Probability and Random Variables

Probability and Random Variables, available at $39.99, has an average rating of 4.35, with 20 lectures, based on 12 reviews, and has 1885 subscribers.

You will learn about Probability and Random Variables This course is ideal for individuals who are Anyone interested in probability and random variables It is particularly useful for Anyone interested in probability and random variables.

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Summary

Title: Probability and Random Variables

Price: $39.99

Average Rating: 4.35

Number of Lectures: 20

Number of Published Lectures: 20

Number of Curriculum Items: 20

Number of Published Curriculum Objects: 20

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Probability and Random Variables

Who Should Attend

Anyone interested in probability and random variables

Target Audiences

Anyone interested in probability and random variables

In this course probability and random variables are thought. First, the basic concepts from of probability concepts such as experiment, sample space, events are explained. Then, repeated trials, permutations, combinations, and multiplication rule, etc. are explained. Following basic topics of probability, random variables are introduced. Probability mass functions are explained by examples. Well known probability distributions, such as Bernoulli, uniform, poisson etc, are examplified. Cumulative distribution function, joint distribution, and calculation of joint distribution functions are taught. A random variable is continuous if possible values comprise either a single interval on the number line or a union of disjoint intervals.

Discrete random variables can take only a countable number of possible values. On the other hand, a continuous random variable has a range in the form of an interval or a union of non-overlapping intervals on the real line (possibly the whole real line). Thus, we need to develop new tools to deal with continuous random variables. The good news is that the theory of continuous random variables is completely analogous to the theory of discrete random variables. After studying the discrete random variables, we focus on continuos random variables, and introduce probability density function. Then, we cover the same set of topics as it is done for discrete random variables.

Course Curriculum

Chapter 1: Experiment, Joint Experiment, Events, Probability Function, Prob. Axioms,

Lecture 1: Introduction

Lecture 2: Experiment, Trial, Sample Space, Events

Lecture 3: Probability function, Probability laws, Joint experiment, Prob. of an event

Lecture 4: Sample space and event prob. calculation of the joint experiments, examples

Lecture 5: Properties of probability function and their proofs.

Chapter 2: Prob. function, conditional prob. total prob. theorem, multiplication rule,

Lecture 1: Conditional Probability

Lecture 2: Total probability theorem and Bayes' Rule

Lecture 3: Multiplication rule and Independence

Lecture 4: Conditional Independence

Lecture 5: Independent Trials and Binomial Probabilities

Chapter 3: Counting Principle, Permutations, Combinations, Partitions

Lecture 1: Counting Principle, Permutations, Combinations

Lecture 2: Partitions

Chapter 4: Discrete Random Variables

Lecture 1: Introduction to Discrete Random Variables

Lecture 2: Introduction to Discrete Random Variables (Continued)

Chapter 5: Probability mass function, cumulative dist. function, mean value, and variance

Lecture 1: Probability mass function of discrete random variables

Lecture 2: Cumulative Distribution Functions of Discrete Random Variables, Part-1

Lecture 3: Cumulative Distribution Functions of Discrete Random Variables, Part-2

Lecture 4: Mean Value and Variance of Discrete Random Variables

Lecture 5: Mean Value and Variance for a Function of Discrete Random Variable

Chapter 6: Well-Known Random Variables

Lecture 1: Well-Known Discrete Random Variables

Instructors

Prof. Dr. Academic Educator
Prof. Dr. Academic Educator

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3 stars: 3 votes
4 stars: 3 votes
5 stars: 6 votes

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