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The Importance of Statistical Science

Every day, reports and news articles announce that we live in the era of “big data.” Advances in computing power and cloud technology, the rapid proliferation of technology enabled devices, and the sheer amount of human activity that is now captured and tracked by banks, stores, social media networks, fitness trackers, and navigation systems has created an explosion of data. There seem to be countless ways to gather information about the natural and digital worlds.

However, data is not the same as knowledge. Without context to understand what types of data are valuable, what makes data reliable, and what the data signify, data are useless. Moving forward, the field of statistics will be increasingly fundamental to academia, business, and government as they seek to make sound, data-driven decisions.

What is Statistical Science?

The science of statistics is the science of collecting, analyzing, and interpreting data.

Long before the proliferation of data, scientists and decision makers in healthcare, government, and business relied on statistics. Statistical science is a branch of mathematics; it provides the theories and methods that are needed to appropriately plan experiments, collect reliable data, and arrive at accurate conclusions about results. Without statistics, there is much less certainty about which data and conclusions are trustworthy.

Because data impacts all areas of learning and life,
statistics is truly an interdisciplinary science.

Why Study Statistical Science?
A Look at Trends and Opportunities in the Field

Because of the explosion of data from devices such as sensors, cell phones, and medical instruments, as well as from business processes, surveys, and social media, there is accelerating demand for specialists who are trained in data collection and analysis.  

“Statistics is concerned with how to design and analyze studies to efficiently acquire reliable information about the world around us.  Its principles are relevant to practically every form of human endeavor, but as it is a difficult subject to master, many disciplines have been slow to adopt statistical thinking.  

For these reasons, there is a strong and growing demand for people who can explain statistical concepts and apply them in science, commerce, and government. Our future has never been brighter.” 

— Dr. Daniel Heitjan
, Professor and Chair

Why study statistics? Learn why & how to study statistical science —
read the full interview with Dr. Heitjan.

A Booming Job Market for Statisticians

The job prospects for those who study statistical science have never been better. Here’s a quick overview of the career outlook for statisticians:


The employment of statisticians is projected to grow 31 percent from 2021 to 2031, much faster than the average for all occupations.



A career as a statistician is currently ranked as #10 in Best Business Jobs, #16 in best STEM jobs and #30 in 100 Best Jobs by U.S. News and World Report.



The mean annual salary for statisticians with a PhD is $116,000.


Where Do Statisticians Work?

Your work as a statistician can be combined with nearly any other field of interest — from sports to astronomy, zoology to national defense. Statisticians address a wide variety of problems in many industries which makes careers in statistics financially rewarding and intellectually challenging. A statistician will never be bored!

What Do Statisticians Do?

  • Work for government agencies, such as the Census Bureau and Food and Drug Administration,
  • Assist in modeling financial data for banks and insurance companies,
  • Design studies and analyze data related to healthcare at medical schools, research hospitals, and pharmaceutical companies
  • Utilize techniques and statistical models to help the tech industry, in particular computer scientists, make sound decisions about data and even enhance algorithms.

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Here’s What Statistical Science Research Looks Like

Our talented group of faculty and graduate students are producing innovative research in the fields of statistical science and biostatistics.

Check out these samples of faculty and graduate student research to get a sense of the type of work you could do as a graduate student in statistical science.

Two Special Statistical Science Research Projects Taking Place at SMU

1. Geometric and Topological Data Analysis —  A defining characteristic of many modern data applications is their unstructured nature. The basic unit of analysis could be something other than a traditional observation, such as regular arrays with fixed numbers of rows and columns and a single observation in each cell. Such questions are not amenable to traditional statistical procedures based on simple array-structured data. Geometric and topological data analysis provides a mathematical representation of the shape of data and extracts structural information from a complex data set. We have developed statistical approaches for geometric and topological data analysis that provide a direct inference on the shape of data.

