Find your perfect college degree
Statistics is a field that has grown more relevant today because of the growing footprint of big data and, subsequently, data science and machine learning. But before big data in the information and computing sciences, data has always been the primary currency of statistics.
A Doctor of Statistics degree is a postgraduate degree program designed to offer students an in-depth understanding of quantitative methods, theories, and applications. Students learn about principles of data modeling, including probability theory and multivariate calculus, the development of statistical models, algorithms for inference, and data analysis.
They also learn about the application of data analysis in organizations and industries, including the healthcare, finance, insurance, telecommunications, and education sectors.
This discipline encompasses data collection, sampling, analysis, and interpretation. The discipline also touches on experimental design, simulation of conditions, computational analysis, predictions (through the concept of probability), and many more.
In addition to coursework, students often take part in industry internships and collaborative research opportunities. Doctoral programs in Statistics typically culminate in a comprehensive dissertation or research project.
With a Doctor of Statistics degree, professionals are prepared to pursue top jobs in academia, government, industry, and commerce.
Quick audio summary:
This elemental nature of statistics is what makes it versatile across industries, from agriculture to food science, to natural sciences like botany, geography, oceanography, and even meteorology, to engineering and the applied sciences, medicine, life sciences, athletics, and of course, social sciences, which is one of the first disciplines to utilize statistics.
Aside from providing empirical and quantitative results, it can also create simulated environments for intangible sample data, where the conditions affecting the data cannot be captured physically or in real-time.
An example would be statistical research involving meteorology, anthropology, microbiology, and even social science, where quantifying human behavior remains an ever-expanding and evolving domain.
Statistics also help government agencies and policy-making institutions do just that and form evidence-based policies and regulations based on quantitative data.
Check out this career guide on becoming a Statistician:
METHODOLOGY
For the top Doctor of Statistics Graduate Schools, we’ve based our selections on the following points:
- Preference is given to schools with active research and initiatives across other disciplines or departments. The involvement may be at the faculty level or the department level through the availability of research centers and institutes or their affiliations.
- Preference is also given to programs with a long roster of faculty involved in research, whether in core or theoretical statistics research or interdisciplinary work. It is valuable for students looking to engage with a prospective adviser as they prepare for dissertation work. A faculty with vast experience in a similar discipline or field of study as the student’s budding research will help the student be nudged in the right direction regarding references, insights, and overall study design.
- Preference is also given to programs that offer statistical consultancy services, as most of these initiatives are helmed by graduate students themselves, thus allowing them to work with non-statisticians within a project.
- Additionally, a factor in the rankings is its Ph.D. completion census over the last ten years, as collected by the National Center for Education Statistics (NCES) and published by the American Statistical Association (ASA).
For more information, see our Methodology page.
20 BEST DOCTOR OF STATISTICS GRADUATE SCHOOLS
Boston University
Boston University (BU) was established in 1839 in Vermont before moving to its permanent home in Boston, MA. Shortly after, one of its faculty members successfully invented the telephone in one of its laboratories – Alexander Graham Bell in 1876.
BU is classified as an R1 research university. It has also produced several acclaimed scholars and graduates – from Nobel prize laureates to MacArthur fellows to Pulitzer winners.
- BU’s Ph.D. program comes in three tracks: Statistics, Probability, and Mathematics.
- Students under the statistics track must complete at least eight core courses at a Ph.D. level proper. Those who have not earned a master’s degree yet must complete sixteen courses, with a maximum of four courses allowed for transfer.
- Proficiency in at least one foreign language—French, German, or another major foreign language—is required.
- Students must complete the following coursework in sequence: Probability Theory I and II, Estimation Theory, Hypothesis Testing, and Advanced Statistical Methods I and II.
- To qualify for doctoral candidacy, they must satisfactorily complete the exams on applied statistics, mathematics, and probability.
Standout Features of the Program:
BU is committed to funding students’ first five years of doctoral study, which, with good academic standing, could go longer than that. In addition, first-year students are eligible for teaching fellowships and the Dean’s Fellowship. Both provide an annual stipend of $23,340, on top of an $11K stipend for the summer term.
Doctoral students in statistics are eligible for a free membership from the Society for Industrial and Applied Mathematics (SIAM), the American Mathematical Society (AMS), and the Association for Women in Mathematics (AWM). They can also avail themselves of discounted memberships from the ASA and other related professional societies.
