Statistics is the fastest-growing STEM major for 2010–2013. With a 95% increase in degrees granted from 2010 to 2013, it outpaced computer/information technology and administration and management environmental/environmental health engineering.

To find out how departments are keeping pace with this increased interest and where their students are going, we asked the heads of some of the largest and fastest-growing departments (see Table 1) to respond to five questions. Four of those departments are below. Stay tuned for more interviews in upcoming issues of Amstat News.

University of Minnesota-Twin Cities

Dennis Cook is professor and director of the school of statistics, University of Minnesota. He received the 2005 COPSS Fisher Lecture and Award and is a Fellow of the ASA and Institute of Mathematical Statistics. He is also an elected member of the International Statistical Institute.

 

What do you believe is driving the growth in the number of statistics majors in your department? What are you doing (if anything) to recruit majors? How much longer do you expect such growth?

There are myriad factors driving the growth in our majors, as well as our enrollments generally. Society is becoming more quantitative, high schools now routinely incorporate statistics and statistical ideas into their curricula, and Big Data is ubiquitous.

The demand is surely driven in part by the contemporary press: In an August 8, 2014, article in The Wall Street Journal, E. Dwoskin wrote that after a couple years of experience, data scientists, essentially statisticians with excellent computing skills, could command salaries between $200,000 and $300,000. Promotions like the ASA’s This Is Statistics campaign also are adding fuel to the progression, as is the impression that “statistics is sexy.” Emphasis on STEM disciplines also could be contributing to our growth.

Other clues may be indicated by statistics for our program. In 2004, we had 34 undergraduate majors, while we have 224 today, for a 560% increase, most of which occurred in the past few years. Undergraduate enrollment at the university as a whole decreased over this time period by about 3%. Double majors comprise 20% of our total; evidently, many students think doubling with statistics will make them more desirable to employers or increase their chances of admission to graduate school. Forty-six percent of our majors are female, and 65% are international. The University of Minnesota’s tuition for nonresident students, including international students, is relatively low. While this might account for a high percentage of international students generally, it does not explain why many of these students choose statistics as their major.

We have never actively recruited undergraduate majors, although we do participate in general recruitment events. Recent data indicate our growth trend is continuing. Last fall semester, we left a 5% enrollment increase on the table because we did not have the resources to cover the unexpected demand. For spring semester, our college allocated additional resources to cover the fall excess plus a bit more, but it appears we will have again underestimated by about 5%.

What kinds of careers or graduate programs are your graduates moving on to? Who are the top recruiters?

Historically, we have regarded statistics as primarily a graduate discipline, and the rapid growth of our major caught us a bit unprepared, so we have limited data on post-graduation status. Nevertheless, current data indicate more than 50% of our seniors will pursue graduate school in statistics or a related discipline and 30% will have jobs at graduation. We recently scored “Excellent” on the 2015 Quality Metrics Review of University of Minnesota Graduate Programs. The review showed particularly strong career placement rates for our graduate students, and we are working to achieve the same success for our undergraduates. We plan to improve our follow-up in the near future.

How have you changed your curriculum to adapt to the data science era, and how will you use the ASA Curriculum Guidelines for Undergraduate Programs in Statistical Science? Have you considered starting a professional MA program?

The ASA guidelines gave us a good starting point for several major changes we plan to introduce for fall 2015. Here are the key changes as summarized by our director of undergraduate studies, Sandy Weisberg:

• A bachelor’s of statistical practice with extensive training in applied statistics at the level usually attained in a master’s program. This degree is designed for those seeking employment as a statistician, but not a further degree in statistics. It also includes flexibility to add a supporting program.
• A bachelor’s of statistical science that will have less applied statistics, but considerably more mathematics to allow students to compete for places in strong statistics graduate programs.
• Introduction of an advisory council and extension of our internship program to undergraduates to provide more opportunity for meaningful work experience, make connections between our students and the vibrant work environments in the Twin Cities area, and provide us with feedback to keep our program relevant.

