More Data, More Problems 3 Quantitative vs. Qualitative Data Proceeding further with Furner’s (2017) definition of data, we must understand that there are two types of research data: quantitative and qual- itative. Qualitative data is the collection of information that intends to describe a topic rather than measuring it. Think of opinions, impressions, and views. Quantitative data, on the other hand, is numerical data. If you say, for example, that 52 percent of the plants tested in a study grew to 12 inches or more, while 31 percent grew to 6 inches or less, you’re considering quantitative data. In contrast, the gender of subjects in a clinical study, dividing bulbs into various categories such as “very bright,” “dim,” and “somewhat bright,” or sorting the kind of pizza customers prefer are all simple examples of quali- tative data. Qualitative data is usually interpreted as written narratives or spoken words rather than as numbers. So it’s concerned primarily with data that’s observable, for instance in terms of appearance, smell, taste, texture, feel, gender, or nationality. Some of the methods of gathering qualitative data are as follows: • Observation • Focus group • Interviews • Archival materials such as newspapers Quantitative data could be used in both computation as well as in sta- tistical tests. It is concerned with measurements such as weight, height, vol- ume, size, length, humidity, age, and the like. Furthermore, quantitative data may be classified further as continuous or discrete data. The methods used to collect quantitative data are as follows: • Experiments • Surveys • Observations and interviews While the approach or method of inquiry in the case of qualitative data is holistic and subjective, quantitative data usually calls for an objective, unbiased, and focused approach. Digital vs. Nondigital Data As previously mentioned, not all data is digital. For example, many researchers often keep handwritten journals, laboratory notebooks, and other materials that are not kept on a computer system. This is nondigital data. A research project, for instance, likely would include both nondigital and digi- tal data or data that might originally be nondigital but digitized later. At a more practical level, the difference between nondigital and digital data is in the way the data/information is measured. Keep in mind that ana- log data, by its nature, is continuous and identifies every nuance of what’s being measured or recorded on the other hand, digital data tends to use sam- pling (the process or action of taking samples of something for comprehen- sive analysis) in order to encode what’s being measured.
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