The main difference between Doctor of Philosophy (PhD) programs in applied mathematics and statistics is the kind of math that you study. Both degree programs have similar graduation requirements and lead to careers in research or academia in various fields, but applied mathematics tends to incorporate a broad range of mathematical analysis tools, while statistics programs focus on statistical concepts. Learn more about the different degree programs below.
Comparing a PhD in Applied Math to a PhD in Statistics
PhD in Applied Math
PhD in Applied Mathematics degree programs provide a range of mathematical training that can be applied to various fields, may range from around 54 to 60 credits, and commonly allow students to earn their Master of Science (MS) along the way. Students are usually required to pass a qualifying exam and complete and defend a dissertation. The curriculum typically requires core coursework in applied mathematics that may cover topics such as computational science, analytic methods, numerical analysis, complex variables, and applied functional analysis, as well as coursework in minors or other areas of specialization. Some programs may offer mathematics-related specialization courses, such as courses in combinatorial theory or Fourier analysis, while other programs break up minors into different fields, such as physics, mechanical engineering, or optics. Graduates of doctoral programs in applied mathematics can teach at universities or conduct research and/or mathematical and statistical analysis in their given area of specialization for business, government, and other organizations.
PhD in Statistics
PhD in Statistics degree programs train students in the theories and methodologies specific to statistics and generally take 4 to 5 years to complete. Students may be able to earn their master's as they pursue their PhD and are usually required to pass qualifying exams and complete a dissertation or PhD thesis. Students in the program may also be required to attend seminars, fulfill teaching responsibilities, and/or have the opportunity to gain other hands-on learning experience through courses like consulting workshops where students provide consulting services to the community. Curriculums for these degree programs typically require some core statistics courses in topics such as linear models, statistical modeling, and theoretical statistics, followed by electives or advanced statistics classes with topics including stochastic processes, probability theory, Monte Carlo, applied statistics, and more. Graduates of these degree programs are prepared for careers as researchers, consultants, or educators in the field of statistics.
Common Entrance Requirements
Applicants to both a PhD in Applied Mathematics or PhD in Statistics program must have at least a bachelor's degree, but some programs may require applicants to hold a master's degree if they are applying directly to the PhD program and not the MS to PhD. Some statistics programs may also require that the bachelor's or master's degree be in statistics, mathematics, or another related field. Both programs also typically require GRE test scores and may require a minimum GPA. Applicants to applied mathematics programs may need to have a certain number of undergraduate hours in mathematical sciences, but statistics programs may require specific coursework in topics like calculus, statistics, linear algebra, and programming. Common application materials for either program include transcripts, letters of recommendation/references, a resume or curriculum vitae, and a personal statement.
Students can pursue a PhD in Applied Mathematics or a PhD in Statistics to work in research and analysis positions in various industries. Both programs typically require a dissertation, but applied mathematics programs generally include additional areas of specialization, while statistics programs focus on subjects in the field.