What risk factors cause the common cold? How does gender determine the survival outcome? Do red cars have more accidents than blue cars? Is there a difference between pre and post measurements in terms of disease? Research questions are tricky in that you need to make something out of nothing. Your nothing or your emptiness stems from the fact that you don’t have your stats 101 course to guide you through your abstracts, introduction, methods, results, and discussion. If it’s a quantitative study you need solid statistics to support the claims in your paper. But before you can analyze data or decide to reject your variables – you need a hypothesis.
What is your theory on a subject? What do you believe in and how does that relate to the world as you understand it? What is your dependent and independent variable? How about your sample size? Another words, your question has to translate into an answer. You have to find a way to answer your hypothesis. Or come very close to an approximation of the boundaries to your beliefs. If you think a particular demographic has a higher rate of morbidity – what data will you use to support that claim? The bottom line is you need to convince the reader that your beliefs can be substantiated into something concrete. It’s not an easy task but in the end you should believe that your questions are worth answering.
If you enjoyed this reflective blog there are more to follow-Amy
