Explanation of qualitative and quantitative data
Research studies require the collection, analysis and interpretation of data, which helps to infer about the population. Qualitative data are collected from study respondents in the form of a specific language that is easily understood by researchers conducting a study. Researchers use qualitative data to approximate or characterize the attributes of a phenomenon being studied. Thus, they are utilized to describe the phenomena rather than give detailed definitions. It is quite difficult to measure qualitative data, but they are observed in study participants. Statistical approaches use categorical data to refer to qualitative data. Categories of data are characterized by specific structures. If data categories do not adopt specific orders, then they are known as nominal data categories. However, if categories of data are ordered, then they are known as ordinal variables (Babbie, 2014).
Quantitative data are represented by numbers. They can be observed and measured using specific instruments that are used in research studies (Cappello, Bleve, Grieco, Dellaglio & Zacheo, 2004). A natural language that could be interpreted is not used. In most cases, quantitative and mixed-methods research designs use quantitative data, which are analyzed using statistical tools. Quantitative data are obtained through systematic approaches that are verifiable and replicable (Cappello et al., 2004; Babbie, 2014).
Thus, they are objective and cannot be compromised through incorrect interpretation. This could be the reason why many research studies use quantitative data. In fact, they produce results that have good statistical powers and that could be relied upon to make conclusions that could have great implications for many scientific approaches in life. Discrete variables adopt specific whole numbers while continuous variables could assume values between whole numbers (Babbie, 2014).
Examples of qualitative and quantitative data points and units
Babbie (2014) argues that data points are sets of observations or measurements that are associated with a sample from a study population. Qualitative data represent observations and they do not have units (Kluge, 2006). Qualitative data points that have a nominal scale could include the following:
- Gender
- Species
- Nationality
- Language
- Style
- Form
- Color
Based on the observations (data points), a phenomenon could be described in great detail without statistical measures. For instance, languages spoken by different study participants could be explained, but they could not be measured and analyzed through statistical tests (Kluge, 2006).
Qualitative data points that have ordinal scales could include the following:
- Agree versus disagree
- Guilty versus innocent
- Wrong versus right
- Sick versus healthy
- Completely agree
Thus, ordinal scale data points are organized in some forms that could be explained, but do not have units. For example, a study subject could be healthy, but the health status could not be measured and be assigned a specific number (Kluge, 2006).
On the other hand, quantitative data points or measurements are represented by numerical values that are quantifiable (Babbie, 2014). Also, the data points have specific units that follow standard forms. The following is a list of quantitative data points and their units:
- Height in meters
- Weight in pounds
- Time in hours
- Scores in percentages
- Concentration of a reactant in moles
As shown in the above examples, quantitative data points are represented by values that can be directly measured. Also, the use of units helps to increase replication of experiments by independent researchers.
References
Babbie, E. (2014). The Basics of Social Research. (6th ed.). Belmont, CA: Wadsworth. Web.
Cappello, M. S., Bleve, G., Grieco, F., Dellaglio, F., & Zacheo, G. (2004). Characterization of Saccharomyces cerevisiae strains isolated from must of grape grown in experimental vineyard. Journal of applied microbiology, 97(6), 1274-1280. Web.
Kluge, A. (2006). Qualitative and Quantitative Analysis of Grammatical Features Elicited among the Gbe Language Varieties of West Africa. Journal of African Languages and Linguistics, 27(1), 53-86. Web.