North Carolina State University
NC State’s Department of Statistics was established in 1941 with statistician Gertrude Cox, famous for pioneering the statistical tenet Experimental Design, at the helm. Its graduate program would later become a research powerhouse, posting great numbers in post-grad career placement.
From 2003 to 2020, NC State has surpassed other universities for the total number of Ph.D. in Statistics degrees conferred, with 332 graduates. It has also topped the list for 2019 and 2020, with 23 and 25 graduates, respectively.
- The Ph.D. in Statistics program requires the completion of 54 to 72 credit units (depending on where the student earned the master’s degree), which combines coursework and a dissertation.
- The featured required courses in Statistical Consulting expose students to professional consulting activities involving the faculty and prospective or current clients.
- Aside from the usual funding sources – TA, RA, fellowship, and grants – a Graduate Industrial Traineeship (GIT) is a unique funding opportunity made possible by the department’s collaborations with government and private firms.
Standout Features of the Program:
Stat Ph.D. students looking to apply to the GIT funding program can apply to the multi-industrial facilities and companies at Research Triangle Park. This economic hub, which has a longstanding partnership with NC State, can also be a good jump-off point for a career after grad school.
The best-selling statistical software SAS was developed at NC State as a project of the Department of Agriculture in 1966. Ten years and 100 clients later, the founding developers established the SAS Institute, one of the biggest private software companies globally and a major benefactor of the SAS Hall, which houses the Department of Statistics.
Purdue University
The Purdue Department of Statistics is well represented in various mathematical and statistical professional circles, such as the Institute of Mathematical Statistics (IMS), the American Association for the Advancement of Science or AAAS, the International Statistical Institute (ISI), an NSF CAREER award, with five Department of Statistics alumni emerging as winners from 2009 to 2012. Also, two of the department’s professors emeriti have sat as president of the ASA, which welcomed nine fellows from Purdue.
- Applicants to the Ph.D. in Statistics program must have a working knowledge of probability, mathematical statistics, and regression.
- The program is as follows: four qualifying exams covering the core coursework, followed by a preliminary exam to determine the student’s readiness for research. A final examination or oral dissertation defense follows.
- All doctoral candidates must hold at least one semester-long teaching experience.
Standout Features of the Program:
Statistics Ph.D. students can avail of the vast IT resources available both at the department and university levels. At least 35 servers running on Ubuntu OS are available, with the largest having 168 TB to boot. Software programs running on R and Python are also available, and statistical computing applications like SAS, Matlab, and Minitab.
At least six interdepartmental research groups are conducting investigative work with Discovery Park, Purdue’s very own research hub. These research groups represent the department’s collaboration with other disciplines like medicine, bioengineering, environmental science, entrepreneurship, and biosciences.
Florida State University (FSU)
Founded in 1959, the FSU Department of Statistics was home to famous statisticians, such as Richard Savage and Frank Wilcoxon. Today, its faculty has expanded the department’s accolades through fellowships in professional societies, holding editorial roles in peer-reviewed journals, and receiving government grants, such as those from the National Science Foundation (NSF).
- The Department of Statistics offers two tracks towards the doctoral degree: the Statistics and Biostatistics track.
- Students in both tracks must take the Ph.D. qualifying exams for the following courses: Statistics in Applications I and II, Distribution Theory, Statistical Inference, and Advanced Probability and Inference I. Additionally, Computational Methods in Statistics and Epidemiology for Statisticians are required for Statistics majors and Biostatistics majors, respectively.
- An essay exam for doctoral candidacy admission and oral defense for the dissertation are required for both tracks.
- Students are also required to document their participation in extracurricular activities such as colloquia, utilization of all physical facilities, interdepartmental or group research, and other academic and professional experiences. These are all required for program completion as well.
Standout Features of the Program:
The department encourages students to pursue interdisciplinary investigative work. The interdisciplinary option requires students to take at least three additional courses in the secondary discipline of choice in preparation for the research work. Additionally, the Supercomputer Computations Research Institute is at the student’s disposal for research requiring complex computations.
The Department of Statistics is currently involved in several types of interdisciplinary research involving oceanography, meteorology, and engineering. Two faculty members of the department are currently studying the application of nonlinear time series models in predicting climate changes and forecasts.
Ohio State University
The Department of Statistics at OSU was established in 1974, although the discipline has been in existence since the ’60s through the Department of Mathematics and the Statistics Laboratory. It would later develop and offer interdisciplinary programs such as biostatistics and data analytics in the succeeding decades.
