'Discrete sample space' diaporamas de présentation

Probability & Statistical Inference Lecture 2

Probability & Statistical Inference Lecture 2. MSc in Computing (Data Analytics). Lecture Outline. Introduction Introduction to Probability Theory Discrete Probability Distributions Question Time. Introduction. Probability & Statistics.

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Probability Theory:

Probability Theory: . Probability theory is the branch of mathematics concerned with analysis of random phenomena. (Encyclopedia Britannica).

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BCOR 1020 Business Statistics

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Objectives (BPS chapter 10)

Objectives (BPS chapter 10). Introducing probability The idea of probability Probability models Probability rules Discrete sample space Continuous sample space Random variables. Randomness and probability.

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Lecture 14

Lecture 14. Continuous sample space, Special case of the law of large numbers, and Probability density function. A non-discrete sample space. Sample space: I = {x: 0 ? x <1} Probability function: For an event E , e.g. an interval within the sample space, then P(E) = length of E .

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Lecture 10: Discrete Probability

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Lecture 10: Discrete Probability

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