Qualitative vs. Quantitative Data
Data is essential for many reasons. It offers a deeper understanding of something, promotes the development of proper theories, helps recognize problems, and encourages proper decision-making. Nevertheless, it is important to note that there are different types of data, namely qualitative and quantitative data. According to Alexander Djerassi, here are the key differences between qualitative and quantitative data.
Djerassi defines qualitative data as descriptive data that can neither be counted or measured. Researchers use language instead of numerical values to present this kind of data. Qualitative data is used to provide answers to “How?” and “Why?” questions. The entrepreneur defines quantitative data as quantifiable data. It is measured in numerical values rather than descriptive words. It is used to answer “how much?” and “how many?” questions.
Differences Between Qualitative and Quantitative Data
Qualitative and quantitative data have differences that set them apart. The differences are primarily based on the kind of information these data types provide. One difference is that qualitative data is descriptive and presented using words, while quantitative data is measurable and presented using numbers. Another difference is that qualitative data provides information about “how” or “why” certain things occurred. Quantitative data includes information about quantifiable concepts like how much an item costs or how often it rains in the city.
In addition, qualitative data is subjective and dynamic from one observer to another. For instance, different people have different qualitative accounts about the quality of fries at KFC. Quantitative data is fixed and doesn’t change. For example, different people will have the same quantitative account about how many seasons the United States experiences in a year.
The ways these two kinds of data are collected also differ. Qualitative data is gathered through observations and interviews, while quantitative information is collected through measures and counts. They are also analyzed differently. Qualitative data is analyzed by sorting information based on common themes and classes. Statistical analysis methods, such as hypothesis testing, standard deviation, and regression analysis, are used to analyze quantitative data.
Types of Qualitative Data
Qualitative data is further divided into different types. Qualitative data is divided into nominal data and ordinal data. Nominal data is qualitative data used to group particular variables without assigning them any quantitative value. Ordinal data is qualitative data in which variables are given a quantitative value.
Types of Quantitative Data
Like qualitative data, there are different types of quantitative data. Qualities can be continuous or discrete. Continuous data is quantitative information that can be put in a continuum and separated into smaller, distinct units. Discrete quantitative data can be presented using specific values and cannot be divided into smaller units.
Examples of Qualitative and Quantitative Data
Qualitative data in real life include recordings, interview transcripts, and observations. Common examples of quantitative data include calculations, counts and projections.
It is necessary to understand data and what they present. Alexander Djerassi’s explanation of the differences between qualitative and quantitative data is helpful in having more information about these types of data.