- Applicants to the Ph.D. program in Statistics must have a solid background in Applied Mathematics, Advanced Calculus, and Real Analysis.
- Students must take a course on either Statistical Consulting and Collaboration or Biostatistical Collaboration on top of the required core courses.
- Once admitted to doctoral candidacy, attendance to departmental colloquia is required.
- There are four exams: two qualifying exams for the coursework, the doctoral candidacy exam, and the oral dissertation defense.
Standout Features of the Program:
Students can utilize the 11 computers housed by the department, which run on both Linux and Windows servers. They also have access to the Ohio Supercomputer Center and various statistical software programs like SAS, SPSS, Mathematica, and many others.
The Department also offers an alternative Ph.D. program for statisticians interested in interdisciplinary work. The Interdisciplinary Ph.D. program in Biostatistics is a joint offering from the Department of Statistics and the College of Public Health. It offers two concentrations: Methodology and Public Health.
University of Arizona
From UA’s College of Mines to the School of Mathematics, math and statistics have been deeply embedded into the university curriculum as early as the late 19th century.
Known today as the Department of Mathematics, its programs are strongly founded on research and interdisciplinary activity, particularly statistics, data science, engineering, and biosciences (biostatistics).
- The department offers two tracks for its Ph.D. in Statistics offering – the regular and the statistical informatics track. Both require the completion of 71 credit units, which includes an 18-unit dissertation.
- The following are the standout curriculum features for each of the tracks:
- Regular:
- Core courses include Theoretical Statistics and Theory of Linear Models
- Of the 50+ elective courses available, at least 12 elective units are required
- Statistical Informatics:
- Core courses include Statistical Machine Learning
- Elective requirement: at least 21 credit units are required. The choices of electives are grouped as follows: general, bioinformatics, business and management informatics, computing, geographic information systems, medical informatics, and an individualized theme as per department approval. Six units should come from the general group and another six units from the other course groups. The rest of the remaining units can come from any of the seven-course groups.
- Regular:
- Both tracks require students to take Scientific Writing Presentation and Bioethics, Statistical Computing, and Scientific Grantsmanship courses.
Standout Features of the Program:
A Ph.D. minor is required for both tracks. At least three units are required under any of the following minors:
- Computer Science
- Mathematics
- Applied Mathematics
- Ecology and Evolutionary Biology
- Biostatistics
- Information Resources and Library Science
- Agricultural and Biosystems Engineering (available with the informatics track only)
Applicants to either Ph.D. in Statistics program are required to have the following:
- Have taken multivariable/vector calculus courses (worth at least three semesters),
- Have taken a course on linear algebra, and,
- Has solid experience in computing systems and processes, such as data analytics and mining, among others.
University of California Los Angeles (UCLA)
The discipline of Statistics at UCLA started from four academic channels during the 1930s: the Departments of Mathematics, Biostatistics, and Biomathematics, and the Division of Social Sciences.
The Department of Statistics would later be launched more than fifty years later in 1998, boasting programs and research that combine theoretical and computational coursework with interdisciplinary applications.
- Aside from mathematics and statistics, preference will be given to Ph.D. applicants with solid backgrounds in computer science, engineering, and other related disciplines like public health or bioinformatics.
- The core of the curriculum is structured into theoretical, application, and computational courses related to the discipline.
- Admission to the Ph.D. program is only every fall term.
- Students are also required to render teaching assistantship services for at least one term.
Standout Features of the Program:
Students can choose to research the following areas under which many of the Statistics faculty have done their research:
- Experimental design
- Environmental Statistics
- Computational statistics, which includes AI and machine learning
- Social statistics
- Bioinformatics
- Applied multivariate analysis
Students can choose to engage with faculty who have researched any of the following areas in an advisory or consultancy role.
The Department is home to three research centers that collaborate across different disciplines to produce studies and literature that demonstrate the value of statistics in these different industries. These are the:
- Center for Statistical Research in Computational Biology, where statistics intersects with health and life sciences
- Center for Vision, Cognition, Learning, and Autonomy, where statistics intersects with information systems and adaptive technologies, and,
- Center for Social Statistics, where statistics intersects with its oldest collaborators – the social sciences and related disciplines.