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Dr. Chul Moon, Assistant Professor

2. Mixed-Value Time Series Analysis — Multivariate time series are routinely modeled and analyzed by the well-known vector autoregressive (VAR) models. The main reasons are ease in computation arising from the imposed linearity, easily understood by a wide audience, and provide predictions. Though VAR models are well understood from a theoretical and methodological point of view, and are quite useful for analysis of continuous-valued data, they are inappropriate when dealing with multivariate time series when some of its components are integer-valued such as the daily number of new patient admissions to a hospital, the number of crimes in a particular region, trading value during a time period. The goal is to develop new statistical tools and models for analyzing multivariate mixed-valued time series data. This is significant because multivariate time series data, discrete and continuous-valued, is collected in diverse scientific areas such as demography, econometrics, sociology, public health and neurobiology for the purpose of forecasting, planning and informing policy. 

The group is also investigating measurement error issues using methods such as SIMEX to correct for the bias of regression coefficients in models in which some of the predictor variables are measured with error. The motivation for this work came from attempts to use teacher intervention fidelity measures as predictors of their student performance. Since teacher fidelity is measured by sampling instruction time, it is measured with error. Professors Stokes, Harris, and Cao are co-investigators in a series of jointly funded projects with SMU's Institute for Reading Research. Several Department of Statistical Science graduate students are supported by work in the data laboratory of the institute managing and analyzing data for large-scale reading intervention programs.


Raanju Sundararajan, Assistant Professor, Department of Statistical Science

Statistical Science Ph.D. Students Discuss their Research

The Moody School hosts an annual Research & Innovation Week event, and graduate students are able to present their research, interact with other students and faculty, and practice their ability to communicate clearly and quickly about the work they are doing. We caught up with two Statistical Science PhD students to hear about their experiences during the Graduate Student Poster Session.

Curious About the Actual Research Going On at SMU? Review it for yourself!


Check out these samples of faculty and graduate student research to get a sense of the type of work you could do as a graduate student in statistical science.

Unlock this collection of FREE faculty and graduate student research samples!

Meet the Statistical Science Thought Leaders at SMU


A Nationally Recognized Faculty

The faculty members of the Department of Statistical Science are prominent scholars, researchers, and consultants, as well as dedicated teachers.

Two have been honored with the title of Fellow of the American Statistical Association; one is a Fellow of the Institute of Mathematical Statistics; and one is a Fellow of the Society for Clinical Trials. Two have won the Don Owen Award, and one has won the ASA Founders Award.

All tenure-track faculty members are actively engaged in research which is being published in professional journals. Their research has been funded by major grants from private organizations and governmental agencies, including:

Students have the opportunity to pursue common interests with faculty members through informal discussions and joint research activities.


Dynamic Faculty-Student Interaction

The faculty-to-doctoral student ratio in statistics is only about 1:3.3. 

Students in the program are encouraged to interact with the faculty and each other. To facilitate this, all graduate students are provided with offices within the department. Faculty offices are located across the hall and an informal faculty "open-door" policy is the rule rather than the exception

Weekly seminars within the department expose students to research efforts by other students, faculty members, and departmental visitors. The seminars also are a forum for discussing statistical topics not covered in regular courses.

Why SMU? Facilities, Resources, and Partnerships

A Superb Library Collection

SMU's Science Library has one of the most extensive collections of statistical literature in the Southwest, including more than 150 statistics and mathematics journals and all major abstracting services. Students have open-stack access and review many journals online.

Excellent Computer Facilities

The Department of Statistical Science has access to the Center for Research Computing — home to the supercomputing complex known as ManeFrame II. The Center exists to provide a state-of-the-art research computing infrastructure for SMU faculty and students, as well as training in the use of the Center’s resources and support in the development of educational programs involving computation.

Professional Enrichment Activities for Graduate Students

In addition to department-sponsored weekly seminars, students have the opportunity to attend regular meetings of the North Texas Chapter of the American Statistical Association (ASA). Students can hear an outstanding array of speakers from academia, business, and industry, and they can network with professional statisticians in the area.

The Southern Regional Council on Statistics promotes the improvement of postsecondary education in statistical science. About 40 member graduate programs coordinate a Summer Research Conference for which there are student fellowships.

SMU Statistical Consulting Center

The SMU Statistical Consulting Center assists scholars, businesses, and organizations by applying statistical expertise to a variety of data analytics projects. Through this service, experienced faculty members in the Department of Statistical Science and supervised PhD and M.S. graduate students can provide help in all phases of research or data related projects, including:

  • Effective data collection strategies
  • Predictive analytics
  • Empirical model building
  • Database management and statistical computing
  • Forecasting
  • Data mining
  • Data visualization

Working with faculty in the Statistical Consulting Center gives graduate students valuable experience communicating with and working with industry leaders to solve real world statistical problems while still in school.

