Abstract
Probability theory is a part of mathematics that aims to provide insights into phenomena that depend on chance or on uncertainty. A basic treatment of probability from a perspective of engineers who are going to use the probability theory as a support for the practical reliability analyses is presented. Probability can be defined in terms of frequency of occurrence, as a percentage of successes in a large number of similar situations. Or probability of the event may express the subjective belief about the event. The mathematical representation of probability theory starts with set theory and basic probability concepts. The definition of factorial and the Pascal triangle represents the background for the theory of combinations. The theory of combinations determines the possible grouping of objects. There are three processes of interest: (i) permutations, (ii) combination, and (iii) variations, which are actually a union of the other two. One could say a permutation is an ordered combination. When the objects of a group are arranged in a certain order, the arrangement is called a permutation. In a permutation, the order of the objects is very important. The conditional probability of an event is the probability given that another event has occurred. Bayes theorem can be seen as a way of understanding how the probability that a theory is true is affected by a new piece of evidence. A random variable is any variable determined by chance and with no predictable relationship to any other variable. The term random variable is presented in theory and examples. Distribution is a degree to which the outcomes of events are evenly spread over the possible values. Probability distribution function is a function that represents probabilities to which the outcomes of events are spread over the possible values. The probability distribution functions are presented. The bathtub failure rate concept is widely used to represent failure behavior of many engineering items. The term bathtub stems from the fact that the shape of the failure rate curve resembles a bathtub. The bathtub curve consists of three periods: (i) an infant mortality period with a decreasing failure rate, (ii) a normal life period or useful life period with a low and relatively constant failure rate, and (iii) a wear-out period that exhibits an increasing failure rate.
The probable is what usually happens
Aristotle
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Kolmogorov A (1993) Grundbegriffe der Warscheinlichkeitsrechnung. Springer Verlag, Berlin
Shiryaev AN (1996) Probability. Springer, New York
Bertsekas DP, Tsitsiklis JN (2002) Introduction to probability. Athena Scientific, Belmont, MA
Rychlik I, Rydén J (2006) Probability and risk analysis: an introduction for engineers. Springer, New York
Durrett R (1991) Probability: theory and examples. Wadsworth-Brooks/Cole, Pacific Grove, CA
Tijms H (2007) Understanding probability: chance rules in everyday life. Cambridge University Press, Cambridge
Feller W (1968) An Introduction to probability and its applications. Wiley, New York
Chung KL (1974) Elementary probability with stochastic processes. Springer, New York
Vesely W, Dugan J, Fragola J et al (2002) Fault tree handbook with aerospace applications. National Aeronautics and Space Administration
Kumamoto H, Henley EJ (1996) Probabilistic risk assessment and management for engineers and scientists. IEEE, New York
Weisstein E, Pascal’s triangle: From MathWorld-A Wolfram Web Resource. http://mathworld.wolfram.com/PascalsTriangle.html. Accessed 4 Aug 2010
Letter frequencies. http://www.simonsingh.net/The_Black_Chamber/frequencyanalysis.html. Accessed 24 Aug 2010
NIST/SEMATECH e-handbook of statistical methods. http://www.itl.nist.gov/div898/handbook/. Accessed 24 Aug 2010
Atwood CL, La Chance JL, Martz HF et al (2003) Handbook of parameter estimation for probabilistic risk assessment (NUREG/CR-6823). Nuclear Regulatory Commission
MIL-HDBK-338 (1984) Electronic reliability design handbook
Dhilon BS (2007) Applied reliability and quality. Springer, London
Bain LJ, Engelhardt M (1992) Introduction to probability and mathematical statistics. PWS-Kent, Boston
Box GEP, Tiao GC (1973) Bayesian inference in statistical analysis. Addison-Wesley, Reading
Çinlar E (1975) Introduction to stochastic processes. Prentice-Hall, Englewood Cliffs, NJ
Derman C, Gleser LJ, Olkin I (1973) A guide to probability theory and application. Holt, Rinehart and Winston, New York
Meester R (2008) A natural introduction to probability theory. Birkhäuser Basel, Boston, MA
Geiss C, Geiss S (2009) An introduction to probability theory. http://users.jyu.fi/~geiss/scripts/introduction-probability.pdf. Accessed 27 July 2010
Williams D (1991) Probability with martingales. Cambridge University Press, Cambridge
Billingsley P (1995) Probability and measure. Wiley, New York
Bauer H (2001) Measure and Integration Zheory. Walter de Gruyter, Berlin
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2011 Springer-Verlag London Limited
About this chapter
Cite this chapter
Čepin, M. (2011). Probability Theory. In: Assessment of Power System Reliability. Springer, London. https://doi.org/10.1007/978-0-85729-688-7_4
Download citation
DOI: https://doi.org/10.1007/978-0-85729-688-7_4
Published:
Publisher Name: Springer, London
Print ISBN: 978-0-85729-687-0
Online ISBN: 978-0-85729-688-7
eBook Packages: EngineeringEngineering (R0)