Quantitative research methods and data collection instruments

Business Research Terms and Concepts

KNOWING THE DIFFERENCES

Understanding Research Terms and Concepts

Quantitative Research Methods and Instruments

Quantitative research tests hypotheses from theories or approximates the magnitude of a particular phenomenon (Eau Claire, 2014). Participants or volunteers are assigned at random to different aspects or derive data from them to control their influence on a dependent variable. Probability sampling may be used if the intent is to generalize (Eau Claire).

Quantitative data collection methods utilize and depend on random sampling and structured data collection instruments (Euau Claire, 2014). These methods and their instruments are suited to different anticipated types of responses. Their findings are easy to determine, summarize, analyze, compare and generalize. The most typical methods are experiments or clinical trials, observation and recording of a specific event, securing data from an entity's management information systems, and surveys with closed-ended questions. Surveys are conducted through interviews or questionnaires as instruments (Eau Claire).

Interviews may be face-to-face, by telephone or by computer-assisted personal interviewing (Eau Claire, 2014). Face-to-face interviews enable the researcher to personally connect with the participants and thus yield the highest level of response. Researchers are also able to clarify uncertain matters or follow up on some question or detail. These interviews are, however, impractical when the population sample is too large. Telephone interviews are faster and more inexpensive. They also provide quick and easy access to participants with telephones. They provide more reliable responses than those derived from mailed interview questions. But these responses are not dependable in that they exclude random participants without telephones who are necessary to the research. And computer-assisted personal interviews are conducted by entering responses directly into a laptop or hand-held computer's database. This type saves times and eliminates the need to carry bulky questionnaires. But they are expensive and require computer and typing skills (Eau Claire).

Questionnaires are either the paper-and-pen type or web-based (Eau Claire, 2014). The paper-and-pen type is cheaper and time-saving to the researcher. Respondents or participants also tend to be truthful with their answers because the questionnaires are anonymous. But the downside is that the majority of respondents do not send back these questionnaires. The result thus is not representative of the sample size. Web-based questionnaires are conducted through emails, which bring the respondents to a website where they are asked to fill in the questionnaire. Like the telephone survey, however, the results are not representative of the sample as the responses of those without computers are excluded (Eau Claire).

Two Articles

The article, entitled "Starbucks, Bank One, and Visa Launch Starbucks Duetto," discusses the use of the descriptive statistical method in managing the business problem of Starbucks (Schindler, 2006). The article presents a concrete concept, planning and mechanics, a clear timetable, accomplishments and projections. Results of quantitative studies lend support to the statement of accomplishments and projections (Schinder).

On the other hand, the article entitled, "Mastering Teacher Leadership," uses the inferential statistical method (Schindler & Cooper, 2001). It uses a multi-stage communication study on teachers at the Wittenberg University Department of Education in determining the viability of a certain course for a certain sample population. This course is the Master of Education program and the sample population consists of Ohio-certified teachers within the school districts in the county (Schindler & Cooper).

Comparison and Contrast

Inferential Statistical Method

This method, like the earlier one, uses the same calculations, such as the mean and standard deviations (Laerd, 2013; Brown, 2010). It also starts with a sample but, unlike the descriptive statistical method, it leads to a generalization of the sample. Moreover and unlike the earlier method, the information it brings out is not in numbers but in parameters. These parameters, however, represent a range of potential numbers. This method because meaningful in a research when the researcher cannot capture the entire population needed. It makes use of samples to represent the larger population. This method allows the use of these samples in establishing generalizations from the samples. But these samples must represent the population. The process is called sampling and the methods involved are the estimation of parameters and testing of statistical hypotheses (Laerd, Brown).

Strengths

The descriptive statistical method provides clear and certain meaning and interpretation of even large volumes of data (Taylor, 2015). In contrast, the inferential statistical method does what the descriptive statistical method cannot. It can generalize using samples, which represent the population that cannot be accessed (Taylor).

Weaknesses

The descriptive statistical method allows a summary and conclusion only on the sample respondents or objects measured (Taylor, 2015). It cannot extend to those, which have not been measured. It cannot make inferences (Taylor). The inferential statistical method, on the other hand, has two major limitations or weaknesses. The first is the uncertainty of the values of data, which have not been measured. That value is based only on inference. The other limitation is related to the first. Some inferential tests require educated guesses, which always have room for error that may have adverse effects on the results of the research (Taylor).

The Two Methods Combined

Burns journal conducted a study on combining these two methods for its articles (Al-Beena et al., 2010). It aimed at determining the descriptive method's men, median, standard deviation and range as well as survey inferential methods, such as statistical tests. It pooled 51 original articles in 2007, except letters to the editor, brief reports, reviews and case reports. It appraised characteristics, the use of descriptive statistics, nd the number and types of statistical methods used. Results showed that descriptive analysis and the basic statistical instruments comprised ost of the statistical tests. Thee information would be useful in educating burn care professionals. These results suggest the importance of a sufficient knowledge of basic statistics among burn care professionals. The study recommended the need for advice from experts in biostatistics and epidemiology by burn care professionals in their use of more advanced statistical methods, techniques and tools (Al-Beena et al.).

In the practice of my profession, I would need to use the combined methods as well to provide me with both clear and certain interpretation of data and a reliable generalization on an entire population of a future study material or project. #