Virginia Polytechnic Institute & State University (Virginia Tech)
The Department of Statistics was established in 1949. The department offers Statistics programs that are well-rounded, touching on every industry and other possible applications of the discipline.
- The Ph.D. in Statistics program offers relevant cross-industry concentrations, such as:
- Sports Analytics
- Biostatistics
- Statistics for Business, Government and Industry
- Environmental Statistics
- Computational Statistics
- General Methodology and Theory (classical track)
- It requires the completion of 90 course credits, which combines coursework and research for both the master’s and doctoral levels.
- Ph.D. students are required to render teaching duties for one term and to undergo three semester-long professional training. The training involves exposure to statistical collaboration under a relevant industry based on the student’s choice of concentration.
Standout Features of the Program:
The department has bilateral partnerships with multinational companies such as Shell and Capital One. Employees from partner companies can avail of the courses for free or pursue a statistics degree at a reduced rate. VT graduates can take advantage of this partnership to leverage themselves and their credentials for career placement.
Recognizing that Statistics is not for everybody, the department offers two offices that offer free tutorial and consultancy services for non-statisticians. The STAT Lab (Statistics Tutoring All Together) is a free tutorial service helmed by statistics graduate students for statistics undergraduates. On the other hand, the Statistical Applications and Innovations Group (SAIG) is a consultancy office that offers free statistical aid to VT students, faculty, and staff outside the department. It also offers free short courses, such as utilizing R software and machine learning.
University of Michigan Ann Arbor
U-M’s Statistics program has consistently been hailed as one of the best in the country, ranking among the top 10 across all school-ranking publications, including the National Research Council’s 2010 rankings.
The department has always collaborated with other U-M departments and schools, such as but not limited to the Ross School of Business and the Department of Industrial & Operations Engineering, to offer a holistic and relevant Statistics program at all levels.
- Ph.D. students must meet the requirements of the following course groups as follows:
- All courses under the “Methods” and “Practice” groups must be completed
- At least two courses each must be completed under the “Statistical Theory” and “Probability” groups
- At least one course must be completed under the “Computing” group
- The following courses are also required: Research Ethics and Introduction to Research Tools, and, Technical Writing in Statistics.
- A minimum of three cognate courses or non-statistic and non-departmental courses are also required before taking the doctoral candidacy exam.
Standout Features of the Program
The NSF recently awarded the department a research training grant to study modern methodologies for analyzing dynamic and complicatedly structured big data, which is ubiquitous today, thanks to social media. It also aims to train U-M students of all levels, from undergraduate to post-doc, on these new techniques and subsequently apply them to their research or professional work.
The Ph.D. in Statistics student council actively maintains a Wiki page for all things statistics and its relevant applications and developments. Access to this page requires a U-M online login credential.
University of Wisconsin Madison
UW’s Department of Statistics was instituted in 1960. Since then, it has conferred close to a thousand graduate degrees, with about half being doctoral degrees. The department prides itself in offering research and training programs, thus preparing graduates of the discipline for statistical work or research in any industry or field.
- The Department offers two Ph.D.-leading tracks: Statistics and Biostatistics tracks. The application process for both tracks is uniform, and students can switch tracks seamlessly.
- GRE scores are currently not required for application for the Fall 2022 term.
- The documentary requirements for the application are transcripts, CV, letters of recommendation, a statement of purpose, and supplemental information as required by the online application. All documentary requirements should be submitted online.
Standout Features of the Program:
The faculty of the Department of Statistics is also associated with the Departments of Mathematics, Computer Sciences, Electrical and Computer Engineering, and Botany. Students looking to engage in interdisciplinary research are very fortunate to have many faculty members as advisers because of their breadth of knowledge and expertise that spans beyond statistics.
In line with the department’s longstanding tradition of collaborative work within UW, it is currently involved in five interdisciplinary initiatives. These are:
- Biometry – a collaboration with the College of Agricultural and Life Sciences (CALS), which also houses the Statistical Consulting Service, which aids all UW students with their statistical and computational needs
- Biostatistics and Medical Informatics
- Machine Learning for Medical Imaging (ML4MI)
- Data Science Hub
- Institute for Foundations of Data Science
Iowa State University
ISU’s Department of Statistics has its roots embedded in the Iowa Agriculture Experiment Station when the latter instituted the Statistical Section in 1935, later becoming the Department of Statistics.
