WHAT CAN I DO WITH A DEGREE IN STATISTICS?
With an undergraduate degree in Statistics, you can get a job, go to graduate
school in Statistics, go to graduate school in a field other than Statistics, or do
something else. The last alternative is possibly the most interesting, but beyond
the scope of this document. Statistics students who plan on graduate study in a
non-statistical discipline probably know how Statistics fits into their plans. Here,
we will deal with the first two options.
GETTING A JOB
With an undergraduate degree in Statistics, you are a more attractive candidate
for jobs that require understanding of statistical information. For example, in an
industrial setting you will be able to readily understand information based on statistical
quality control, even though you probably will not have a course in it. In a
management or sales position in an insurance company, you will be able to understand
actuarial data, even though you are not an actuary. In a marketing or market research
setting, lots of the data come from sample surveys and are subjected to standard
statistical analyses. You will be able to understand and use these data, even though
you may not be crunching the numbers yourself.
A degree in Statistics is also an advantage to Computer Science students. It's a lot easier to participate in the "Big Data" revolution if you know the basics of what to do with data. Yes, anybody who can code will be able to do something, but it helps if you understand what you are doing. Some of the black boxes will be a little less dark, and everybody will be better off. Wise employers know this.
Even apart from the whole Big Data thing, statistical analysis is an important part of what many companies do. From banking to the pharmaceutical industry, to the human resources department in almost any big company, data needs to be converted into information that managers can use. All
other things being equal, job applicants who appear to know some statistics have an
advantage in almost every field.
On the other hand, an undergraduate degree in Statistics -- even a specialist
degree -- does not qualify you as a professional statistician. You may wind up doing
statistical analyses for a living, depending on the type of company or organization
you're in, but you probably will not be hired in that capacity initially. It happens, but
in our experience it is rare.
Let's face it; with a degree in History, are you qualified as a professional
historian? With a degree in Mathematics, are you going to be hired as a
mathematician? With a degree in Physics, are you going to get a job as a physicist?
With a bachelor's degree in statistics, you should not count on being employed as a
statistician. You will probably be hired as something else.
In fields like History, Mathematics and Physics you need a Ph. D. in order to be
taken seriously as a professional. In fields like Engineering and Computer Science, an
undergraduate degree is just fine. Statistics is in a sort of intermediate category. A Master's degree qualifies you to do applied statistics for a living in a medical, business
or government setting. A Ph. D. is an extremely powerful credential for applied jobs,
and also allows you to seek university faculty positions. It is still possible to be a
university teacher with a master's degree, but that door is closing.
GRADUATE SCHOOL
So if you really like stats and you're sure that's what you want to do for
a living, you should consider graduate study. Generally, a master's program should
take 1.5 to 2 years, and a Ph.D. program is expected to take 4 or 5 years (2 or 3 if
you get a master's degree first). The specialist program at UTM is designed as a
preparation for graduate school.
An overall grade average of B+ should be good enough for admission to
graduate school in Canada; in the United States, it is possible to get into many
reasonable master's programs with a C or C+ average. They are hard up for students.
Of course there is some inconvenience involved in getting a foreign student visa and
so on, but think of all the time you have saved by not studying!
MASTER'S PROGRAMS
Let's be clear about one point. We are not talking here about what you know,
or what you are truly qualified to do. We are talking about the perceptions of potential
employers. The material taught in our Specialist and Major programs has a large
overlap with what is taught in Master's level courses, both here and in other schools.
In theory, the topics covered at a more advanced level in graduate school. Sometimes
this is true, and sometimes it is not. But in grad school, at least you will learn the material better than
you did the first time, and after you finish your career earnings should be significantly
higher. You will get more respect, and the work will be rewarding --- assuming you like analyzing
data. You'll need about a year of on-the-job experience before you are actually as
qualified as you appear to be, but that's no problem. It's true in any field. In any
respectable master's degree program, there will be at least a one year course in
mathematical statistics (same material as STA256 and STA260 but deeper and faster),
in which your brains are pulverized and poured back into your ear. This is thought to
be a beneficial experience.
At the University of Toronto, there are M. Sc. and Ph. D. programs in both the
departments of Statistics and Biostatistics. The Statistics department here is widely
believed to be the best in Canada. The Biostatistics department is really a Statistics
department (and a good one), but it is affiliated with the medical school, it does not
offer any undergraduate courses, and it tends to focus on statistical problems that
appear in biomedical research. In spite of the "Bio" in Biostatistics, and contrary to what you might assume, you do not need any training or background in biology or the biomedical sciences for graduate study in biostatistics. Zero. Most practicing biostatisticians know something about biomedical research, but they have picked it up on the job. Their training is almost exclusively in statistics. When biostatistics faculty complain about their students (Can you believe it? This actually does happen!), they are almost always complaining about lack of undergraduate training in mathematics and mathematical statistics. Of course the students are complaining about their professors too, but is that really a surprise?
PH. D. PROGRAMS
Many Ph. D.'s in Statistics go into the private, public and medical sectors as
applied statisticians on the fast track. Their training, however, is in statistical
research. In Statistics, as in all other disciplines, Ph. D. students learn to create new
knowledge in their field, to formulate important new questions and answer them.
Every theorem and statistical technique you learn is the result of somebody's research.
Researchers in Statistics mostly are professors at universities, and their students tend
to view them exclusively as teachers. In fact, at U of T the typical professor's job
description consists of 40% teaching, 40% research, and 20% administrative duties
and community service. This is true in most fields, not just Statistics.
For a Ph. D. in Statistics, what you need more than anything else is a solid
mathematical background. Basic Calculus is certainly not enough for
doctoral study in Statistics. Real Analysis, Complex Variables and Topology are very
helpful content areas. Pay attention to the proofs! This is the main way that knowledge
is created in the mathematical disciplines, and what a Ph. D. says is that you know
how to create new knowledge.
One other thing you should be aware of is that after the first year or so of grad school, taking
courses and doing well is not the main point. Research training is primarily a process
of apprenticeship. You find somebody who is doing something interesting (or he/she
finds you), and the person trains you one on one. Probably the most important choice
a Ph. D. student makes is whom to work with. Almost any professor will tell you
more than you want to know on this topic, if given half a chance.
Last Updated: Tue 28 Feb 2023 02:36:16 PM EST