted ranges from simple numerical information

such as age, income, number of people in the household, number of children in the household to

data such as favorite color and personal goals. It is the information that is not so easily converted

that must then be coded or translated to a simple attribute usually described as a variable. Coding


itself poses a challenge as the coding process can be long, tedious and frustrating. If inaccurately

categorized the data has the inclination of becoming skewed and useless. It is for these reasons

researchers developed a codebook designed to combat the uncertainty of categorization. Once

this process is completed the task of quantitative analysis can begin. There are several methods

used to statistically analyze the data including but not limited to: univariate analysis, bivariate

analysis, and multivariate analysis. As the names suggest, univariate analysis refers to” the

analysis of a single variable”, bivariate refers to an analysis that “focuses on relationships

between variables rather than on comparison groups”, and multivariate analysis refers to the

“simultaneous relationships among several variables” (Babbie, 2007, pg. 427).

What could be considered the polar opposite of quantative analysis is qualitative analysis

or qualitative research. According to Gates & McDaniel,

Qualitative research is a term used loosely to refer to research whose findings are not

subject to quantification or quantitative analysis…While quantitative research might be

used to find statistically significant differences between heavy and light users, qualitative

research could be used to examine the attitudes, feelings, and motivations of the heavy

user. (2006, p. 78)

One would think that a major flaw in qualitative research method would be the inability to utilize

software to categorize the information; however, this is not the case. In fact, there is software

designed to assist researchers gather all the data necessary. One such software is NUD*IST or

Non-numeric Unstructured Data, Index Searching, and Theorizing (Babbie, 2007). Qualitative

research goes beyond the numerical aspect of information retrieval and uses information that can

be recovered through observation and interaction. Focus groups, one-on-one in person

interviews, mail interviews, and phone surveys are but just a few examples of how information is


gathered utilizing the qualitative research method. There are many challenges to this method

including bias, skewed interpretation, fear of privacy violations and fear of repercussions.

As anyone can see, utilizing either one of the aforementioned methods has its advantages;

however, there is still much debate as to which method is the best method. For instance, while

Donald Campbell claims “all research ultimately has a qualitative grounding” Fred Kerlinger

stands with the notion that “there’s no such thing as qualitative data. Everything is either 1 or 0”

(Neill, 2007). So, who is correct? Prior to answering this question it is best to do a comparison of

each method. Quantitative research analysis is directed toward classifications, numerical

analysis and statistical models in order to explain what is and to predict what could be while

Qualitative research analysis takes a step back and attempts to get a complete detailed picture of

the situation. Since the results are usually numeric the quantative researcher has the advantage of

knowing in advance not only the design of the study but also what he/she is looking for in the

end while both design and purpose for the qualitative researcher are vague and do not come to a

close until later in the project. Due to the numerical and statistical focus of the quantative method

the objective allows for tools such as questionnaires, surveys, etc... in order to develop an

efficient and targeted analysis of concepts and test hypothesis. Qualitative analysis, on the other

hand, is much more time consuming as the only tool utilized is the researcher himself/herself to

gather information in the form of words (in-depth interviews, focus groups), pictures (participant

observations) or objects (artifacts). Yet, because this method is highly contextual it allows details

that could not be gathered numerically (Neill, 2007).

So the question remains….which method is the best method? According to Colorado State

University,


Although there are clear differences between qualitative and quantitative approaches,

some researchers maintain that the choice between using qualitative or quantitative

approaches actually has less to do with methodologies than it does with positioning

oneself within a particular discipline or research tradition. (2011, p. 1)

However, this author maintains that both methods can prove to be equally beneficial and can be

used simultaneously. For instance, most research universities fund the professors’ research

projects in order to develop a distinguished faculty and gain respect from the academia body.

Research projects may range from common subject matter to innovative teaching designs. What

is interesting is research reaches far past the actual academics and can be found in areas such as

grant development and admissions/retention departments. An instance where both quantitative

and qualitative methodology can be utilized simultaneously is where the student services

department is considering whether or not to implement a mentorship program. The department

can gather all the numerical and statistical data regarding the program to include participation

rate, age and degree specifics and then conduct focus groups to determine how the program may

affect the overall feeling of acceptance and social interaction of the students. In the automotive

industry numerical statistics are great indicators of the increases and declines in model demands

but may not indicate the reasoning for each occurrence. Only through direct interviews processes

can this be achieved. It only proves that when necessary a primarily inductive (qualitative)

process will only compliment a primarily deductive (quantitative) process (Oak Ridge Institute

for Science and Education, 2011).

Deciding between qualitative and quantitative analysis method in research is nothing

more than another area of which it is a matter of perspective and purpose. What will benefit one

may not benefit the other. However, when the opportunity arises where both methodologies can


be utilized offering a much more complete and comprehensive approach then that is where the

company, regardless of industry, will benefit the most.


References

Babbie, E. (2007). The Practice of Social Research (11th ed.). Belmont, CA: Thomson Learning,

Inc.

Colorado State University (2011, July 6). The Qualitative versus Quantitative Debate. Retrieved

September 3, 2011, from http://writing.colostate.edu/guides/research/gentrans/pop2f.cfm

Gates, R., & McDaniel, C. (2006). Marketing Research Essentials (fifth ed.). Hoboken, N.J.:

Wiley & Sons, Inc.

Neill, J. (2007, February 28). Qualitative versus Quantitative research: Key Points in a Classic

Debate. Retrieved September 3, 2011, from

http://wilderdom.com/research/qualitativeversusquantitativeresearch.html

Oak Ridge Institute For Science And Education (2011, July 6). Differences between Qualitative

and Quantitative Research Methods. Retrieved September 3, 2011, from

http://www.orau.gove/cdcynergy/demo/content/activeinformation/tools/toolscontent/

soc_qual_quant_chart.htm


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Differences Between Qualitative and Quantative Research