Since 2000, the department has consistently ranked among the top 10 statistics programs in the country regarding research activity (especially interdisciplinary research), curriculum rigor, job placement, and student census.
- The Ph.D. program in Statistics requires the completion of 72 credit units.
- To be admitted for doctoral candidacy, students must complete the preliminary exams, one written and one oral. The oral prelims represent the dissertation topic proposal.
- The minimum required coursework for students who have already earned a master’s degree coming into the Ph.D. program consists of the following courses:
- Foundations of Probability Theory
- Advanced Probability Theory
- Advanced Statistical Methods
- Advanced Theory of Statistical Inference
- Plus 9 to 12 elective credits.
Standout Features of the Program:
Students can opt to co-major in another area or discipline while also pursuing a doctorate in Statistics. It has been a common pathway for many students who are keen on interdisciplinary studies. The common co-majors include engineering, agriculture, genetics, and computer science.
With this option, students will have to choose a Statistics track that is more relevant to the second major, Applied Statistics or Theoretical Statistics.
The department is home to three research centers that collaborate across the academic ecosystem, such as forensic science, health informatics, botany and biology, and experimental design, to push the envelope and demonstrate the value of statistics in fields that require statistical analysis to derive empirical results.
Stanford University
Stanford’s Department of Statistics has always been motivated by interdisciplinary collaboration since its establishment in 1948. As a start, two members of its pioneering faculty are also affiliated with the Departments of Psychology and Economics – Quinn McNemar and Kenneth Arrow, respectively.
The succeeding decades saw the continuation of joint faculty appointments, which resulted in the seamless integration of Stanford Statistics with other schools and departments like Engineering, Medicine, Liberal Arts, Natural Sciences, Business, and Food Science.
- The doctoral program in Statistics requires the completion of 135 credit units, with at least ten units taken every term. Stanford observes a quarter-term academic calendar.
- Students are advised to gain mastery of the following subjects before embarking on the core courses:
- Linear algebra
- Matrix theory
- Real variable functions
- Probability theory
- Statistical Inference
- Python Programming
- For doctoral candidacy admission, students must pass two of the three exams in the following areas: theoretical statistics, applied statistics, and probability theory.
- To prepare students for interdisciplinary work, they must take at least three courses in a discipline that is outside yet relevant to statistics, like engineering, information science, social science, natural science, biology, or mathematics.
Standout Features of the Program:
While Stanford observes a quarter system, students of the Department of Statistics are not required to be in residence or enroll for the summer terms, except for first-year students. Despite this, the department still holds lectures and other campus sessions, with which students can electively attend.
Stanford Statistics emphasizes the increasing value and relevancy of interdisciplinary research. It strongly encourages its students to join such projects or research groups, or form their own, as the department has received generous funding from the NSF for this very purpose.
University of Connecticut
UConn’s Department of Statistics was instituted in 1962, with a faculty of seven professors. Today, most of its 23 professors are recipients of NSF and NIH grants. They are also recipients of the Microsoft Azure Research Award and the prestigious NSF CAREER Award.
- Doctoral students in Statistics are required to complete 18 courses, especially those coming from the undergraduate level.
- They are also required to take the following core courses:
- Mathematical Statistics
- Applied Statistics
- Linear Models
- Theory of Statistics
- Measure Theory and Probability Theory
- Design of Experiments
- Investigation of Special Topics
- As for the electives, students are strongly encouraged to look into Biology, Computer Science, Mathematics, or Economics courses. One to two courses should suffice.
- The department will provide funding for 4 to 5 years (maximum).
Standout Features of the Program:
The faculty of the Department of Statistics is composed of 20+ professors with a vast breadth of experience in interdisciplinary research; from theoretical statistical subdisciplines like multivariate analysis, probability, and statistical computation to interdisciplinary statistical approaches such as biostatistics, bioinformatics, statistical genomics or econometrics, there is no shortage of research advisers from the department, regardless of the student’s chosen field of study or research.
Ph.D. Statistics students lend their time to the Statistical Consulting Service (SCS), which fields inquiries from UConn and non-UConn clients. From experimental design to grant writing assistance, data modeling, statistical computation, and analysis results in interpretation, or software troubleshooting, the SCS team, is ready to assist statistically, regardless of the nature of the research or project. Simple queries are free of charge, while project engagements usually cost $40 per hour.
The University of Chicago
UChicago’s Department of Statistics was formally launched in 1949 with two main objectives: providing further insight into advanced statistics through research and applying statistics in other fields of study.
