In research, random variables in the form of numerical values are used to represent counts and measurements. Researchers must define the concepts being observed in research as they determine how the variables will be measured. Discrete and Continuous variables are the major types of variables. Categorical variables fall under discrete variables. This essay discusses the different examples of continuous, discrete, categorical, and dichotomous variables.
Continuous variables represent values which are not limited to whole-numbers only. These are variables that belong to a wide range of values. Examples of continuous variables include height, weight, age, blood pressure measurement, and salary. Variables that can only be represented by a limited number of values, which in most cases are whole numbers are referred to as discrete variables. While discrete variables may differ from one person to another, a limited number of the values associated with these variables are compatible with life. Discrete variables include respiratory rate values, number of siblings that a patient has, and the number of people who have attended a therapy session. Other examples or discrete variables include clinical stage of cancer and number of admissions to a hospital (Cannon, 2015; Woodwell, 2013).
Categorical variables, on the other hand, are discrete variables which are non-quantitative. They represent variables which cannot be measured numerically. They include variables such as ethnicity groups, blood group, gender, marital status, HIV status, and pregnancy test results. Some of the dichotomous variables among those included in these three categories include gender, HIV status, and pregnancy test results (Cannon, 2015).
Dichotomous variables are variables that have no numerical basis and only consist of two categories. In the case of gender, participants can either be male or female. Patients’ HIV status, on the other hand, can only be represented as positive or negative, while pregnancy test results can only be documented as positive or negative (Cannon, 2015). In a research conducted on the gender differences in symptoms of depression, the researchers used gender as a dichotomous variable. The patients were also categorized as depressed and non-depressed which provided another dichotomous categorical differentiation of variables (Frazier, et al., 2012).
Cannon, B. S. (2015). Introduction to Nursing Research. Burlington, MA: Jones & Bartlett Publishers.
Frazier, L., Yu, E., Sanner, J., Liu, F., Udtha, M., Cron, S., . . . Bogaev, R. C. (2012). Gender Differences in Self-Reported Symptoms of Depression among Patients with Acute Coronary Syndrome. Nursing Research and Practice, Article ID 109251. Retrieved from https://www.hindawi.com/journals/nrp/2012/109251/.
Woodwell, D. (2013). Research Foundations: How Do We Know What We Know? Washington DC: SAGE Publishers.