What is a variable? This frequently encountered term in college baffles students who had no previous exposure to research. This term is used when a student enrolls in either their subject in research or statistics. A good understanding of what variable means, therefore, is required to be able to understand the other jargons of research or statistics. This article explains in simple terms what the term variable means.
A very common term encountered by students in the development of a thesis is the word variable. This word is encountered both in elementary and advanced statistics as well as in the construction of the theoretical and the conceptual framework in the course of preparing a thesis proposal or a research paper.
A good knowledge of what variable means is required in order to construct the conceptual framework based on the theoretical framework as well as to determine the type of variable that will have to be analyzed in order to come up with good conclusions. This is especially true to quantitative studies where numbers are required for computation of correlations among variables identified in the study or differences between variables in groups.
But what are variables and what are examples of these variables? This important terminology in statistics and research is explained in a simple manner below with two examples.
What is a variable?
A variable is something that varies and should be measurable so that it can be analyzed, discussed empirically and interpreted. Derived from the root word "vary", a variable is a feature or a characteristic found in a phenomenon or object which researchers would like to study.
Phenomena in nature are those that are of interest to researchers that somehow strike their curiosity. It is in man's nature to be inquisitive about what is going on around him. Facts, events or the like in the world is complex or abstract.
There is a need, therefore, to pin down these complex occurrences in nature into manageable bits, isolated in their simplest forms as much as possible to allow statistical analysis and interpretation. These simplified bits are the variables.
Example of Variables
To illustrate what is a variable, take the case of a researcher who wants to find out the relationship between waistline and lifespan, there are actually two variables here. One is the waistline and the other is the lifespan of an individual.
What varies in the waistline? Of course, the size of the waistline varies from person to person. Since a scientific investigation must be done and the researcher must be empirical about it, the waistline should be measurable. A better term for the variable "waistline" therefore to make it measurable is "size of waistline".
Since size at this point can be measured, the researcher might want to categorize size into four: small, medium, large, and very large. But this is a crude way of measuring size as the word "small" may be interpreted by people in different ways. What is small in one person's perspective may be medium in another person's assessment.
So to make the whole thing much more objective and thus more scientific, the researcher may decide to use a tailor's tape and measure the waist of people to derive the size of the waistline. For consistence across measures, the standard of measure that will be adopted by the researcher might be in centimeters. Centimeter is the unit of measure. Now, the waistline in centimeters will vary among the individuals whose waistlines are measured. And this is a better way of measuring waistline compared to just saying small, medium, large or very large. The size of waistline in centimeters will lend itself better to statistical analysis.
The researcher must ensure that the circumstances in measuring the waistline should be the same to avoid arriving at wrong conclusions. The measures, in fact, are subject to error as there will be inconsistency in measuring the waistline. Inconsistency in measures may be committed if the individuals studied were measured by different researchers.
Measurement also depends on how keen the researcher is in doing the measurement. Will measurement of the waistline be done by tightening the tailor's tape around the waist, will the researcher let the person take in some air before measuring, or should this be done after lunch when the person is full?
But the above is only about the waistline as a variable. How about lifespan?
The lifespan of a person may be defined as the period between birth and death. This, therefore, means that the researcher has to actually gather data of people who have already died to measure the number of years they lived. So a record of their waist measurements will have to be available to be able to carry out this study.
Where to look for this data? The researcher might want to go to hospitals or request records from doctors. To find out the correlation, the data gathered may be analyzed using Pearson's product moment of correlation as a statistical tool. But this is a different story.
Variables are of four different types according to how these are measured. Learn more about these types in Four Statistical Scales of Measurement.
©2012 September 19 Patrick A. Regoniel