This column is written for statisticians with master’s degrees and highlights areas of employment that will benefit statisticians at the master’s level. Comments and suggestions should be sent to Megan Murphy, Amstat News managing editor, at megan@amstat.org.

Contributing Editor
Lauren Bailey is a first-year biostatistics PhD student at the University of Illinois at Chicago. She earned her bachelor’s degree in mathematics from the University of California at San Diego and a master’s degree in statistics from San Diego State University.

When I was an undergraduate at the University of California at San Diego, a professor introduced Cantor’s diagonal argument. The elegance and creativity of Georg Cantor’s contradiction blew me away. It now seemed the real numbers was merely a giant block of Swiss cheese, containing infinitely many holes.

This was the first time I saw mathematics as a creative undertaking, not merely a dry application of stodgy equations. Appreciating that proof was a life-changing day for me and solidified my commitment to mathematics and statistics. Elated, I stood up, grabbed my skateboard, and soared to the registrar’s office to change my major from chemistry to mathematics. The sparkle of ingenuity I discovered that day is embedded in mathematics and statistics. It continues to reveal itself and keeps me motivated to push myself and the boundaries of research.

When I finished my undergraduate degree, I had a difficult time securing a job. Interview after interview I was told the same thing: “We like that you have a degree in math; that tells us that you can think. However, we need someone here who knows statistics.” I had no idea that statistics was so valuable in the workplace. As an inroad to the subject I loved, I decided to return to school and complete a master’s degree in statistics.

Fresh from my master’s degree, I landed my first job as a research statistician and statistical programmer at the University of California at Irvine (UCI). I worked with a health economist on several projects involving regulation and quality measures of nursing facilities. It was at this job that I learned about the practical and interdisciplinary nature of statistics, which I continue to find rewarding.

Working on econometric modeling procedures required me to tweak my statistical approach and way of thinking. For example, when deciding which variables to throw out of a model, school had taught me to use stepwise regression (or some other type of iterative variable selection technique). However, my boss disdained these techniques, opting to use joint F-tests with a pre-selected group of variables based on the theory underlying the research question, to discard variables from the model. These new methodologies forced me to consider several approaches when analyzing data or setting up an investigation. One valuable lesson I took away from working at UCI was to keep an open mind about statistical approaches—there is more than one way to skin a cat!

After working as a researcher at the university for almost two years, I had identified the objectives buy ativan wyeth that would contribute to a fruitful and stable career for me. These included (1) research leadership, (2) specialization, (3) networking and getting involved, (4) working extremely hard every day, and (5) smiling. I had (4) and (5) down, so I decided to focus on (1)–(3).

I had taken several biostatistics classes in my master’s program and enjoyed health topics. This seemed like the perfect segue to specialize in a rewarding statistics-related field with a healthy growth outlook. I thought a doctorate would enable me to obtain the knowledge and credentials I would need to be a lead on a research team. So, I resolved to pursue a PhD in biostatistics. In my quest to get more involved, I was recently elected secretary for the ASA’s Section for Statistical Programmers and Analysts. It has been exciting to work with a group committed to representing and enriching the statistical programmer community.

Going back to school has entailed life changes. Daily life now involves several challenging classes, providing mentoring to students through a teaching assistantship, and working as a research consultant. I have relocated from the sunny beaches of Southern California (where I spent my entire life) to Chicago. And winter has just begun to set in … However, after all these events, I am confident this was the best choice for me and my future professional objectives.

One of my current activities is a research assistantship position at the Institute for Health Research and Policy. The interdisciplinary work I enjoyed at UCI continues to expand in my work at UIC. Clinicians and researchers come to me with their statistical questions and problems to solve. They may need power and sample size calculations for an R-01 grant, exploratory longitudinal graphs, or programming help for a certain flavor of logistic regression. I have the exciting opportunity of assisting all types of researchers with diverse problems.

Much like the lessons learned from my former economist boss, clinicians have different statistical needs than what I expected and they often have a very practical approach to problems. Recently, a clinician asked me for help analyzing data from a small investigation. When I proposed several analysis plans using fancy models that would yield (somewhat) complicated results and multifaceted conclusions, the clinician said, “No, no. I need something that physicians can use in the clinic, one simple measure that is easy to use when there are 100 things all happening at once in a busy clinic environment.” I had never really understood the value of results that are easily interpretable and can be applied quickly in the clinical setting.

I have been thrilled to go through a journey from that initial spark of creativity stemming from Cantor’s diagonal argument through a master’s and now onto doctoral training in an exciting, applicable field where I have the opportunity to work with and learn from a diverse array of health professionals.