Today, both the faculty and the students are guided by these same motivations as they expand the utilization of statistics to modern disciplines (such as adaptive technologies and medicine) beyond the traditional ones (natural and social sciences).
- Students in the Ph.D. in Statistics program are required to take the following courses during their freshman year:
- Applied Statistics
- Probability
- Mathematical Statistics
- Computational Mathematics and Machine Learning
- Each course is accompanied by a preliminary exam held at the beginning of the sophomore year.
- The program takes as short as three to five years.
- Applicants to the Ph.D. program are encouraged to develop a solid background in advanced mathematics courses like calculus, linear algebra, and real analysis. Experience in computer programming and another discipline that involves empirical data analysis is also preferable but not required.
Standout Features of the Program:
The faculty of the Department of Statistics built a portfolio of work intersecting the fields of biostatistics, neuroscience, genetics, machine learning, chemistry, environmental science, econometrics, and finance.
The department offers free statistical consultative services to other UC students or faculty members who need statistical assistance with their projects.
Helmed by the department’s graduate students, mostly doctoral candidates, the services are confined to theoretical and applied statistical insight at every level of research – from experimental design, sampling, prediction, computation, and simulation to interpretation. Statistical software assistance or troubleshooting is not included in the service.
Carnegie Mellon University
Ph.D. in Statistics (regular and joint degrees)
In 1966, CMU instituted the Department of Statistics (now known as the Department of Statistics and Data Science) and consistently produced graduates with advanced degrees. The introduction of joint Ph.D. degrees started in the mid-’90s, with Public Policy and Machine Learning as the pioneer offerings.
- Aside from the regular Ph.D. in Statistics program, the department also offers dual Ph.D. degrees with the following options for the second doctorate:
- Engineering and Public Policy – where statistics meets risk analysis in formulating policies governing communication technology infrastructures, sustainable resources policies, and overall R&D regulations.
- Neural Computation – where statistics meets neuroscience experiments involving cognition, among others.
- Public Policy – where statistics meets research that forms the basis for various public policies for various sectors and industries.
- Machine Learning – where statistics meets computational science and data analysis in the design of experiments to further develop adaptive technologies.
- The core coursework comprised of seven courses is required for all Ph.D. students.
- All Ph.D. students must complete an Advanced Data Analysis (ADA) Project, which is different from the dissertation requirement. One of its objectives is for students to learn to effectively engage and work with non-statistical professionals on any project of any nature.
Standout Features of the Program:
Before a student can deliver a dissertation proposal, they must first demonstrate a forte, or an “Area of Strength,” a course or a subdiscipline where they excel with exemplary grades as proof. Common “areas of strength” demonstrated by previous students include theoretical, applied, and computational statistics.
Unlike other Statistics programs in the country, the department does not require qualifying exams for coursework competency and doctoral candidacy admission.
Cornell University
Statistics at Cornell University has been taught since pre-WWII. The discipline grew from then on and can be attributed to the different notable faculty who came in and subsequently left, like Prof. Jacob Wolfowitz, who pioneered the concept of interdisciplinary collaboration.
This led to the decentralization of the field within Cornell, with various statistic research groups existing in different departments. In 2005, the Department of Statistical Sciences was formally launched, housed by the Faculty of Computing and Information Science (CIS).
- The Ph.D. program in Statistics requires applicants to have, at the very least, taken coursework or have a solid background in statistics, computer science, or advanced mathematics.
- Upon satisfactory completion of the required coursework, students must undergo two exams: one for doctoral candidacy admission (A exam) and one for dissertation defense (B exam).
- Applicants with only a bachelor’s degree are also accepted, as the program also confers a master’s degree in statistics, but not as a terminal degree, but rather as a continuing degree towards the doctorate.
- Admission is only every fall term. Tuition costs $20,800. Two to four recommendation letters are accepted, and GRE scores are also recommended (confirm with admissions if this is optional).
Standout Features of the Program:
Students are required to run their computations and other modeling tasks via the statistical software program SAS. Software licenses can be purchased through the Cornell licensing store and are valid for one year. SAS runs on either Linux or Windows platforms.
The department houses a collection of previously accepted dissertations along with the post-Ph.D. career information of the student-authors. This page is a valuable resource for students preparing for their dissertations or career jump points after earning a doctorate.
