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Quantitative Research Methods In Criminal Justice And Security

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Quantitative Research Methods In Criminal Justice And Security
Quantitative Research

Research Methods in Criminal Justice and Security
Professor Beshears
27 February 2014
Quantitative research collects numerical data through surveys, questionnaires, and polls. Quantitative research main purpose is to find the relationship between two variables. According to Babbie (2010) a descriptive study establishes only associations between variables while experimental defines the casualties (pg. 1). The data that is collected from the research is usually used for bigger representation of a population. The data can also be repeated if it was considered to be very accurate and reliable. Every part of quantitative research is scrutinized very carefully before the data is actually collected.
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In a quantitative research, the introduction will contain the problem that is being defined in the research, the reviewing of the literature, and the hypotheses. The methodology will contain the things that were involved in the research. Providing detailed information is important during this process, it will give the reader a better understanding on the research study. If the research use different population or subjects, it is important to list where the data came from and how important it is to the study. The various instruments should also be listed along with a description as to why this instrument was used. The method should also be described in the research along with how the data was gathered. A data analysis should be conducted and contain all techniques and procedures that was used in the study. The results will be presented in past tense. According Babbie (2010) to the results should include graphs, tables, charts, and other non-textual elements to help the reader understand the data (pg. 2). The results should also include the different types of scales that are being measured and a description of the statistics i.e., the types of statistics and the calculation for the interval data. Ouyang (2001) mentions how inferential statistics should lest the levels of significance and the test of significance. The test of significance should include the test for both independent and dependent variables. The discussion will included the interpretation of the results which will discuss the research problem that was identified and then compare and contrast the results with the questions tied to the study. This will answer what happened, if the questions were confirmed, or denied. All of the implications should be discussed, for example, the meaning of the results, and did the results fill any gaps that were in the initial findings. Other findings that may seem irreverent should

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