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Presser & and Sandberg (2015) notes that interviews are data collection techniques widely used in criminology to collect both quantities and qualitative data. Usually, interviews are held on a one-on-one setting between the interviewer and the interviewee. In criminology, interviews are used as part of a qualitative research paradigm which is classified into three parts. The three classes’ broad category includes structured, semi-structured, and unstructured interviews constitute the broad category of interviews. Structured interviews are often administered verbally as questionnaires by writing down predetermined questions that are administered on the respondent. However, structured interviews do not possess the follow-up quality and further elaborations for the respondent. Structured interviews are often applied in criminology to clarify an issue from a respondent with low literacy skills.
On the other hand, unstructured interviews are time-consuming data collection techniques that can be used to conduct an in-depth probe of the perceptions, feelings, and experiences of the respondent. Unstructured interviews lack the systematic component of observation on the respondent. Semi-structured interviews provide the interviewer with the flexibility to alter some questions to pursue a matter with the desired in-depth understanding. Numerous benefits such as the existence of positive rapport between the interviewer and the interviewee have been observed. This is because a respondent can express personal feelings, emotions, and attitudes towards an issue being interviewed on. It is easy to clarify issues and complex questions. However, the time-consuming technique is less reliable because it is difficult to trace exact questions besides being difficult to ensure the validity of data collected in this way.
Hypothesis testing in a criminal case
According to Vito and Maahs (2015), the second data collection technique is the questionnaire. Often used for collecting survey data, questionnaires can either be designed with closed-ended or open-ended questions. It is easy to code the questions, hand out, and use questionnaires for data collection and analysis. Typically, the frequency with which answers to questions occur can be analyzed to establish if an emerging trend can be observed. Besides, questionnaires need not be answered immediately, which enables the respondent to take time off to read and answer the questions. It is important to note that the questionnaire gives the respondent a great degree of anonymity besides the lack of interview bias and the ability to provide data that can be used to test a hypothesis in a criminal case. However, questions sometimes arise on the data quality, the low response rates, the assumption that respondents have answers, and lack of control in answering the questions.
Observations are appropriate for collecting contextual data from a dynamically changing situation as well as the enumeration of target behaviors, which allows for the use of video as a reliable data collection technique (Presser & Sandberg, 2015). The different categories of observations are highly structured, unstructured, and semi-structured. Observations provide deep insight into an issue.
Weisburd (2015) states that focus groups are used to generate information about the views held by individuals by addressing specific research questions and research objectives. Besides, focus groups enable the researcher to identify the most appropriate data and assure its quality. The method is characterized by a multi-design method for data collection and factors the research norms for each member of the group. Typically, the purposeful composition of groups for exploring a specific issue can be achieved through discussions and intragroup discussions. Focus groups have a major shortcoming where members might not feel free to express individual opinions that might differ with other group members.
Ethnography is a data collection technique from a single phenomenon or a large cultural group over a long period (Fabijan, Olsson & Bosch, 2015). The data collected using this method is characterized by patterns such as group values, beliefs, and behavior.
The importance of data examination is to maintain the integrity of the research to ensure that it is accurate. Data should be appropriate and able to answer the research questions (Copes & Miller, 2015). Research data that has not been examined might have inherent systematic errors, fraud, errors in individual items, and violation of data collection protocols. The other problems that can be avoided by examining data include harm to the respondents, poor replication and validity of data, compromising public policy, and the use of distorted findings.
According to Bachman and Paternoster (2016), statistics in the criminal justice system can be used to predict human behavior, understand the nature of the crime, and the connection between human variables such as employment, age, income levels, crime rates, and attitude. The average set of data which can be shown by the measure of central tendency shows how the impact of a certain human variable on the crime rate. It is important to note that statistical data can be used to establish the prevalence of a certain crime. Besides, social reality and the ability to test a certain hypothesis can be done. Statistical data can enable the researcher to infer a certain characteristic of the population.
Bachman, R. D., & Paternoster, R. (2016). Statistics for criminology and criminal justice. New York: SAGE Publications.
Copes, H., & Miller, J. M. (2015). The Routledge handbook of qualitative criminology. New York: Routledge.
Fabijan, A., Olsson, H. H., & Bosch, J. (2015). Customer feedback and data collection techniques in software R&D: a literature review. New York: Springer International Publishing.
Presser, L., & Sandberg, S. (2015). Narrative criminology: Understanding stories of crime. New York: NYU Press.
Vito, G. F., & Maahs, J. R. (2015). Criminology. Jones & Bartlett Publishers.
Weisburd, D. (2015). The law of crime concentration and the criminology of place. Criminology, 53(2), 133-157.