Random Variable Probability And Expectation

Random Variable, Probability,Expectation,Moment and Moment Generating function.

What you'll learn
Random Variables , Probability, Expectation, Moments and Moment generating function
Requirements
All Prerequisites are Covered in Course only so need of any prerequisite.
Description
In this course, You will be going to learn Random Variable, Types of Random variable, Expectation, Variance, Standard Deviation, Moment and Moment generating function with respect to Discrete and Continous Random variable. This course will build a strong foundation probability and statistics. In this course, all types of problems are systematically organized and solve with clear crystal explanation.

Overview

Section 1: Introduction and Basics

Lecture 1 Introduction

Lecture 2 Random Variables

Lecture 3 Types of random Variable

Section 2: Probability in Discrete Random Variable

Lecture 4 Probability Mass Function

Lecture 5 Properties of PMF

Lecture 6 Cumulative distribution function

Lecture 7 Road Map of Course

Lecture 8 Sample Space of Experiment

Section 3: Probability Computation in Discrete Random Variable [Exercise-1]

Lecture 9 Overview of Exercise-1

Lecture 10 Type-A [1]

Lecture 11 Type-A [2]

Lecture 12 Type-A [4]

Lecture 13 Type-A [5]

Lecture 14 Type-B [1]

Lecture 15 Type-B [2]

Lecture 16 Type-B [3.1]

Lecture 17 Type-B [3.2]

Lecture 18 Type-B [4.1]

Lecture 19 Type-B [4.2]

Lecture 20 Type-B [5]

Lecture 21 Type-B [6]

Lecture 22 Type-B [7]

Section 4: Probability Computation in Continuous Random Variable [Exercise-2]

Lecture 23 Overview of Exercise-2

Lecture 24 Type-A [1]

Lecture 25 Type-A [2.1]

Lecture 26 Type-A [2.2]

Lecture 27 Type-A [3]

Lecture 28 Type-B [1]

Lecture 29 Type-B [1]

Lecture 30 Type-B [3]

Lecture 31 Type-B [4]

Lecture 32 Type-B [5.1]

Lecture 33 Type-B [5.2]

Lecture 34 Type-B [6]

Lecture 35 Type-B [7]

Lecture 36 Type-C [1]

Lecture 37 Type-C [2]

Lecture 38 Type-C [3]

Section 5: Expectation

Lecture 39 Expectation in Discrete Random variable

Lecture 40 Expectation in Continuous Random variable

Lecture 41 Variance

Section 6: Exercise-1 [calculation of expectation]

Lecture 42 Exercise-1 Overview

Lecture 43 Type-A [1]

Lecture 44 Type-A [3]

Lecture 45 Type-A [4]

Lecture 46 Type-A [5]

Lecture 47 Type-A [6]

Lecture 48 Type-B [1]

Lecture 49 Type-B [2]

Lecture 50 Type-B [4]

Lecture 51 Type-B [5.1]

Lecture 52 Type-B [5.2]

Lecture 53 Properties of Line of Variance

Lecture 54 Type-C [1]

Lecture 55 Type-C [2]

Lecture 56 Type-C [3]

Lecture 57 Type-C [4]

Section 7: Moment and Moment Generating Function

Lecture 58 Moment Introduction

Lecture 59 Definition of Moment

Lecture 60 Types of Moment

Lecture 61 Mathematical expression of Moments

Lecture 62 Moment Generating Function

Lecture 63 Mathematical expression of MGF

Lecture 64 How to Generate MGF ?

Lecture 65 Why MGF is Useful ?

Section 8: Exercise-2 [Calculation of Moment and MGF]

Lecture 66 Exercise-2 Overview

Lecture 67 Type-A [1.1]

Lecture 68 Type-A [1.2]

Lecture 69 Type-A [4.1]

Lecture 70 Type-A [4.2]

Lecture 71 Type-A [5]

Lecture 72 Type-A [6]

Lecture 73 Type-A [7]

Lecture 74 Type-B [1]

Lecture 75 Type-B [2.1]

Lecture 76 Type-B [2.2]

Engineering Students,Management Students,Industry Professional,Mathematics Scholars and Research Scholars.