Participants Phil Crook (ODA), Kirsty Davidson (Napier
University), Glyn Davis (University of Teeside), David Edelman (Royal
Bank of Scotland), Laurence Ewan (Quintiles), Anne Hawkins (RSS Centre
for Statistics), Lynne Holton (Astra Clinical Research Unit), Peter Holmes (MEANS
Project), Iain Knox (Royal Bank of Scotland), Cecilia MacIntyre (Scottish
House Condition Survey), Zamalia Mahmud (University of
Strathclyde PhD student), John McColl (University of Glasgow),
Maria Melling (The Scottish Office), Bob Peacock (Astra Clinical
Research Unit), Trevor Ringrose (University of Aberdeen), Prof
Peter Sprent (Retired), Stuart Young (University of Glasgow).
Notes
The meeting was organised by John McColl of the University of
Glasgow and held in the Melville Room of the Gilbert Scott
Building. He and Peter Holmes welcomed the delegates and thanked
them for coming.
The main purpose of the meeting was to obtain insights into
the problems of matching education, assessment and employment
needs in statistics from the different perspectives of those
attending the seminar.
Peter Holmes and Anne Hawkins summarised the work done so far
by the project and drew attention to the newsletter. Each
delegate then gave a short presentation which was followed by
discussion.
Glyn Davies spoke from his experience as senior
lecturer in IT and Quantitative Methods within the school of
Business Management. Students there generally do not like number
crunching so the emphasis now is on the ability to take and use
data, use commercial software and then communicate to non-statisticians.
Students work on individual and group reports - if courses
requiring this are optional then students do not choose them.
They have tried to find out what employers want and do not get
much demand for higher level techniques. Most statistics at
Teeside is done in non-specialist courses. There is a fear of the
subject - do we need a new name? In discussion it was suggested
that the department might get feedback from students who had
graduated; they and staff from the 'home' departments might be
used on the courses.
Zamalia Mahmud is doing research on statistical
education in Scotland. She sees problems of students coming on
courses from a wide variety of backgrounds with a general dislike
of the subject which they see as largely irrelevant. There is a
need to educate employers on the role of statistics.
Stuart Young is responsible for the electronic side of
the CTI in Statistics and is list manager for Allstat. He sees
the need for universities to take a problem based approach to
teaching and to put statistics as part of a problem solving
process. Increasingly, with growing computer power, there is a
need to emphasise interpretation rather than calculation.
Statistics only stands with its applications. He queried the
value of the 10 week service course - the main thing that people
should learn from this is to consult a statistician.
Employers may need educating to employ statisticians, and not
think they can do it all with their computing packages. Students
need to learn how to use packages - though they should be able to
transfer from one used at university to a different one in
industry if necessary. This would be helped if there were an
element of programming in the university course. This would also
promote logical thought.
Discussion. If we are to teach appreciation of
statistics to user departments then we need staff who can do it.
Such people may or may not be found in each department and it is
unreasonable to expect staff in the statistics department to have
a deep knowledge of all the contexts. It is not possible to
divorce appreciation completely from understanding and the
ability to do some statistics. We need to discourage the idea
that a package will solve all statistical problems. The timing of
service courses is important; in many cases they are too early.
Reference was made to John Whitehead's courses in medical
statistics run at the University of Reading. He also goes to
specific companies and gives tailor made in-house courses.
Lynne Holton recently graduated from the University of
Glasgow and all her work is now connected with clinical trials.
She works as a lone statistician on a day to day basis, dealing
with experts in many other disciplines. She thinks a good
theoretical background is essential in the undergraduate course.
This she had. It was the practicalities of the job that were
missing. These include: discussion with others; having to use SAS;
communication skills; why statistics is useful to solve problems.
In her undergraduate course she did two pseudo-real problems with
other departments. These were valuable in giving insight. They
were not real enough; they were still too tidy and paid
insufficient attention to the non-statistical issues.
As a statistician she needs to understand the biology but not
make biological/clinical decisions.
Statistics has problems with a bad press. The 10 week service
course does not help here. Statisticians need to learn to
communicate with non-statisticians; they need more real problems
as part of their undergraduate course.
Discussion. Could we use external people to bring in
real problems? Could the statistician become involved in, say,
the biology practicals? Could the statisticians from PSI become
involved in pharmacy courses? There are real practical
difficulties in building cross-subject co-operation into
undergraduate practicals. There are also associated assessment
problems - but the experience itself is very important.
Kirsty Davidson started work in the Scottish Office
which required versatility and many transferable skills. She is
now at Napier University lecturing mainly on service courses. The
major problems here are motivation, attendance and modularization.
Statistical methods need to be a core part of the course - if
they are optional they will be avoided. Areas of good practice
include written communication; group projects with peer
assessment; case studies; operational research output interpreted;
5 minute interviews on interpreting computer output. She has had
students visit the Scottish Office and the General Registrar's
Office to help students learn the practicalities. She has also
had external speakers from pharmacy etc. The problem of
motivation is strongly linked with assessment. Visits have to be
written up as an assessed report. She uses real life problems e.g.