University of California Berkeley
Berkeley Statistics, founded in 1938, has always been at the forefront of research and interdisciplinary innovation. Proof of this is its highly acclaimed faculty, many of whom are National Academy of Science members, MacArthur Genius Grant winners, and recipients of the prestigious National Medal of Science.
- Ph.D. in Statistics students are expected to take courses on Theoretical and Applied Statistics and Probability during their first year of study.
- The program offers two emphases or concentrations:
- Computational and Data Science and Engineering
- Computational and Genomic Biology
- Students are required to hold in-campus residence for four semesters.
- Students need to complete only one qualifying exam, the one for doctoral candidacy admission.
Standout Features of the Program:
During the summer term of the first year of study, students are required to participate in any of the following activities:
- Graduate teaching assistantship
- Internship
- Reading course
- Short research
- Other relevant research activities will be performed as approved by the department.
The recently opened residence hall for first-year students, Blackwell Hall, was named after one of Berkeley Statistics’ founding fathers – David Blackwell. He is also the first professor of African-American descent to be granted tenure status at the university.
Pennsylvania State University
By the numbers, Penn State Statistics is indeed a powerhouse in the discipline, particularly in scholarly research. Eighteen of its faculty are elected fellows of the ASA, ISI, and the AAAS, members of the National Academy of Sciences, and National Medal of Science award recipients.
- The doctoral program in Statistics offers the following concentration areas:
- Biometrics
- Geometrics
- Statistical computation
- Statistical ecology
- Environmental Statistics
- Biostatistics
- Only one preliminary examination is required, the one for doctoral candidacy admission. The exam tests the student’s competency in probability, applied and theoretical statistics, and the Monte Carlo methods.
- Students are expected to undertake a written and oral exam for the dissertation proposal by the second and third years.
Standout Features of the Program:
A dual Ph.D. degree option is also available. There are two programs to choose from:
- Operations Research – which combines research techniques from engineering, economics, mathematics, and the sciences. This second major should be useful for Statistics doctorates who aspire to focus on experimental design and simulations.
- Social Data Analytics – largely draws from social science and data science to formulate methodologies to ethically extract, analyze, and utilize big data, both a predictor and an upshot of human behavior online.
Students can apply to any of these degrees once they have been admitted into the Statistics Ph.D. program. A separate admission committee and chair govern each of the programs.
Penn State Statistics has consistently ranked among the country’s and the world’s best programs. The National Research Council recognized it among the top 15 in 2010, while a more recent world ranking, the 2019 Academic Ranking of World Universities (ARWU), pitted the program as the 23rd best in the world.
Columbia University
Long before the department’s inauguration in 1946, statistics had already been taught at Columbia for more than a decade. The department started with four faculty members and conferred its first Ph.D. degree in 1947.
In the early 2000s, it saw an unprecedented rise in enrollees, forcing the department to relocate after it already did once during the ’60s.
- The Ph.D. in Statistics program usually spans four to six years, which culminates with a dissertation. Only full-time enrollment is allowed.
- Applicants must have a working knowledge of linear algebra and advanced calculus.
- Doctoral students can expect full funding for up to five years, provided good academic standing. Other funding sources are fellowships, TA and RA work, and travel subsidies for conferences and other academic activities outside Columbia.
- A dual-degree option is also available. Some of the viable options include:
- A J.D./Ph.D. option
- An M.D./Ph.D. option
- An additional concentration in Mathematical Structures for Environmental and Social Sciences to complement the doctorate in Statistics.
Standout Features of the Program:
The department is affiliated with three research centers:
- The Applied Statistics Center, which is under the Institute of Social and Economic Research and Policy,
- The Center for Applied Probability, which is under the School of Engineering and Applied Science, and,
- The Grossman Center for the Statistics of Mind pursues studies on neuroscience while utilizing statistical methods.
The department offers a free statistical consultancy service exclusive to students, faculty, and staff of Columbia University. Engagements are on an appointment basis and can be booked by emailing consult@stat.columbia.edu. It is advised to lead with the following pertinent information in the email for expedited service:
- Specific consulting service needed (e.g., experimental design, computation, analysis, interpretation, etc.)
- Source of data and the collection method employed
- Objectives of the research project
- Statistical methods employed and software used (if any), and,
- The timeline of the project.
Texas A&M University
TAMU’s Department of Statistics was established in 1962 with two main objectives: expanding statistical research and conferring graduate degrees under the discipline.
