Quantitative and qualitative journal approaches

Quantitative vs. Qualitative Research

This paper reviews two pieces of literature regarding the debate between qualitative and quantitative research.

Quantitative research focuses on quantifiable features, features that can be counted and used to construct statistical models. In Quantitative analysis, the researcher knows plainly what evidence that they are looking for, as such, all facets of the research are designed before the collection of data. Using questionnaires as well as other tools to collect numerical data, this numerical and statistical data is very efficient when testing a hypothesis, but sometimes misses the related detail of the study. In quantitative research, it is more likely that the researcher to remain objective during the research, separating himself from the subject.

In contrast, qualitative research strives for a complete description of the topic at hand.

This is especially useful when a researcher only has a vague idea of what they are hoping to discover. For this reason, the design of the study is developed as the research is conducted. Instead of relying on tools and questionnaires, the researcher is the means of data collection. and, instead of numerical and statistical data, as in quantitative data, qualitative research data comes in the form of words, objects and pictures. For this reason, more contextual detail is collected; however it is less efficient and the researcher is less likely to be able to remain subjective regarding the topic at hand.

Literature Review:

The research question of what are the differences between qualitative vs. quantitative research is one that has been hotly contested amongst researchers.

This is a logical extension of other previous studies as the topic, in the end, has never been firmly settled. Trochim (2006) argues that there is very little difference between the two types of research, despite the conflict. He notes that all qualitative data can, in fact, be coded quantitatively.

Trochim notes, "Anything that is qualitative can be assigned meaningful numerical values.

These values can then be manipulated to help us achieve greater insight into the meaning of the data and to help us examine specific hypotheses." An example of a typical qualitative questionnaire is used to make Trochim's point.

Open-ended questions are utilized asking respondents provide text responses, these answers are then categorized by theme, which is a quantitative method when one then notes the number of respondents per theme.

Trochim (2006) also notes that all quantitative data is based on qualitative judgment. "Numbers in and of themselves can't be interpreted without understanding the assumptions which underlie them." Trochim uses a typical quantitative 1-to-5 rating variable to help clarify this point, scoring between strongly disagree to strong agree. Should a respondent choose value 2 - disagree, this numerical response can't be interpreted until the researcher investigates some of the judgments and assumptions that underlie it including whether or not the respondent understands that by circling 2 they mean they are disagreeing with the statement and that they're not simply circling something arbitrarily, amongst many other things.

This numerical data always involves judgments what the number means. For this reason, Trochim concludes that quantitative and qualitative data are virtually inseparable, since "(n) exists in a vacuum or can be considered totally devoid of the other."

Ferch (1998) also explores the difference between quantitative and qualitative research. He notes that q) uantitative research is objective; qualitative research is subjective. Quantitative research seeks explanatory laws; qualitative research aims at in-depth description. Quantitative research measures what it assumes to be a static reality in hopes of developing universal laws. Qualitative research is an exploration of what is assumed to be a dynamic reality. It does not claim that what is discovered in the process is universal and, thus, replicable.

Perhaps the most insightful finding Ferch discovers in his exploration is that research is conducted in the real world, and therefore often does not fit into the ideal paradigms of either or research methodology exactly.

He notes that the dualistic thought, either/or dichotomy, is dangerous. and, that it is often the taking these two disparate types of research out of the ideal and into the real world where people become confused.

Method:

The researchers both used qualitative and quantitative methods for proving their point that neither research type can stand alone in the real world; however no data, other than their own experiential data was collected. Therefore, the sample size was considerably small. They used this data to generalize their unique findings to demonstrate the connectivity between the two methods.