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
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Prof. Dr. Academic Educator
Prof. Dr. Academic Educator
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 0 votes
- 3 stars: 3 votes
- 4 stars: 3 votes
- 5 stars: 6 votes
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