Ever since elementary school, we have learned how to perform mathematical functions, from simple addition and subtraction to more complex multiplication and division. Included in our early math studies was how to determine the values of the mean, median, mode, etc. For years, we were asked to calculate these values at all levels of academia; from a simple sixth grade homework assignments, to determining the mean fluorescence level of viral entry in an undergraduate thesis. As a result, we have taken for granted the power that is contained from the values we use in these calculations: the power of continuous variables.
Before this class, I was one of those people who didn’t appreciate the power of continuous variables in science. However, by simply flipping through Harvey Motulsky’s Intuitive Biostatistics, it is clear that I was missing out. A quick glance at the table of contents shows that nine chapters are included under the continuous variables subsection in the book. Since the book has 49 chapters, that means that the study of continuous variables makes up 18% of the textbook. Upon looking more closely at these chapters, you see that continuous variables make quite a contribution to the study of statistics. These variables are used to make scatter plots, determine confidence intervals, make a Gaussian distribution, and so forth. The use of continuous variables opens the door for a huge range of different possible statistical tests and possible analyses.
What impresses me the most about continuous variables is not the vast number of analyses that can result, but rather the ability of these variables to connect the scientific community. As described in the lecture, a continuous variable is a scalar physical property, such as mass, concentration, etc. Within each of the different measurements, a standard unit of measurement has been established which is used by scientists all over the world. This allows for scientists around the world to compare data easily and without any blocks in data analysis or losing anything in translation. As a result, a scientist in the United States can have a collaborator in Russia and be able to share data back and forth without giving a second thought to possible data conversion. This ability is achieved by the power of continuous variables.