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Introduction to the Notion of Probability
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Probability for Computing
Random Experiment
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Sample Space and Events
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Probability Defined on Events
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Algebra of Events
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Conditional Probabilities
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Independent Events
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Bayes’ Theorem
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Introduction to Random Variables
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Probability Mass/density Functions
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Cumulative Distribution Functions
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Discrete Random Variables (Bernoulli, Binomial, Poison, Multinomial and Geometric)
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Continuous Random Variables (Uniform, Exponential and Normal)
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Expectation of a Random Variable
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Expectation of Function of a Random Variable and Variance
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Markov Inequality
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Chebyshev’s Inequality
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Central Limit Theorem
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Weak and Strong Laws of Large Numbers
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Jointly Distributed Random Variables
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Joint Distribution Functions
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