A500.7.3.RB – Quantitative Research Reflection

            McLeod, Saul (2008) described quantitative research as:
…a research that gathers data in a numerical form which can be put into categories, or in rank order, or measured in units of measurement.  This type of data can be used to construct graphs and tables of raw data.  Experiments typically yield quantitative data, as they are concerned with measuring things.  However, other research methods, such as observations and questionnaires can produce both quantitative and qualitative information.  For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g. “yes”, “no” answers).  Whereas open-ended questions would generate qualitative information as they are a descriptive response. Experimental methods limit the possible ways in which a research participant can react to and express appropriate social behavior.  Findings are therefore likely to be context-bound and simply a reflection of the assumptions which the researcher brings to the investigation.
 Collecting quantitative data has many avenues such as interview by telephone
or in person, surveys that are self-administered via the internet and testing in central locations.  Whatever the researcher’s research methodology of choice is, a quantitative research design should contain a) conservative choices of the best research methodology since one methodology does not apply to all.  Budget, security issues and timeline has to be however taken into consideration; b) focus in sample design in order to administer accurate with the data collection; c) an intelligent and well-composed questionnaire that consist of a clear understanding of the objective of the research and a clear flow and logic of questionnaires where participants are not questioned about their situation instead, they are given appropriate questions to respond to; and d) statistical analysis that answers to the researcher’s inquiry.
Chukwuba, K. (2015) launched a study regarding turnover rates of the hotel industries, approximately losing 3.4 billion dollars for about 5 years.  It was discovered that the reason behind revenue loss and high rate of turnover were caused by the insufficiency of data to chronicle the hotel professionals’ interconnection between gender, education, job satisfaction and transformational leadership.  The hospitality industry in America has been facing significant challenges in their hiring practices and retaining skilled hotel employees. 
In his study that was focused on transformational leadership, Chukwuba, K. (2015) utilized a quantitative methodology with a survey design on the effects of transformational leadership on job satisfaction for hotel industry professionals because transformational leadership affords the opportunity to describe the relationships among quantitative variables.  The aim of the quantitative research was to investigate and explain the nature of the relationship between two variables in the world.  For Chukwuba’s (2015) study, transformational leadership and job satisfaction variables were involved.  Correlational research studies go beyond describing what exists and concern systematically investigating relationships between two or more variables of interest.  Quasi-experimental research design would have been inappropriate for the study because it did not involve the manipulation of independent variables, and lacked one or both the essential properties of randomization and control group (Chukwuba, K., 2015).
According to Sukamolson, S. (n.d.), there are six main types of research questions that quantitative research is particularly suited to find an answer to 1) when we want to a quantitative answer; 2) numeral change can likewise only accurately be studied utilizing quantitative methods; 3) quantitative research is useful for conducting audience segmentation by dividing the population into groups whose members are similar to each other and distinct from other groups; 4) quantitative research is useful to quantify opinions, attitudes and behaviors to find out how the whole population feels about certain issue; 5) quantitative research is suitable to explain some phenomena, and 6) quantitative research is especially suited for testing hypothesis.
 Overall, the foundation of a quantitative design is its scientific method.  It utilizes deductive reasoning where we a) create a hypothesis, b) during the investigation in resolving the problem, we collect data, and c) we use the collected data from our investigation for analysis in order to arrive at a conclusion or prove that our hypothesis is true or false.  Taking a realistic method, we have to determine the type of questions that can be best answered by using quantitative approach.  Researchers take a realistic method and utilize quantitative approach whenever they want to experiment on a hypothesis.

References:
Chukwuba, Kenneth (2015). Quantitative Model Studying Effects of Transformational
McLeod, Saul A. (2008). Qualitative Quantitative. Retrieved from
Sukamolson, Suphat (n.d.). Fundamentals of quantitative research. Retrieved from

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