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Course Contents

Probability set function. Axioms of probability. Conditional probability and independence. Total Probability and Bayes theorem. Random variables. Distribution function, probability function and probability density function. Chebyshev’s inequality. Moments, factorial moments and cumulants. Probability generating function. Moment generating function. Cumulant generating function. Univariate distributions. Discrete Uniform, Binomial, Hypergeometric, Multinomial, Poisson, Geometric, Negative Binomial, Normal distribution and their properties, Continuous Uniform, Exponential, Gamma, Log-Normal, Double Exponential Distribution and their properties.

Course Synopsis

To discuss the concept of probability models, random variable and its functions and to familiarize students with certain parametric families of univariate density functions and their application to real world problems.

Course Learning Outcomes

The students should be able to learn the basic concept of probability and solve the application of probability related problems.


Probability explained | Independent and dependent events | Probability and Statistics | Khan Academy

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[Discrete Mathematics] Axioms of Probability

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Addition rule for probability | Probability and Statistics | Khan Academy

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Conditional Probability With Venn Diagrams & Contingency Tables

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The Law of Total Probability

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Conditional probability and combinations | Probability and Statistics | Khan Academy

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Basics of Probability: Unions, Intersections, and Complements

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Introduction to Discrete Random Variables and Discrete Probability Distributions by jbstatistics

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An Introduction to Continuous Probability Distributions

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Expected Value and Variance of Discrete Random Variables

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Deriving the Mean and Variance of a Continuous Probability Distribution

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An Introduction to the Binomial Distribution

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The Poisson Distribution: Mathematically Deriving the Mean and Variance

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An Introduction to the Geometric Distribution by Jbstatistics

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Moment Generating Function of Geometric Distribution, Lecture | Sabaq.pk | by Sabaq Foundation - Free Videos & Tests, Grades K-14

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Mean and Variance of Geometric Distribution by Dr. Harish Garg

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11 Negative Binomial Distribution & its Moment Generating Function (MGF) by This Makes It Easy

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Negative Binomial Distribution - Derivation of Mean, Variance & Moment Generating Function (English) by Computation Empire

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Introduction to the normal distribution | Probability and Statistics | Khan Academy

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Normal Distribution | Moment Generating Function | Mean & Variance By MGF

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Moments of a Normal Distribution by statisticsmatt

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Point of Inflexion of Normal Distribution, Lecture | Sabaq.pk |

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Uniform Distribution by A Statistical Path

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Exponential Distribution by A Statistical Path

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Gamma Distribution Definition by Lawrence Leemis

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Gamma Distribution ( Mathematical Statistics) by Sonali Singh

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Log-Normal Distribution | Derivation of Mean, Variance & Moments (in English) by Computation Empire

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Double Exponential Distribution | Derivation of Mean, Variance & MGF (in English) by Computation Empire

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Book Title : Introduction to Mathematical Statistics
Author : Hogg R V & Craig A T,
Edition : 7th
Publisher : Prentice-Hall International, Inc. Engle Wood Cliff, N.T.
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Book Title : Introduction to the Theory of Statistics
Author : A. M. Moods, F.D Graybill and D.C. Bocs,
Edition : 3rd
Publisher : McGraw Hill International Editition
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Title : Introduction to Statistical Theory
Type : Reference Book

View Introduction to Statistical Theory


Title : Theorems Chapter 1
Type : Presentation

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Title : Probability function
Type : Presentation

View Probability function


Title : Probability function-I
Type : Presentation

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Title : Chapter 3 Expectation
Type : Other

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Title : Chapter 4: Generating Function
Type : Other

View Chapter 4: Generating Function