What started as a class of 12 graduate students and five faculty members had grown into a thriving department of 44 faculty members deeply involved in both core and interdisciplinary or collaborative research.
- Depending on the student’s educational attainment, the Statistics program’s required coursework ranges from 96 to as little as 42 credit units, including a 4-unit seminar and a 2-unit statistical consulting requirement.
- The statistical consulting requirement spans two terms and must be completed before the end of Year 4.
- Five of the seven core courses will be covered in the oral qualifying exam for doctoral candidacy admission. These are Statistical Computations, Statistical Methodology I and II (Bayesian Modeling), Probability, and Theory of Linear Models.
- Residency is also required for admission to candidacy. The minimum residency is two successive terms or one academic year.
Standout Features of the Program:
The department is involved in several interdisciplinary studies in agriculture and toxicology, among many others. It is also instrumental in the establishment of the Center for Environmental and Rural Health. It is funded by the National Institute for Environmental Health Sciences – NIEHS. The renewal of the university-wide Superfund Basic Research Program is funded by the Environmental Protection Agency (EPA).
Aside from the department’s active initiatives in interdisciplinary research, it also houses the Center for Statistical Bioinformatics, which receives generous funding from four national agencies: the National Cancer Institute (NCI), NSF, the National Human Genome Research Institute – NHGRI, and NIEHS. The department is also affiliated with the Institute for Applied Mathematics and Computational Science.
FREQUENTLY ASKED QUESTIONS
Why pursue a Ph.D. in Statistics?
Recent BLS data projects the median annual salary of statisticians and mathematicians at $99,960, which is just for those who have attained a master’s degree.
With the academic and research pedigree of a doctorate, this figure will skyrocket, especially since the demand for statisticians across industries grew by 30% in 2022, and this projection is expected to go higher as economies and industries reopen.
Most universities, especially those listed below, do not offer terminal master’s degrees in Statistics but rather a continuing degree leading to a doctorate. The master’s degree is conferred once the student becomes a doctoral candidate.
The short answers to this question? One, because an advanced degree in Statistics can command a high salary, and two, most graduate programs in Statistics lead to a Ph.D.
What is the difference between Statistics and Mathematics?
Statistics were used to be recognized as a subset of Mathematics. The former, however, has grown into its own discipline as it has become an integral part of various industries that rely heavily on scientific investigations.
The need for real-world integration of the quantitative results also helped statistics grow into its discipline, compared to mathematics’s abstract and theoretical approach. Its heavy utilization of electronic and computational methods also demanded a different methodology distinct from its parent discipline.
It is still safe to say that mathematics, to some extent, subsumes the discipline of statistics, particularly theoretical statistics. However, applied and computational statistics do warrant the argument for statistics being its discipline because of its varied applications, methodologies, and requirements.
Who can apply to the program?
Both bachelor’s and master’s degree holders can apply to a Ph.D. program in Statistics, provided they have a working knowledge of advanced mathematics courses, which is usually the trifecta of Advanced Calculus, Linear Algebra, and Real Analysis.
Knowledge in real variable functions, elementary statistics and probability, experimental design (if the applicant is coming from an applied science program), and programming, particularly Python and R, are not usually required but are advantageous.
Are GRE scores required? What are the other admission requirements?
Most of the programs listed below do not require GRE scores for the 2022 applications. Other admission requirements include transcripts, CV, letters of recommendation, an essay, and a TOEFL exam.
What are the usual degree requirements?
Most of the programs listed below follow the following flow:
- Required coursework completion
- First preliminary examination to test for coursework competency
- Second preliminary or qualifying examination for doctoral candidacy admission, which includes the dissertation proposal
- Final examination, which includes the oral dissertation defense
- Acceptance of the dissertation by the committee, which signifies program completion or graduation.
Some programs may only require one qualifying exam, which is for doctoral candidacy. The final examination for the dissertation defense is a staple among all Statistics programs. Other requirements for graduation include participation in colloquia, seminars, consultancy, short research projects, and internships. There is also a residency requirement.
Do I need to be an expert in Mathematics to excel as a Statistician?
No, you do not need to be an expert in mathematics to excel as a statistician. Having a general knowledge of mathematics is helpful; however, much of the work that statisticians do does not require advanced knowledge of complex mathematics. A lot of the work relies on statistical techniques and software programming.
