People say that graduate school (an institution where you do your masters or PhD) is where you unlearn everything you have learnt so far and start afresh. The truth of this is beginning to make sense to me finally. Let me tell you why. All my 27+ years of education, I was taught how to find out answers to questions. The math teacher wrote down a question on the board and we quickly solved it. The Geography teacher asked a question and we raised our hands (It is a different matter that sometimes we raised our hands because she always targeted the students who didn’t raise their hands or shifted uncomfortably because they did not know the answers). The trend continued from school to high school and followed me through college. Read a question, solve it for an answer. However, things changed in the PhD program.
As a part of my curriculum, I started taking higher level statistics classes. I learnt using Statistical Package for the Social Sciences (SPSS). The instructor gave weekly homework we had to turn in. I realized to my dismay that even though I found the answers to the questions she asked, I lost lot of points. It seems it was no longer enough to find an answer, what was more important was how I interpreted the answer. Using SPSS is nothing more complicated than punching in a set of commands and feeding some data, while it obediently spews out answers. Anyone with the basic knowledge of using the computers could do that. However as a researcher, it was my job to make sense of those numbers. Now this is easier said than done. Think of this example I just made up. I am looking at the number of television shows children in the metropolitan cities watch every week, and the grades they obtain in school. Intuitionally, watching too many television shows would lead to impaired grades in school. The fun part begins here. Add to it variables like the socio-economic status of the family, religion, parental education, number of siblings, and gender. Consider factors like who else lives in the family. Think of how the child performed before and how it performs now (pre-test and post-test). Add in a whole bunch of data and the SPSS will faithfully spew numbers. I will look at the numbers and go, wow. But wait, what do the numbers mean? It seems it is not enough to state the value of R-square (variance), you also need to say what it means in the context of the problem. You need to make decisions about statistical significance, but after that, you need to tell them what it means in the context of the problem.
These days, I am not just learning to find answers. I am also trying to make sense of the answers I get. And I am no longer talking only about statistics. If this sounds philosophical to you, you now know why the degree is called a doctorate of philosophy.