PROBABILITY DISTRIBUTIONS AND
THEIR APPLICATIONS
3 Day Course £850.00 +VAT
Who should attend?
This course is designed for engineers who wish
to gain an understanding of probabilistic
techniques and how they can be applied in an
engineering context. It is also suitable for
engineers who are already familiar with the
basic concepts of probability and who wish to
consolidate and enhance their knowledge.
Why Attend?
Probability distributions are widely used in
industry to provide useful insights into
engineering problems and their solution. They
have particular application in the field of
reliability engineering, but one of the aims of
this course is to introduce attendees to a wider
range of applications. A further objective is to
create an awareness of the types of situation in
which probabilistic analysis can be applied, the
most relevant probability distributions in
practice, and the most useful models and techniques available.
Emphasis is given throughout the course on
understanding concepts, how they relate to
practical problems, and identifying those
situations in which probabilistic techniques are
most commonly and usefully applied.
By the end of the course attendees should have a
good general understanding of the concept of
probability, probability distributions, and how
they are applied to solve practical problems in
engineering and industry.
Full practical illustrations are given using the
Probability functions within Microsoft Excel.
What Does the Course Cover?
- The concept of
probability – its meaning and interpretation
- Conditional
probability and Thomas Bayes
- Similarities and
differences between probabilistic and
statistical analysis
- Discrete and
continuous distributions
- Distributions used
for measurement error
- Distributions used in
reliability engineering
- Quality control
applications of probability
- Markov analysis
- Extreme value
distributions
- Overview of other
useful techniques such as Statistical
Process Control (SPC), Six Sigma, etc.
Applications and practical examples are
provided throughout.
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