![History
• The scientific study of probability is a modern development.
Gambling shows that there has been an interest in quantifying the
ideas of probability for millennia, but exact mathematical
descriptions arose much later. There are reasons of course, for the
slow development of the mathematics of probability. Whereas
games of chance provided the impetus for the mathematical study
of probability, fundamental issues[clarification needed] are still
obscured by the superstitions of gamblers. Christiaan Huygens
probably published the first book on probability](https://image.slidesharecdn.com/applicationofprobabilityindailylifeandincivilengineering-160801185041/85/Application-of-probability-in-daily-life-and-in-civil-engineering-3-320.jpg)
![History
• According to Richard Jeffrey, "Before the middle of the seventeenth century, the
term 'probable' (Latin probabilis) meant approvable, and was applied in that sense,
univocally, to opinion and to action. A probable action or opinion was one such as
sensible people would undertake or hold, in the circumstances." However, in legal
contexts especially, 'probable' could also apply to propositions for which there was
good evidence.
• The sixteenth century polymath Gerolamo Cardano demonstrated the efficacy of
defining odds as the ratio of favourable to unfavourable outcomes (which implies
that the probability of an event is given by the ratio of favourable outcomes to the
total number of possible outcomes ). Aside from the elementary work by Cardano,
the doctrine of probabilities dates to the correspondence of Pierre de Fermat and
Blaise Pascal (1654). Christiaan Huygens (1657) gave the earliest known scientific
treatment of the subject Jakob Bernoulli's Ars Conjectandi (posthumous, 1713) and
Abraham de Moivre's Doctrine of Chances (1718) treated the subject as a branch of
mathematics.See Ian Hacking's The Emergence of Probability and James Franklin's
The Science of Conjecture[full citation needed] for histories of the early development
of the very concept of mathematical probability.
• .](https://image.slidesharecdn.com/applicationofprobabilityindailylifeandincivilengineering-160801185041/85/Application-of-probability-in-daily-life-and-in-civil-engineering-4-320.jpg)
![History
• The theory of errors may be traced back to Roger Cotes's Opera
Miscellanea (posthumous, 1722), but a memoir prepared by
Thomas Simpson in 1755 (printed 1756) first applied the theory to
the discussion of errors of observation.[citation needed] The
reprint (1757) of this memoir lays down the axioms that positive
and negative errors are equally probable, and that certain
assignable limits define the range of all errors. Simpson also
discusses continuous errors and describes a probability curve](https://image.slidesharecdn.com/applicationofprobabilityindailylifeandincivilengineering-160801185041/85/Application-of-probability-in-daily-life-and-in-civil-engineering-5-320.jpg)
![History
• Daniel Bernoulli (1778) introduced the principle of the maximum
product of the probabilities of a system of concurrent errors.
• Adrien-Marie Legendre (1805) developed the method of least
squares, and introduced it in his Nouvelles méthodes pour la
détermination des orbites des comètes (New Methods for
Determining the Orbits of Comets).[citation needed] In ignorance
of Legendre's contribution, an Irish-American writer, Robert
Adrain, editor of "The Analyst" (1808), first deduced the law of
facility of error,](https://image.slidesharecdn.com/applicationofprobabilityindailylifeandincivilengineering-160801185041/85/Application-of-probability-in-daily-life-and-in-civil-engineering-7-320.jpg)
![History
• In the nineteenth century authors on the general theory included
Laplace, Sylvestre Lacroix (1816), Littrow (1833), Adolphe Quetelet
(1853), Richard Dedekind (1860), Helmert (1872), Hermann Laurent
(1873), Liagre, Didion, and Karl Pearson. Augustus De Morgan and
George Boole improved the exposition of the theory.
• Andrey Markov introduced[citation needed] the notion of Markov
chains (1906), which played an important role in stochastic processes
theory and its applications. The modern theory of probability based on
the measure theory was developed by Andrey Kolmogorov
(1931).[citation needed]
• On the geometric side (see integral geometry) contributors to The
Educational Times were influential (Miller, Crofton, McColl,
Wolstenholme, Watson, and Artemas Martin)](https://image.slidesharecdn.com/applicationofprobabilityindailylifeandincivilengineering-160801185041/85/Application-of-probability-in-daily-life-and-in-civil-engineering-8-320.jpg)
![Definition
• Probability is the measure of the likeliness that an event will
occur.[1] Probability is quantified as a number between 0 and 1
(where 0 indicates impossibility and 1 indicates certainty). The
higher the probability of an event, the more certain we are that
the event will occur. A simple example is the toss of a fair coin.
