Quantitative Research and Methodology

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Quantitative Research

Quantitative research can be defined as a systematic experimental investigation that quantitatively provides the data to facilitate analysis and conclusion. Quantitative research performs a noble role in the research continuum. It places much emphasis on research findings thereby increasing both validity and credibility. It makes use of statistical, mathematical, and computational techniques to enhance understanding of research findings. Many of the issues around the globe today that form the basis of theses and research cannot generate meaningful findings if the inherent data and findings are not quantified (Adam & Healy, 2000).

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Quantitative research performs this role by making research findings significant and effective for the users of the research (Denzin & Lincoln, 2000). By presenting the findings in form of charts, graphs, and tables, the research sheds more light on the research problem and ensures that the process of analyzing data is done effectively. This research technique equally reduces bias because large samples of data are used in data collection thereby achieving sample validity and credibility and therefore the study.

Several strategies that can facilitate further understanding in the area of quantitative research techniques exist. These include the application of the method practically when confronted with day-to-day world issues. For instance, one can use data on height, distance, weight, scales, or even ratings to compute the basic statistics such as mode, frequency, mean and median in addition to applying other statistical techniques. Microsoft Excel offers a good platform through which individuals can effortlessly perform various statistical procedures like regression analysis, drawing of graphs and charts that are primary components of a quantitative technique. Similarly, a review of previous quantitative research can equally offer useful insights into the application of the technique (Stanton & Rogelberg, 2001).

Research Methodology

Emergency workers play a significant role in society. This study investigates how the attitudes, experiences, training, and education of emergency workers influence their level of service delivery. The research hypothesis is: the experience, knowledge, and attitude of emergency workers in prioritizing emergency measures affect accident victims.

The researcher proposes a quantitative research technique that makes use of a descriptive design. Questionnaires will be used to collect data from a simple random sample of 250 emergency workers who are selected to participate in the research. The questionnaires will permit a large sample size at a reduced cost. Similarly, it will yield statistical data that can be analyzed using SPSS software.

The contrary methods are the qualitative method that is the best in studying human behavior as it ensures objectivity (Walsham, 2006). A descriptive survey will equally be undertaken to gather data on experience, current attitude, and knowledge of emergency workers in rescue operations. Descriptive analysis will be applied to the data gathered. Analysis of the qualitative data will be done. Each reply to the questions in the questionnaire will be coded using numbers on a scale of 1 to 7. A statistician will then be hired to load the data into the SPSS (Social Packages for the Social Sciences) computer package and analyze the data. The data will be described using central tendency (mode) and frequency (charts, tables, and bars).

To ensure the quality and reliability of data, my friends will do a test-run to the questions to ensure that they are clear, unambiguous, and relevant. Two experts will evaluate the questionnaires in terms of content validity. This will ensure that the questions highlight the concepts under investigation and that they have an adequate scope (Saunders, et al. 2006). To test for reliability, the questionnaires will be administered twice, once a week one week apart and the results compared.

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References

Adam, F. & Healy, M. (2000). A practical guide to postgraduate research in the business area. Dublin: Blackhall Publishing.

Denzin, N. & Lincoln, Y. (2005). The Sage handbook of qualitative research. 3 ed. Thousand Oaks, NJ: Sage.

Saunders, C. et al. (2006). How low should you go? Low response rates and the validity of inference in is questionnaire research. Journal of the Association for Information Systems, 7(6), 351-414.

Stanton, J. & Rogelberg, S. (2001). Using internet/intranet web pages to collect organizational research data. Organizational Research Methods, 4(3), 199-216.

Walsham, G. (2006). Doing interpretive research. European Journal of Information Systems, 15(3), 320-330.

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