In the last few years, Qualitative Comparative Analysis (QCA) has become one of the most important data analysis methods in comparative research. According to the guidelines of this method, there are certain steps that a researcher needs to follow, before causally analyzing the data for necessary and sufficient conditions. One of these steps is the process of "data calibration." This data calibration process depends on several factors, like the type of data collected, and the form of data distribution, amongst other factors. So, in this article, I have tried to demonstrate the data calibration processing, by focusing on one type of variable. I have focused on an interval variable, and then described how to calibrate it, following Ragin's Indirect Method of calibration. I have applied my own research data to demonstrate these steps. I have used the R Software packages of QCA and SetMethods. By describing these steps, I hope to help future researchers in their own work on data calibration.