Since the two outcomes are equally probable, the probability of
"heads" equals the probability of "tails", so the probability is 1/2
(or 50%) chance of either "heads" or "tails".](https://image.slidesharecdn.com/applicationofprobabilityindailylifeandincivilengineering-160801185041/85/Application-of-probability-in-daily-life-and-in-civil-engineering-9-320.jpg)
Application of probability in daily life and in civil engineering
- 1. 1
- 2. Application of probability in Daily life and in Civil engineering Presented by: Engr Habib ur Rehman Chandio Department of Civil Engineering University of Wah, Wah Cantt.
- 3. History • The scientific study of probability is a modern development. Gambling shows that there has been an interest in quantifying the ideas of probability for millennia, but exact mathematical descriptions arose much later. There are reasons of course, for the slow development of the mathematics of probability. Whereas games of chance provided the impetus for the mathematical study of probability, fundamental issues[clarification needed] are still obscured by the superstitions of gamblers. Christiaan Huygens probably published the first book on probability
- 4. History • According to Richard Jeffrey, "Before the middle of the seventeenth century, the term 'probable' (Latin probabilis) meant approvable, and was applied in that sense, univocally, to opinion and to action. A probable action or opinion was one such as sensible people would undertake or hold, in the circumstances." However, in legal contexts especially, 'probable' could also apply to propositions for which there was good evidence. • The sixteenth century polymath Gerolamo Cardano demonstrated the efficacy of defining odds as the ratio of favourable to unfavourable outcomes (which implies that the probability of an event is given by the ratio of favourable outcomes to the total number of possible outcomes ). Aside from the elementary work by Cardano, the doctrine of probabilities dates to the correspondence of Pierre de Fermat and Blaise Pascal (1654). Christiaan Huygens (1657) gave the earliest known scientific treatment of the subject Jakob Bernoulli's Ars Conjectandi (posthumous, 1713) and Abraham de Moivre's Doctrine of Chances (1718) treated the subject as a branch of mathematics.See Ian Hacking's The Emergence of Probability and James Franklin's The Science of Conjecture[full citation needed] for histories of the early development of the very concept of mathematical probability. • .
- 5. History • The theory of errors may be traced back to Roger Cotes's Opera Miscellanea (posthumous, 1722), but a memoir prepared by Thomas Simpson in 1755 (printed 1756) first applied the theory to the discussion of errors of observation.[citation needed] The reprint (1757) of this memoir lays down the axioms that positive and negative errors are equally probable, and that certain assignable limits define the range of all errors. Simpson also discusses continuous errors and describes a probability curve
- 6. History • The first two laws of error that were proposed both originated with Pierre-Simon Laplace. The first law was published in 1774 and stated that the frequency of an error could be expressed as an exponential function of the numerical magnitude of the error, disregarding sign. The second law of error was proposed in 1778 by Laplace and stated that the frequency of the error is an exponential function of the square of the error. The second law of error is called the normal distribution or the Gauss law. "It is difficult historically to attribute that law to Gauss, who in spite of his well-known precocity had probably not made this discovery before he was two years old."
- 7. History • Daniel Bernoulli (1778) introduced the principle of the maximum product of the probabilities of a system of concurrent errors. • Adrien-Marie Legendre (1805) developed the method of least squares, and introduced it in his Nouvelles méthodes pour la détermination des orbites des comètes (New Methods for Determining the Orbits of Comets).[citation needed] In ignorance of Legendre's contribution, an Irish-American writer, Robert Adrain, editor of "The Analyst" (1808), first deduced the law of facility of error,
- 8. History • In the nineteenth century authors on the general theory included Laplace, Sylvestre Lacroix (1816), Littrow (1833), Adolphe Quetelet (1853), Richard Dedekind (1860), Helmert (1872), Hermann Laurent (1873), Liagre, Didion, and Karl Pearson. Augustus De Morgan and George Boole improved the exposition of the theory. • Andrey Markov introduced[citation needed] the notion of Markov chains (1906), which played an important role in stochastic processes theory and its applications. The modern theory of probability based on the measure theory was developed by Andrey Kolmogorov (1931).[citation needed] • On the geometric side (see integral geometry) contributors to The Educational Times were influential (Miller, Crofton, McColl, Wolstenholme, Watson, and Artemas Martin)
- 9. Definition • Probability is the measure of the likeliness that an event will occur.[1] Probability is quantified as a number between 0 and 1 (where 0 indicates impossibility and 1 indicates certainty). The higher the probability of an event, the more certain we are that the event will occur. A simple example is the toss of a fair coin. Since the two outcomes are equally probable, the probability of "heads" equals the probability of "tails", so the probability is 1/2 (or 50%) chance of either "heads" or "tails".
