The reason I decided to take Regression was to prepare for another course (SEM and Meta-Analysis) the following semester. Therefore, I had assumed that this class would not be too challenging. Being a naïve PhD student, it was hard for me to imagine how one class based on one analysis—regression, can be as difficult as a general statistics course. Upon completing the course, I can confidently say that regression was the most difficult class I have ever taken.  The breadth and depth of statistics reviewed in this class was overwhelming. I was surprised at how many questions can be answered with regression and the many different approaches one can use with regression from simple linear regression to random coefficient modeling. I am still amazed that one simple concept such as the regression line can be mathematically manipulated and interpreted in so many different ways to answer a variety of questions. However, I also learned how easy it is to misinterpret statistical data and how important it is to be aware of both the different theories and statistics in order to correctly interpret the data. For example, if mathematics self-efficacy was not found to significantly predict achievement, one must rely on their knowledge of both heteroscedasticiy assumptions and gender differences in motivation to test if there is an interaction between self-efficacy and gender.  Overall, this was an important course for me to take and will undoubtedly help me in my future research endeavors.