The course is Statistics and Probability for Safety, Reliability and Quality. This course
is one of the most important modules we offer if you are thinking about a career in Safety
and Reliability Engineering. It provides all the required understanding and a basis for
you to excel in the risk calculations that you may do as a reliability engineer. The course
is suitable for anyone with an Engineering degree or with a degree in Physical Sciences.
We tend to look at all the applications very closely to make sure that if you want to proceed
on one of our MSc programmes then you have all the required skills. The course is suitable
if you want to become a Safety and Reliability Engineer or a Technical Safety engineer, or
a researcher in probability and risk quantification. Many students have stayed with us to continue
for their PhD, or moved on to other universities to do PhDs in related areas. So this course
offers a wide range of opportunities for you. In addition to all of that you may also achieve
required skills for understanding financial mathematics, so you may acquire skills for
understanding the investment side of risk calculations. This course is part of one of
the longest standing MSc programmes at the School of Engineering, the Safety and Reliability
Engineering Programme. We have been teaching it for over 20 years and it's very well received.
We have graduates in almost every type of industry and academia that you can think of.
Students will learn about uncertainty quantification. The first question I ask in the first lecture
is - Why do you think risk is important? - and if you want to quantify risk effectively you
need to understand that every system has uncertainties. So you will develop an appreciation for uncertainties
and making sure that you question every number that you see in these calculations. And this
course provides you with all the required background to get that skill. This course
gives you all the basic probably insights, so it starts with a very basic theory on probably
axioms, and the first example that it is gives is that of tossing a coin, which you may have
heard when you were in school. So we start at that level and towards the end of the course
we make sure that you have the required understanding on how you quantify data, how you can think
about any problem, probabilistically, and we provide all the skills and uncertainty
modelling in that direction. We teach all the statistical principles, basic probability
models, distribution models and we also touch on regression analysis so that you can use
the equation editors and all that you see in other software easily. The module that
that we’re discussing is also taught on campus and we record the lecture. The recording
is available online for you to stream at any time and we give the associated lecture notes
with the course materials so you can access it at any point of time, learn what was there
in today's lecture and then recap as you move on. When it comes to assessment you have two
components. The first component is continuous assessment for 20% of the course and we design
it to make sure that the online students have enough time and resource to attempt the assessment.
The second component is an examination for 80% of course and we have arrangements to
conduct this exam anywhere in the world. In terms of time the module requires around 10
to 15 hours per week, including the recorded sessions and any tutorials that were given.
This is an intense mathematical course so if you have not been using mathematics for
the last few years you may need to put in more effort to make sure that you come up
to the required level.