- 10. Definition • These concepts have been given an axiomatic mathematical formalization in probability theory (see probability axioms), which is used widely in such areas of study as mathematics, statistics, finance, gambling, science (in particular physics), artificial intelligence/machine learning, computer science, and philosophy to, for example, draw inferences about the expected frequency of events. Probability theory is also used to describe the underlying mechanics and regularities of complex systems.
- 11. Applications • • Probability theory is applied in everyday life in risk assessment and in trade on financial markets. Governments apply probabilistic methods in environmental regulation, where it is called pathway analysis. • A good example is the effect of the perceived probability of any widespread Middle East conflict on oil prices—which have ripple effects in the economy as a whole. An assessment by a commodity trader that a war is more likely vs. less likely sends prices up or down, and signals other traders of that opinion. Accordingly, the probabilities are neither assessed independently nor necessarily very rationally.
- 12. Applications • The theory of behavioral finance emerged to describe the effect of such groupthink on pricing, on policy, and on peace and conflict. • The discovery of rigorous methods to assess and combine probability assessments has changed society. It is important for most citizens to understand how probability assessments are made, and how they contribute to decisions.
- 13. Applications • Another significant application of probability theory in everyday life is reliability. Many consumer products, such as automobiles and consumer electronics, use reliability theory in product design to reduce the probability of failure. Failure probability may influence a manufacturer's decisions on a product's warranty. • The cache language model and other statistical language models that are used in natural language processing are also examples of applications of probability theory.
- 14. Applications • Consider an experiment that can produce a number of results. The collection of all results is called the sample space of the experiment. The power set of the sample space is formed by considering all different collections of possible results. For example, rolling a die can produce six possible results. One collection of possible results gives an odd number on the dice. Thus, the subset {1,3,5} is an element of the power set of the sample space of dice rolls. These collections are called "events." In this case, {1,3,5} is the event that the dice falls on some odd number. If the results that actually occur fall in a given event, the event is said to have occurred. • A probability is a way of assigning every event a value between zero and one, with the requirement that the event made up of all possible results (in our example, the event {1,2,3,4,5,6}) is assigned a value of one. To qualify as a probability, the assignment of values must satisfy the requirement that if you look at a collection of mutually exclusive events (events with no common results, e.g., the events {1,6}, {3}, and {2,4} are all mutually exclusive), the probability that at least one of the events will occur is given by the sum of the probabilities of all the individual events.
- 15. Applications • It can also be used to in real-time analysis of piezo electric current transfer of pressure through electric impulses due to strain and stress concentration at localized spots. Like this the applications are many with the modern Civil Engineering taking a huge leap into modernity with the aid of electronics, it becomes more fun and highly technical to use probability and Statistics in Civil Engineering • It can be used in amplification and fine tuning of resonant frequency wave identification in Wind Structures, to monitor remotely the structural health of a structure (such as a bridge, tall building, dams etc).
- 16. Applications • every two years 3 cyclones hit the coastal area of Andhra Pradesh and Orissa states. If it is assumed that the cyclone hitting the coastal areas follows Poisson distribution then what is the probability of two cyclones crossing the coastal area of Andhra Pradesh and Orissa in the next two years • It is useful in risk assessment • it can be used for random decrement analysis. • In earth quake engineering, in a specific time interval the probability of occurrence of an earth quake at a particular fault follows Poisson distribution. Occurrence of cyclones in a particular time period follows Poisson distribution.
- 17. Applications • Two major applications of probability theory in everyday life are in risk assessment and in trade on commodity markets • probability theory in everyday life is reliability. Many consumer products, such as automobiles and consumer electronics, utilize reliability theory in the design of the product in order to reduce the • a toss of a coin may result in either a head or a tail. Also, the sex of a new-born baby may turn out to be male or female. In these cases, the individual outcomes are uncertain. With experience and enough repetition, however, a regular pattern of outcomes can be seen (by which certain predictions can be made). • In the twentieth century probability is used to control the flow of traffic through a highway system • a telephone interchange, or a computer processor; find the genetic makeup of individuals or populations; figure out the energy states of subatomic particles; Estimate the spread of rumors; and predict the rate of return in risky investments. • When a meteorologist states that the chance of rain is 50%, the meteorologist is saying that it is equally likely to rain or not to rain. If the chance of rain rises to 80%, it is more likely to rain. If the chance drops to 20%, then it may rain, but it probably will not rain.
- 18. Thank you … … for paying attention