Overview
Ref Books

###### 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.

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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

View Theorems Chapter 1

Title : Probability function
Type : Presentation

View Probability function

Title : Probability function-I
Type : Presentation

View Probability function-I

Title : Chapter 3 Expectation
Type : Other

View Chapter 3 Expectation

Title : Chapter 4: Generating Function
Type : Other

View Chapter 4: Generating Function