Probability and Statistics: Overview

This is the introductory overview video in a new series on Probability and Statistics! Probability and Statistics are cornerstones of modern data science and machine learning, and this short course will rapidly cover all of the basics and get into advanced topics. The course is roughly structured into four parts: Introduction to Probability (5 hours), Introduction to Statistics (5 hours), Advanced Probability (5 hours), and Advanced Statistics (5 hours).

Special thanks to Dr. John Quintanilla from the University of North Texas for his inspiring lectures that first got me excited about Probability and Statistics! Thanks Dr. Q!

This video was produced at the University of Washington, and we acknowledge funding support from the Boeing Company

%%% CHAPTERS %%%
00:00 Intro
02:22 Applications of Probability
08:07 Divination and the History of Randomness and Complexity
10:30 Randomness and Uncertainty?
12:26 Defining Probability and Statistics
14:51 Outline of Topics: Introduction
16:36 Random Variables, Functions, and Distributions
22:30 Expected Value, Standard Deviation, and Variance
23:52 Central Limit Theorem
25:54 Preview of Statistics

[Eigensteve]

Special thanks to Dr. John Quintanilla from the University of North Texas for his inspiring lectures that first got me excited about Probability and Statistics! Thanks Dr. Q!

[Am-peiy]

People in science don't understand this enough. If you have the knowledge and experience this it's a moral obligation to share it. Imo people like you is the reason why we still have hope in this dark modern world. A lot of respect and appreciation.

[alexs]

I have a bachelors in math and a masters in data science, so technically I should be familiar with these things, but I don't feel like statistics ever clicked with me in the same way the other basic areas of maths did. Really looking forward to your lecture series on this.

[danielmrosser]

Honestly the best introduction to a truly essential branch of mathematics— widely used in engineering and physics modeling. All of modern technology and advancement of our understanding of how nature behaves are a direct result of the discovery and application of this field of mathematics, a product of astounding human ingenuity. Probabilistic modeling is a powerful mathematical tool that truly shines a light on developing practical solutions to otherwise intractable problems owing to the complexity of nature and human behavior. The most profound feature and remarkable gift of nature is that nearly all complex processes are imbued or characterized by a remarkably small set of numbers (statistical properties e.g., mean, variance, correlation) that tend to exhibit a surprising high degree of predictability. These properties can therefore be exploited to extract useful information to make decisions and reveal relationships among quantities (random variables) that would otherwise be hidden from view of a naive observer looking at raw data without the aid of Probability and statistics.

[Bollocks_Inc.]

I love that probability and statistics is getting some spotlight. In electrical engineering, people are often more familiar with calculus, algebra, differential equations and all that jazz, but probability and statistics is very sneaky and it is EVERYWHERE. I'm ecstatic to learn more about it and i'm glad that of all people you are doing a series on it. Thank you very much professor Brunton.

[martincardenas]

.I am now retired but I am following your lectures because I am very interested in the field of AI.
Your lectures show two things thát rarely coincide by a specialist: passion for the field and the gift of a good pedagogue.
Your lectures are really a pleasure. I am enjoying them.
Thank you very much for your knowledge and YOUR PRECIOUS TIME.

[HackionSTx]

I can't believe this. Thank you very much, professor Brunton. I'm eager for the rest of the course.

[eliegakuba]

I watched the introduction out of curiosity but couldn't take my eyes off the screen. You are an awesome teacher, Steve. I am looking forward to the entire series. I appreciate that the videos are no longer than 30 minutes, the average time most people can maintain focus without losing interest.

[bobtivnan]

Christmas came early this year. Thank you Dr. Brunton.

[josemariaroman]

Fantástico! I always regretted not having taken a course on probability and statistics. Now you are giving us this opportunity. Thank you.

[alarissacamila]

I am beyond grateful that I found this. Can not wait for the rest of the series. 🎉

[ahmedhamza]

This is a game changer in AI content world, these 4 heavy topics which make people run away from the core and the heart of AI and ML in single course just WOW, have no more words to say, only thank you professor for your great efforts

[ivlivs.c]

This is honestly the best overview of stats and probability I've seen. Can't wait to start this course!

[mainfranklin]

Thanks Steve for this new series.
May God bless you.

[gusromul]

really nice overview... im an old man (0x44yo) who did really well in school but had the hardest time with probability and random procs... looking forward to revisit the whole thing.. or the hole thing.. thanks steve

[zhezheng]

Cool! A new series! Thank you for making such nice videos!

[HassanKhan-csho]

So looking forward to this lecture series...Dr. Brunton Thank you

[gustavodelgadillo]

This has become one of my favourite channels great content, great pedagogy, superb expertise in every knowledge area that I feel like I am doing something wrong in having access to this for free, I am from Mexico and We don't have this quality of content even in our biggest Universities, so I cannot thank You enough, from the heart, Thank You professor and blessings in every thing You do.

[matejsedo]

Amazing video, I can't wait for the following videos on this topic

[marijnnederpelt]

Dude this is perfect timing!! Im currently following course on this topic