We redesigned our master’s program last year so it leans more toward a professional degree and provides more opportunity for mentored internships. This is on top of the data science MS degree we initiated last year in collaboration with computer science, electrical engineering, and biostatistics. The program will begin admitting students this spring. We also plan to have a joint degree with actuarial science by the fall of 2016.

How have you managed the growth in the number of majors? Has the university allocated more resources (e.g., finances, space, personnel) to your department?

Our growth in the number of majors has been accompanied by similar growth in the number of students in service courses. This overall growth has been managed by hiring non-tenure-track full-time teaching faculty, expanding the size of our classes to beyond reasonable capacity, increasing the number of teaching assistants and graduate instructors, and expanding the curriculum for our majors. We have been fortunate to hire strong teaching faculty. Our requests for additional funding/support have met with varied results. Unfortunately, because of collegiate priorities, it appears hiring teaching faculty has led, perhaps inadvertently, to a reduction in FTE [full-time equivalent] ladder-rank research faculty through retirements.

To sustain our curricular advances and accommodate further growth, we need to hire ladder-rank research faculty and ladder-rank faculty to lead our undergraduate program, but this also will hinge on collegiate priorities. We also hope to obtain help advising our majors, as our in-house advisors are seriously overburdened. Some universities offer statistics in very large classes, perhaps in excess of 200 students. So far, we have resisted that trend, but the pressure is building. Some variation of online learning is another option for programs with many students and limited resources, but the learning curve can be quite steep and costly to navigate.

What recommendations do you have for students considering a major in statistics? Any advice for students already committed to a major in statistics?

Anyone with an innate curiosity and an aptitude for quantitative thinking is a likely statistician. We would encourage students with a long-term interest in statistics to also pursue a related field because most statisticians are involved heavily with problems in the applied sciences. We have faculty with joint appointments in psychology and sociology. Other members of our faculty are deeply involved with statistical genetics, image analysis, biostatistics, climate statistics, and statistical problems arising in educational and psychological assessment.

The needs of students who seek employment immediately after a four-year degree are quite different from those continuing to graduate school. Our new undergraduate degree programs are designed to meet the requirements of both groups. We offer the potential for course work with prominent research statisticians and opportunities to network with a wide array of employers and individuals, and our classes are still relatively small.

Carnegie Mellon University

Christopher Genovese is the head of the Carnegie Mellon Department of Statistics. Rebecca Nugent and Howard Seltman are the co-directors of the department’s undergraduate program and have both played a pivotal role in building such an outstanding program.

What do you believe is driving the growth in the number of statistics majors in your department? What are you doing (if anything) to recruit majors? How much longer do you expect such growth?

Our internal data show much larger numbers and faster growth than the NCES data shown in the table. The number of our undergraduate majors has roughly doubled since 2010 and has grown twenty-fold (!) since 2005. Part of this is attributable to a widening recognition among students that data-analysis skills and statistical thinking are potent tools that add value to many career paths. The rise of “data science” has only increased the excitement in this direction, which we would like to capitalize upon. Part of the growth in our program also may be due to AP Statistics, which has increased awareness of statistics as a field and viable major. We also believe part of our growth followed from our developing an engaging, high-quality curriculum with emphasis on modern methods, strong communication skills, and the analysis of data from real, interdisciplinary research problems (with no “textbook” data sets after the intro level).

One strategy we have used is to build on and highlight connections between statistics and other fields. We have joint majors with economics and machine learning (new this year). We also have new tracks within our major in neuroscience and statistical theory, along with a statistics-operations research track in the math department. At Carnegie Mellon, it is common for students to double major, and our program offers productive paths for students to explore the intersection between statistics and another field.

We expect the growth to continue for quite some time because the value of a good statistical education will only increase. We will foster this growth by keeping our program fresh and effective with outstanding classroom experiences.

What kinds of careers or graduate programs are your graduates moving on to? Who are the top recruiters?

In recent years, roughly 10–20% of our primary majors have gone on to graduate or professional school. Among the rest, the most common sectors in which our students get jobs are, in recent years, finance and banking, consulting and analytics, and management and marketing. It is becoming more common for our students to get jobs labeled “data scientist.” There are also a reasonable number who work in industrial research, pharmaceuticals, software companies, and teaching.

