Probability made easy: Continuous randomness
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Probability made easy: Continuous randomness

Get ready for a college exam
4.8 (2 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
1,136 students enrolled
Created by Dynamic Lectures
Last updated 1/2016
English
Current price: $10 Original price: $20 Discount: 50% off
1 day left at this price!
30-Day Money-Back Guarantee
Includes:
  • 2 hours on-demand video
  • 36 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • learn how to predict the results of continuous random events (expected value)
  • learn how to predict how much on average the actual results would deviate from your estimate (standard deviation)
  • 18 theoretic video lectures and lectures with motivations
  • 17 practice video lectures marked as easy, intermediate and advanced
  • more than 50 pages of transcripts of video lectures
  • hundreds of slides, and
  • my help (post your questions on the board!)
View Curriculum
Requirements
  • familiarity with such notions as outcomes, events and probability
Description

This course is a part in a series of courses that covers a complete course in probability theory taught in the US colleges.

In this course you will learn continuous probability theory. You will learn how to predict the results of continuous random events and how to predict how much on average the actual results would deviate from your estimate.

If you are looking for an efficient way to learn/review probability theory, this course is for you. With dynamic slides, each hour of the series covers the material of more than a week of regular live lectures!

You may review lectures as many times as you want, skip easy exercises when the material is familiar, choose your own pace! If you need help, I will answer every question you post on the discussion board. If you are not completely satisfied, I offer a 30 day money back guarantee.

Who is the target audience?
  • students who would like an efficient tutorial
  • students who would like a review before an exam
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Curriculum For This Course
37 Lectures
01:54:13
+
Introduction
1 Lecture 01:40
+
Distribution and Density Functions
5 Lectures 16:31
Probability distribution function: Motivation
01:56

Probability density function: Definition
02:27

Problem solving (easy)
03:55

Problem solving (intermediate)
04:04

Cumulative distribution function
04:09
+
Uniform Random Variable
3 Lectures 10:20
Uniform random variable
03:34

Problems solving (easy)
01:34

Problem solving (intermediate)
05:12
+
Conditional Probability
4 Lectures 11:40
Conditional probability: definition
03:21

Conditional Probability: theorem
03:18

Problem solving (easy)
02:43

Problem solving (easy)
02:18
+
Exponential Density
5 Lectures 20:47
Exponential density
04:35

Problem solving (easy)
07:47

Problem solving (easy)
03:41

Memorylessness
01:52

Problem solving (advanced)
02:52
+
Independence of Random Variables
10 Lectures 30:06
Two properties of distribution functions
01:28

Independent random variables
04:00

Joint distribution functions
02:34

Problem solving (easy)
01:31

Joint density function
02:59

Problem solving (easy)
01:19

Independence of random variables: Theorem
03:55

Density functions computed from the joint density function (trick)
05:05

Problem solving (intermediate)
04:58

Problem solving (intermediate)
02:17
+
Expected Value and Variance
5 Lectures 13:26
Expected value
01:43

Properties of expected value
01:45

Problem solving (easy)
03:53

Variance
02:16

Problem solving (easy)
03:49
+
Thank you!
1 Lecture 00:00
Thank you!
1 page
About the Instructor
Dynamic Lectures
4.5 Average rating
29 Reviews
3,003 Students
6 Courses

I am a professional mathematician. As a mathematician I worked in US, Mexico, Japan, Canada and Germany. I am an author of 16 research papers published in internationally renowned journals.

I taught courses ranging from middle school to PhD level, including such high level courses as Topological Quantum Field Theory, Moduli spaces of Riemann curves, and Topological Surgery Theory.

What you may expect from me is a well structured course with clearly explained notions and theory.