Napier customer satisfaction for catering. 2000 interviews were
given to MSc students to check, analyse etc. Another project was
on performance indicators. There was a landscape project with
employers and graduates; they come in to assess students.
Business students use Excel. They use TLTP STEPS material in
teaching. They teach research and consultancy on MSc courses.
Discussion. In the pharmaceutical industry they have to
use validated packages in the investigation, hence the use of SAS.
Excel would not be good enough.
John McColl lectures at the University of Glasgow.
There is a difference between specialist statistics courses and
service statistics courses. Statistics and mathematics graduates
have a wide range of possible careers. The main ones are research,
medical, actuarial, government, pharmacy and teaching. The
specific requirements in these differ so the department needs to
look at the general skills needed. So they look for a strong
theoretical foundation. Statistics graduates need to do much more
in statistics than, say, the psychologist. But it is also
important to emphasise the applied side, so they do project work,
laboratory work and work in teams to solve problems. In some
specialist areas they have developed specialist courses.
Psychology includes one third of a year in statistics. They use a
computer package, emphasise collection, design and interpretation.
There is a problem that no text books take this emphasis.
Universities should be teaching generally how to use a
statistical package. The employer is responsible for the
specialities.
Discussion. What should be included in the theoretical
foundation course. How much is proof important. For example
should all be able to prove the Central Limit Theorem or should
they know in practice when the CLT will give good enough results?
Laurence Ewan As an employer he is looking for a basic
understanding of statistics and the ability to explain simple
concepts. He wishes his graduates to know about design of
experiments and modelling and data-fitting. They need to be
computer literate with word processing skills and know about
systems and network communications. They will work with a group
which includes IT people and the clients. They need good
reporting skills and commonsense. They need to be able to think
round a problem and use their time well. Over the years students
seem to be graduating with fewer programming skills. (Fortran was
good for teaching logical thinking.)
Group work modules have been found useful by young employees.
Work placement students fit in well. Laurence did a degree
including practical statistics. The group work was assessed; the
overall mark was shared within the group. A logbook was kept of
the group's meetings and this was seen by the lecturer.
Students need to be taught to look at the data before analysis
and plot before any inferences. Any training on the job has to
have a short term pay off or the experience will be used to get
promotion elsewhere.
Discussion. In some areas, such as pharmacy, experience
and a Masters degree are expected for the first job!! Large
companies find it easier to put on their own training schemes
than do small companies. One large employer was reported as
looking for lifetime development.
Maria Melling works for the Scottish Office in a group
of four statisticians and five assistant statisticians.
Assessment on entry requires the candidate to explain things to
statisticians and show they can understand data. They are
assessed for quick thinking and the ability to hold an argument.
A statistician needs to be flexible to move round different
departments. They are expected quickly to pick up the background
in each department and also quickly to take on responsibility.
Maria also gets involved with policy decisions. At times there is
a need to dig to find what colleagues actually want - this was
not part of her training. You may have to cope with people who do
not like your conclusions, so at times there is a need to stand
up for professional integrity and here a code of practice can
help A weakness in her own undergraduate course was that she was
not taught SAS or any package. There are in-service courses
within the Civil Service to fill gaps and develop new skills.
Discussion. At times you may have to hold out for what
you can NOT say from the data as well as what you can. A good
course in consultancy should do this.
Cecilia MacIntyre works for Scottish Homes as a
statistician with one assistant. When advertising for the
assistant they were looking for intelligence, fast thinking,
ability to do some boring work sorting data files, working
together in a team to produce a report, not easily side-tracked.
They found someone with a mathematics/statistics degree who had
done an external project one Christmas.
Before working for Scottish Homes, Cecilia had lectured to
medical students. She had to use students to help with projects
in the summer each taking about two weeks and using a statistical
package.
Although she had a practical component in her MSc she learned
properly how to deal with real (unclean) data when she started
work. She learned a lot by absorbing ideas from colleagues.
Employers need to appreciate that statisticians have skills to
offer. It would be helpful for undergraduate statisticians to see
themselves as part of the whole research process.
Discussion. John McColl gives his students 3-4 months
outside placement work between the third and fourth years. It is
possible that the Office of National Statistics could use summer
students like this. David Edelman used something like this scheme.
Cecilia MacIntyre has a large amount of data which could be used;
it would be helpful to have such people looking at it. The
Government Statistical Service runs a sort of probationary year
which has similarities to university work placement schemes.
David Edelmen What employers are looking for depends on
whether they are employing for a job or a career. If for a job,
and the person is working in a team, then an employer can cope
with weaknesses if they can be developed. Employers may be
looking for numerate/scientific skills not just statistical.
It is essential in an undergraduate course for students to
look at data. As an undergraduate he had 6 hours of labs for two
years which was very helpful. In the assessment exercise he was
given 3 hours to say what he would do to analyse a set of data
and was then given 3 days in which to do it. Any change in plan
had to be justified. He also had to collect his own data which
taught him a lot.
Report writing needs to be taught separately from assessment
and could be part of an undergraduate course, thought it is not
clear at which stage. It should not be optional.
Discussion. John McColl reported that at the University
of Glasgow, as part of the statistics course, four times a year
students had to do a practical, report on it and receive feedback.