How have you changed your curriculum to adapt to the data science era, and how will you use the ASA Curriculum Guidelines for Undergraduate Programs in Statistical Science? Have you considered starting a professional MA program?

Our goal has always been to train students with the skills they will need to be effective, practicing statisticians, which is an essential part of data science as it is currently understood. For example, we emphasize experiential learning through the use of real data sets in methods classes and hands-on practice with consulting, visualization, and computing.

In recent years, we have strengthened the role of computing in our undergraduate program. We now require a course in statistical computing of all our majors. Our core computing course gives about equal attention to classical computational statistics (optimization, simulation, Monte Carlo), programming and software engineering in R, and databases and data management. We also offer courses in visualization, data mining, and advanced statistical computing. This reflects changes in the scope of problems students will face and in the range of skills they will need in their careers.

In our advanced methodology (capstone) courses, we continue to include assignments and projects that use large, real data sets and modern methods with a variety of scientific and modeling contexts. All these courses emphasize statistical thinking, computing practices, and analysis grounded in the applied questions of interest. And in all of them, students sharpen their communication skills by preparing substantial written reports or giving oral presentations of their work, and often both.

We feel our efforts so far are directly aligned with the ASA guidelines.

We already have one professional MS program (in statistical practice) and are developing a second one (a multidisciplinary program in data science).

How have you managed the growth in the number of majors? Has the university allocated more resources (e.g., finances, space, personnel) to your department?

Mostly by using duct tape to keep the seams from bursting. We are pushing capacity in many of our courses, which makes it difficult to add the new courses we would like to. Keep in mind that this change is not just from the number of majors, but also from the tremendous increase in the number of non-majors across the university who are taking statistics courses. We have quite a few courses targeted to help students and programs in other disciplines.

We have redesigned our advising model several times, both to make it more efficient in the face of growth and to more effectively target advice to the students’ needs. Accommodating growth requires more than just adding faculty for courses; it is also necessary to think about how to best advise students in such an interdisciplinary subject that draws people from many areas and interests.

Several new teaching-track faculty members also have joined the department, which has certainly helped, though we are hoping to add more personnel in the near future. The university is sympathetic … and discussions continue.

What recommendations do you have for students considering a major in statistics? Any advice for students already committed to a major in statistics?

Get hands-on experience with real data through internships, courses, and even just for fun. Work toward developing strong oral and written communication skills; their value cannot be overemphasized. It also never hurts to get as much programming and mathematical experience as you can.

For students in both groups, look for statistical questions and issues that arise in areas that interest you. These can give you concrete examples with which to frame what you are learning, give you a chance to practice doing what statisticians do, and can spur you to explore new ideas and make new discoveries.

Grand Valley State University

Paul Stephenson joined the faculty at Grand Valley State University in 1994 and is a professor of statistics. He has served as the statistics department chair since it was established in 2001.

 

 

What do you believe is driving the growth in the number of statistics majors in your department? What are you doing (if anything) to recruit majors? How much longer do you expect such growth?

Significant media attention has been focused on the emerging availability of Big Data and the need for analysts to discover useful information from these massive reserves of data. This demand for data scientists has been a catalyst for growth in student interest in our statistics major and applied statistics minor. While there are a variety of reasons for this growth, some of the reasons include the following:

• The statistics faculty make a real commitment to engage their students
• Our department offers flexible programs that allow students to take coursework germane to their interests
• Our faculty make a concerted effort to reach out to students who demonstrate interest and aptitude
• Our department spearheads programming (such as the Michigan Statistics Poster Competition, walk-up events at Science Olympiad, and Super Science Saturday events) that encourage students from 1st grade to 12th grade to participate in activities geared at statistical thinking
• Our department hosts a Statistics Career Day every three years

While I expect that the growth will level off, I do anticipate current demand for statisticians will remain high.

What kinds of careers or graduate programs are your graduates moving on to? Who are the top recruiters?

