A master’s degree in statistics is one of the highest paying master’s degrees, but there are more types of programs in this discipline than you might expect. If you’re having trouble choosing between a general master’s in statistics program and a master’s in applied statistics program, understanding the differences between these types of programs can help.
Focus on Theory vs. Practical Application
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To fully understand just about any area of study, it’s important to learn both abstract theory and practical application. You need to grasp the concepts and theories that form the abstract foundations of the field to truly comprehend how to use these theories. To make a difference in the real world, you also need to learn ways to apply those concepts to solve problems.
Both traditional statistics programs and applied statistics programs will likely involve some amount of coursework in both theory and practical application. The difference is which area your degree program emphasizes. A general statistics graduate program is more likely to focus on theory. This means you will often have to follow a more rigid curriculum that includes more math-based work, such as extra calculus coursework. A master’s in applied statistics program will still cover some foundational theory, but that won’t be the focus of your studies. You are more likely to complete more extensive studies in data science, machine learning, data mining and more.
While a graduate student of general statistics might take a class in linear regression, a student of applied statistics would be more likely to find a class with the title “Applied Regression.” Both general and applied statistics programs tend to cover similar concepts and formulas, because both are, after all, advanced programs of study in the field of statistics. The distinction is whether the program of study places more value on understanding the details of what a concept or formula means and why it is true, or on learning when and how to apply that concept or formula to real-world issues.
While master’s in applied statistics degree programs place more emphasis on practical application than theoretical foundations, that doesn’t mean research is out of the question. Instead, participating in research may be optional rather than mandatory, and the research opportunities that are available to you are likely to be less theoretical and more practical in nature. Many master’s in applied statistics degree programs are non-thesis programs, but not all applied statistics graduate programs have a non-thesis track. You might still be expected to write a thesis or do some other sort of capstone project based on original research or work.
Some applied statistics programs emphasize the practices of conducting research so heavily that they include this aspect in the degree title, with program names like Master of Science in Applied Statistics and Research Methods.
The Amount of Opportunity for Study in Other Disciplines
You can apply statistical concepts and analytical approaches to any number of fields, from healthcare and education to finance and professional sports. However, you need to have enough foundational knowledge of these fields to understand how to use statistics when working in them. Because this depth of knowledge outside of statistics is necessary, students of applied statistics programs are more likely to be encouraged, or even required, to complete coursework outside of their own discipline.
Some possible choices of disciplines you might study to gain breadth while earning a master’s in applied statistics degree are relatively close to statistics, including biostatistics, mathematical finance and bioinformatics. Other popular options, like sociology, psychology, biology and education, may seem farther removed from your core program of study. Each of these fields utilizes statistical methods in its own ways, so while an elective course or two won’t lock you into one career path, it can give you an advantage in breaking into statistical work in that field.
What you want to do with your education should guide your choice in elective and non-program courses. For example, you might take coursework in financial statistics and industrial statistics if you’re interested in a business role or in survey sampling if you would like to apply your statistical knowledge to work and research in the social sciences.
Besides general statistics and applied statistics, there are also master’s degrees in analytics, data science, computational statistics and quantitative finance. An applied statistics program is often a good middle ground between general and highly specialized coursework.