What Do Trees, Mining, and Random Walks Have in Common?
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 email@example.com, ASA research and graduate education manager.
Theresa Gilligan is a senior health outcomes analyst at RTI-Health Solutions. She earned her Master of Science in analytics from the Institute of Advanced Analytics at North Carolina State University and a bachelor’s degree in psychology from Appalachian State University. She serves as the vice president of the Analytics Alumni Society and is a member of the Analytics Industry Advisory Board.
Trees, mining, and random walks are all key words associated with the emerging discipline of analytics. Analytics helps organizations make sense of large amounts of data by integrating statistical methods and complex processes for better decisionmaking. Those who love analytics get excited about finding patterns, anomalies, and relationships in data. They perform analyses involving predictive modeling, data and text mining, geospatial analytics, forecasting, optimization, simulation, and experimental design. Most important, analytics is an applied discipline that looks at the facts (data and quantitative analyses) to drive decisions.
With the wealth of quantitative information provided by computers and new technologies, analytics has become an in-demand tool in guiding industry. The Institute of Advanced Analytics was founded at North Carolina State University in 2007 to address the growing need for professionals to meet this demand. I was a member of the first class to graduate with my Master of Science in Analytics from the institute. Below, I will answer some of the questions you might have about analytics as a career.
What Level of Education Do I Need?
Most people who apply analytic methods at work have advanced degrees in analytics, statistics, or another quantitative field.
Where Can I Work?
Those studying and applying analytics are found in myriad industries, including consulting, retail, telecommunications, manufacturing, banking and finance, and product development and research.
How Does Analytics Fit?
A background in analytics gives you the option to choose from multiple levels in a company’s structure. The beauty of this discipline is that it plays a role in both mathematical and statistical analyses and decisionmaking. If you prefer the analysis side, you can complete the ‘meat’ of the analyses and work closely with the data. If you prefer the decisionmaking side, you can interpret and use the outcomes of the analytic techniques to inform business and research decisions. Good analysts must not only understand the quantitative analytical methods, but also clearly communicate and explain the output and higher-level concepts to decisionmakers at all levels.
What Would My Job Entail?
You would grow trees, perform mining, and take random walks.
- Decision trees: What are the common characteristics of patients with breast cancer? Create decision trees to visualize a hierarchy of physical and health characteristics associated with a disease. Use this information to decide when to educate and take action to prevent late detection.
- Data mining: How can we predict fraudulent insurance claims? Analyze data to find the patterns associated with existing fraudulent insurance claims. Apply this information to identify potential fraudulent activity and prioritize claims.
- Random walks: Can we predict the electricity usage for tomorrow? Use forecasting to identify electrical use patterns and determine when excess power can be sold to other plants.
What Do You Do with Your Degree?
My MSA degree supports my career as a senior health outcomes analyst at RTI Health Solutions. I work with psychometricians, biostatisticians, and survey researchers to understand the experiences of patients, health-care providers, and other stakeholders. We develop and validate instruments and analyze their health outcomes to drive pharmaceutical product decisions.
I am currently researching text-mining applications to quantitatively support claims from patient interview transcripts. Text mining has the potential to help us extract the frequency of concepts elicited from patients and define relationships between key words and phrases.