Roughly half our students pursue a graduate degree after completing the major. Since some of our students double major in complementary degrees, our graduates have enrolled in a variety of graduate programs, including statistics, biostatistics, mathematics, data analytics or science, actuarial science, economics, business, psychology, and epidemiology. The application areas that employ the highest number of GVSU statistics graduates include the bio/medical sciences, business/industry, actuarial sciences, and agencies associated with the government.

How have you changed your curriculum to adapt to the data science era, and how will you use the ASA Curriculum Guidelines for Undergraduate Programs in Statistical Science? Have you considered starting a professional MA program?

The statistics major at GVSU requires a number of applied statistics courses. As such, we were able to quickly adapt our curriculum to the data science era by offering more elective courses that infused data science content. That being said, our department is strongly considering a second major with an increasing emphasis on Big Data analytics. Our department already offers a professional science master’s program in biostatistics. This program is designed to integrate graduate-level biostatistics coursework, an industrial internship, and professional skills content that prepares students for the variety of career pathways associated with the life science and health science industries.

How have you managed the growth in the number of majors? Has the university allocated more resources (e.g., finances, space, personnel) to your department?

The demand for statistics courses has been very high, and our administration has steadily increased our resources consistent with our growth. Once the administration allocates our annual resources, we must do our best to use those resources efficiently and meet our unit’s overall responsibilities in instruction, research, and service. Our department has worked hard to develop and employ hiring strategies that meet the diverse demand for statisticians (both in teaching and scholarship) within the GVSU community. In an effort to meet course demands at the undergraduate and graduate levels, we have carefully balanced the combination of tenure-line, affiliate, visiting, and adjunct faculty.

What recommendations do you have for students considering a major in statistics? Any advice for students already committed to a major in statistics?

I would encourage every undergraduate student to do the following:

• Broadly explore a variety of topics within statistics and pursue at least one minor in a discipline outside of statistics (e.g., computer science and mathematics). Don’t be too quick to specialize.
• Strongly consider pursuing an internship experience.
• Build a relationship with at least one of your favorite professors and ask them to serve as your mentor.

University of California at Los Angeles

Frederic Paik Schoenberg is chair of the UCLA Statistics Department and editor of the Journal of Environmental Statistics. His research is in on-point processes and environmental applications, and he wrote An Introduction to Probability with Texas Hold’em Examples.

 

 

What do you believe is driving the growth in the number of statistics majors in your department? What are you doing (if anything) to recruit majors? How much longer do you expect such growth?

The main driver is the job market. Our graduates are getting excellent jobs in industry with a statistics degree. Businesses throughout the country are forming analytics groups and seeing the value of data analysis. They are therefore hiring statisticians at a high rate and that is fueling our majors. I expect this growth to continue for five years at least. Our department does a lot of outreach to try to recruit majors, including a stats club on campus, outreach to local high schools and community colleges, and our annual DataFest.

What kinds of careers or graduate programs are your graduates moving on to? Who are the top recruiters?

About 15–20% of our undergraduate majors go on to graduate school, and most of the others get jobs in industry—in a wide variety of areas. Many seem to go into online or tech companies like Google, internet startups, etc.

How have you changed your curriculum to adapt to the data science era, and how will you use the ASA Curriculum Guidelines for Undergraduate Programs in Statistical Science? Have you considered starting a professional MA program?

We proposed a professional master’s program in applied statistics several years ago, and it is still pending approval. It will feature evening classes so workers in local business can enroll. We always have been a department focusing on applied statistics and have increased our instruction of machine learning, computer vision, and the analysis of Big Data in recent years.

How have you managed the growth in the number of majors? Has the university allocated more resources (e.g., finances, space, personnel) to your department?

The university has allowed us to hire in recent years. In 2010, we had 9.5 FTE [full-time equivalent]. Now, three years later, we are at 13.5. The growth has been in ladder faculty at the assistant professor level, and we also have increased our number of lecturers by one over this period.

What recommendations do you have for students considering a major in statistics? Any advice for students already committed to a major in statistics?

I think students should try to get a broad education. For students majoring in statistics, it really helps to get as solid a mathematical background as possible, and computer science skills are also extremely valuable. Having a broad range of skills can set students apart from their peers, and I think a broad knowledge base is going to become increasingly important in analytics applications.