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Содержание слайда: NATCOR
STOCHASTIC MODELLING
(preliminary reading)
Introduction to Probability
& Random Variables
IMPORTANT
This material is designed to be viewed is two ways:
In ‘Slide Show’ format, to take advantage of the animations;
In ‘Notes Page’ format, so that you can see the accompanying notes.
You might find it helps to print out the latter (to refer to) whilst viewing the former.
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Содержание слайда: Overview
Concepts
Laws and Notation
Conditional Probability
Total Law of Probability
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Содержание слайда: BASIC PROBABILITY CONCEPTS: ‘Experiments’ and ‘Events’
Experiment: an action whose outcome is uncertain (roll a die)
Sample Space: set of all possible outcomes of an experiment (S = {1, 2, 3, 4, 5, 6})
Event: a subset of outcomes that is of interest to us (e.g. event 1 = even number, event 2 = higher than 4, event 3 = throw a 2, etc)
Probability: measure of how likely an event is to occur (between 0 and 1)
№4 слайд
Содержание слайда: Classical Definition
Classical Definition
- Calculate, assuming events equally likely
Relative Frequency Approach
- Doing an experiment, using historical data
Subjective/Bayesian Probability
- Trusting instinct, using judgement
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Содержание слайда: Discrete Random Variables
№16 слайд
Содержание слайда: Probability Mass Function (pmf)
of a discrete random variable
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Содержание слайда: Expected value and variance of discrete random variables
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Содержание слайда: Expected value and variance of combinations of discrete random variables
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Содержание слайда: Poisson Random Variable
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Содержание слайда: Poisson Random Variable
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Содержание слайда: Poisson Random Variable
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Содержание слайда: Continuous Random Variables
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Содержание слайда: Expected value and variance of continuous random variables
№28 слайд
Содержание слайда: Expected value and variance of combinations of continuous random variables
NB. Exactly same as for discrete r.v.
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Содержание слайда: Exponential Random Variable
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Содержание слайда: Exponential Random Variable
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Содержание слайда: Exponential Example
THEORY
IF Events occur ‘at random’, at rate A per unit time.
THEN: Time between events has an Exponential distribution, with mean of 1/A.
AND: Time to next event has an Exponential distribution, with mean of 1/A.
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Содержание слайда: Normal Random Variable
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Содержание слайда: Standardised Normal Random Variable
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Содержание слайда: Normal Random Variables
Important (in general) because:
Many naturally occurring r.v.’s have a Normal distribution, e.g. weights, heights …
Many useful statistics behave as Normal r.v.’s, even if the r.v.’s from which they derive are not Normal, e.g. Central Limit Theorem.