Report writing skills were developed in the context of the data
with not too much detail. The Government Statistical Service
course for Africans insists on report writing, including an
appropriate level of approximation and a proper use of English.
Eurostat has produced a report on how to write a statistical
report for press releases. It really would help if universities
trained people to write clearly.
Bob Peacock works in clinical research. The unit
employed its first statistician in 1986 and as it grew he joined
in 1991 from the Open University with a multidisciplinary
background. His MSc was largely useless - his job was a big
learning experience. Clinical Research is to assist drug
development through to drug licensing and is all heavily
legislated. A university course needs to raise the idea of
constraints like this. The context is of randomised, controlled
clinical trials and often the non-statistical aspects are
difficult. For large data sets he uses SAS because it is
validated software. The data analysis is followed by a report.
Protocols have to be reviewed and he has to advise on design,
sample size, power, analysis and plans. There is both a
statistical report and a clinical report. He has to collaborate
with statistical and medical colleagues for presentation. He also
has to follow up queries. More and more nowadays recruitment is
from graduates with an MSc in medical statistics and two to three
years experience. They look for someone who can communicate,
write and program and who also has interpersonal skills. Recent
recruitment has been from the University of Reading and de
Montfort University. Some come through in-house promotion.
Trevor Ringrose lectures at the University of Aberdeen.
Aberdeen has a placement programme for four days a week for the
first term in the fourth year. This counts as 2 to 3 courses. All
is done in the local area and supervised from the department.
Suppliers have included BIOSS, medical centres, hospitals.
Students are given feedback during their period of placement.
They also have team bonding exercises at weekends. Modularisation
is posing problems of slicing up knowledge into too small slices.
It is difficult to use many real examples in a course -
especially when the course is tied to specific methods. Should
data analysis be separated from methodological courses? Students
can learn by having to explain. Could we do this in an
undergraduate course by having groups of, say, five explain to
each other. We might have to disentangle this from assessment.
Logical thought is an important of transferable skills;
students pick up some during the course but do need practice.
They also had help in framing a question statistically and in
seeing the importance of asking the right questions. One
possibility for service courses is to have students read papers
and present to others.
Discussion. The practicalities of the 4 day a week
placement were questioned. It works reasonably well because there
are only a few students involved.
Phil Crook works for the Government Statistical Service.
His degree was in Pure Mathematics, Statistics and Geography
followed by an MSc in Statistics. This had an emphasis on
Bayesian statistics which was not much use in the GSS. His first
job in the Ministry of Defence was modelling the Navy Stock
Control System. He employed students there to do some of the work.
He them moved to the Seychelles as one of two statisticians.
For 6½ years he did all the non-economic statistics. He designed
the questionnaire, duplicated it, went out and trained
enumerators to administer it. He learned how to deal with
practical problems in small area statistics such as when the
tomato production figures depended entirely on the sole non-cooperative
tomato grower.
He then moved to working on manpower statistics in the navy
and is now with ODA developing statistics projects for Developing
Countries.
In a statistician he is looking for numeracy, literacy,
logical thinking based on a statistical background and the
ability to get into the mind of other professions. Possibly a
background in philosophy and language would help. [He would have
found it useful if, as a student, he had been made to write more
and speak in public.] Statisticians need to be able to look at
data, the shape of the data and need to do some hand calculations.
It is not possible at the undergraduate level to cater for all
possible careers. ODA is now working in a more interdisciplinary
way and statisticians have to show they have skills to offer
others. GSS recruitment is about to be based on competencies and
entrants will be assessed against competency skills. The GSS does
have a University Liaison Service.
Iain Knox recently started work for the Royal Bank of
Scotland. As an undergraduate he would not have chosen statistics
but his course included it. He then did an MSc which covered most
areas of statistics and included report writing and dealing with
people. By specialising in statistics he found there were many
fields to choose to enter. University courses therefore have to
concentrate on giving general skills.
In the Bank he has to work quickly to sharp deadlines. Early
on he had to learn the basics of SAS and handling large data sets.
His boss is looking for someone who thinks clearly. His area of
work is on behavioural scoring systems, how they work and how the
model is derived. He monitors the system giving feedback. He has
needed general skills, including consultancy skills to find out
genuinely what the customer wants.
Discussion. If students don't learn theory at the
university it will not get learned. You may only appreciate the
significance of theory after you start work.
Peter Sprent is now retired. Universities can make
theory more attractive by broadening courses to include
applications. Regression should include some examples with dirty
data so that students can learn to deal with it. Simple examples
can be used to show what is going on; maybe bring in ideas rather
than detail. Student awareness can be raised by using interesting
examples. The difference between statistically significant and
practically important is not sufficiently emphasised; neither is
the problem of the power of a test and its effect on significance.
Paradoxes can be used to make people think.
His own background was probably too theoretical and he had to
develop practical skills in an applied statistics job on fruit
trees which posed particular problems for design of experiments.
The good basic grounding enabled him to pick up the specific
skills.
As an external examiner he has seen university courses which differ markedly from each other. One is highly theoretical and one highly practical. But it is not obvious which is better when it comes to picking up new techniques.