ADVANCING THE FIELD: Stories and Resources for Graduate Students

Advancing the Field is a weekly blog that offers prospective graduate students insight and advice as they consider the challenges and exciting possibilities that come with getting a graduate degree.stats-job-icons (1)-1

Ready to Read More? Subscribe to Our Blog!

Understanding the Statistical Science and Biostatistics Programs at SMU

The SMU Department of Statistical Science is a nationally recognized department with a history of producing outstanding, highly marketable graduates and of being at the forefront of statistical research and innovation.  

At SMU, we offer doctoral degrees in both statistical science and biostatistics. We will explore both degree options below in order to give the prospective graduate student who is choosing between statistics and biostatistics more context on these two paths and more information about curriculum and program structure.

The Statistical Science Curriculum at SMU

 The emphasis in the PhD program is on developing a fundamental breadth and depth in both theory and applications. During the first year in the program all PhD students are required (unless previous coursework is deemed equivalent by the Graduate Advisor and Chair of the department) to complete:

  • a two-semester course in theoretical principles of statistics, Mathematical Statistics (6327, 6328), 
  • a two-semester course in statistical methods, Statistical Analysis (6336, 6337), 
  • an introductory course in statistical computing, Computational Statistics using R (6324),
  •  and Regression Analysis (6345). 

Students continue to take courses during the second and third years in the program.  At the end of the first year students will be assigned an advisor, and with the aid of the advisor, each student will draw up a course schedule which should reflect both the departmental requirements and the student's interests.

Students are admitted into candidacy after passing both the Basic and Qualifying exams, preparing a written prospectus, giving an oral presentation in a research area on which the dissertation will be based, and receiving approval of the prospectus from his or her dissertation committee. The oral defense of the written dissertation is the culmination of the student's training. The written dissertation demonstrates the student's ability to conduct research at an advanced level.

Statistical Science PhD

The courses in the PhD curriculum in Statistical Science at SMU provide our students with a strong theoretical foundation in mathematics, statistical inference, and probability. Students also acquire extensive experience in statistical applications and practice that will enable them to take leadership roles in innovative uses of statistical science in industry, government and many other diverse fields.  

The emphasis in the PhD program is on developing fundamental breadth and depth in both theory and applications. The courses in the PhD curriculum provide students with a strong theoretical foundation in mathematical statistics, probability and stochastic processes along with applied courses covering the intricacies of statistical practice needed for students pursuing a well-rounded, research-oriented PhD degree.

Biostatistics PhD

One of the areas where statisticians can have the greatest impact is in the healthcare industry. In this field, data carries life and death significance. 

The PhD in biostatistics is conferred by the Department of Statistical Science at SMU in collaboration with faculty in the Peter O'Donnell Jr. School of Public Health at the University of Texas Southwestern Medical Center at Dallas. Students attain a strong mathematical and statistical foundation such as that provided in the PhD in statistical science curriculum, but they will also take courses and become involved in research projects that prepare them for a research career in biostatistics. During the third and fourth years of the curriculum, students work with researchers at UTSW under the joint supervision of one or more SMU faculty mentors.

Applied Statistics and Data Analytics MS

The Master of Science in Applied Statistics and Data Analytics (MASDA) degree from the Department of Statistical Science at SMU prepares students with the statistical foundation and critical thinking skills to tackle today’s problems and those that don’t even exist today. 

Courses concentrate on practical applications of statistical data analytics including statistical data analysis, big data analytics, database management, statistical computing, and data mining, and the curriculum is designed to allow you to graduate in 18-24 months. The MASDA program at SMU has an outstanding record of job placement for its graduates.

Hear from Students and Alumni of the Statistical Science Ph.D. Program

Bingchen Liu
Data Scientist/Statistician for the
Educational Testing Service (ETS)

Elizabeth Ribble
Professor in the Mathematics at
Metropolitan State University of Denver

Charles South
Professor of Practice & Director of
Statistical Consulting Center

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