Differences Between Qualitative and Quantitative Data – Advantages and Disadvantages of Data Collected

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Qualitative and quantitative data are collected through observations by scientists with the intentions of making vital conclusions about phenomena in life (Ellis, Hartley & Walsh, 2010). Scientists often choose the type of data to collect in their studies depending on the study design and objectives. Qualitative data are collected by scientists through unstructured observations (Ellis et al., 2010). For example, a scientist could be interested in assessing breastfeeding patterns among women in a geographical area. He or she could visit breastfeeding mothers and observe them as they breastfeed. The scientist could use unstructured ways of observing and recording data. He or she could record all data that he or she finds interesting for analysis. On the other hand, quantitative data are collected using structured observations (Ellis et al., 2010). For example, scientists could be interested in establishing the relationship between sickle cell anemia and mutations in some human genes. The scientists could collect data using structured observations in the laboratory.

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Qualitative data are collected in the form of words (Ellis et al., 2010). During the data collection process, a scientist could write down his or her observations in the form of words which could be coded later to have some numerical values. On the other hand, quantitative data are collected through observations in the form of numbers (Ellis et al., 2010). The numbers are analyzed by use of statistical tests to draw some conclusions. Qualitative data are used to gain some in-depth knowledge about phenomena in life while quantitative data are used to quantify some observations in life. In other words, qualitative data are based on the quality of observations while quantitative data are based on the quantity of observations under investigation. Scientists can use quantitative data to test many hypotheses in a research study. On the other hand, qualitative data cannot be used by scientists to test any hypothesis in a research study (Ellis et al., 2010).

When scientists use self-reports to collect data from respondents, they give the respondents the freedom to read the questions and choose responses. Scientists do not interfere with the respondents’ responses (Onwuegbuzie, Johnson & Collins, 2009). Questionnaires and interviews are the two methods that are used to collect data in self-report studies. Data collected using self-reports could be a lot because the data collection methods could allow the administration of questionnaires and interview questions to many respondents simultaneously (Ellis et al., 2010). Another advantage of self-report data is that the data are authentic because they are actual responses from respondents. Scientists have no chance to manipulate the data (Onwuegbuzie et al., 2009). This is essential because data for study analysis should be authentic and unbiased. Data collected using open questions usually provide detailed answers, and they could be used to tell what respondents were thinking as they gave the responses (Onwuegbuzie et al., 2009).

On the other hand, data collected through self-reports have several disadvantages. One disadvantage of self-report data is that the data lack validity (Onwuegbuzie et al., 2009). For example, there have been concerns that respondents could provide wrong answers to questions in questionnaires intentionally (Onwuegbuzie et al., 2009). Self-report data could also be exaggerated when respondents feel that some responses could touch on their personal lives. Self-report data could also be biased because respondents could give responses based on their situations. If they are in bad moods, they could give responsthatich could be biased.

Responses

Ellis, L., Hartley, R. D., & Walsh, A. (2010). Research methods in criminal justice and criminology: An interdisciplinary approach. Lanham, MD: Rowman & Littlefield.

Onwuegbuzie, A. J., Johnson, R. B., & Collins, K. M. (2009). Call for mixed analysis: A philosophical framework for combining qualitative and quantitative approaches. International journal of multiple research approaches, 3(2), 114-139.

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