Probability Lecture 1: Events, probabilities & elementary combinatorics - 1st Year Student Lecture

[@edbertkwesi4931]

there is an 80 % chance of rain what an ammazing way to begin.

[@user20517]

Writing on the white board makes learning and understanding math easier than just quickly reading it from powerpoint slides, although it takes more efforts from the lecturer and student to write. Thank you

[@barryparsons6092]

at 11.35 wonderful ; the concept of ink and think .

[@jorgejoaquindelgadogomez4745]

Mathias is a fantastic Professor!

[@kwiky5643]

Learning from the best, thanks 💪

[@mgamgam]

we love matthias 🙏

[@shahulrahman2516]

Watching at 1.75x makes it more engaging

[@Hermes1548]

‘Is weather random? Lots of philosophical questions here’ (min. 1:41). My reason to click on the opportunity to hear this lecture precisely. Popper (1934, 1959, The Logic of Scientific Discovery) has some piercing critiques on Bayesian-Probabilistic scientific methodology.

[@kishou]

please cite your primary source by Thomas Bayes (i.e. doctrine of chances, etc).

[@Hermes1548]

I’m sure what you say is true, but my remark was not on the practical side, but on the philosophical side. As Popper says in The Two Fundamental Problems of the Theory of Knowledge, corroboration cannot be based on probability. I have read a philosopher deciding a question of fact via Bayesian probability, which cannot prove confirmation of a fact (event, theory). Footnote 11 of Popper’s 1978 Introduction to the work mentioned above reads: At the time of writing The Two Fundamental Problems, and for many years after that, I did not move significantly beyond the following intuitive insights: (1) Newton’s theory is exceedingly well corroborated. (2) Einstein’s theory is at least equally well corroborated. (3) Newton’s and Einstein’s theories largely agree with each other; nevertheless, they are logically inconsistent with each other because, as for instance in the case of strongly eccentric planetary orbits, they lead to conflicting predictions. (4) Therefore, corroboration cannot be a probability (in the sense of the calculus of probabilities). Unfortunately, until recently I have neglected to think through the intuitively very plausible point (4) in detail and to prove it through points (1), (2) and (3). But the proof is simple. If corroboration were a probability, then the corroboration of “Either Newton or Einstein” would be equal to the sum of the two corroborations, for the two logically exclude each other. But as both are exceedingly well corroborated, they would both have to have a greater probability than ½ (½ would mean: no corroboration). Thus, their sum would be greater than 1, which is impossible. It follows that corroboration cannot be a probability. These thoughts may be generalised: they lead to a proof that the probability of even the best corroborated universal laws is equal to zero. Peter Havas (“Four-Dimensional Formulations of Newtonian Mechanics and their Relation to the Special and the General Theory of Relativity”, Reviews of Modern Physics 36 (1964), pp. 938 ff.) has shown that Newton’s theory may be rendered in a form that is very similar to Einstein’s theory, with a constant k that in Einstein’s case becomes k = c (c is the velocity of light) and in Newton’s case k = ¥. But then there will be more mutually exclusive theories with c ≤ k ≤ ∞ that are denumerable, all of them being at least as well corroborated as Newton’s theory. (We avoid randomly distributed a priori probabilities.) In any case, from this set of theories one can select denumerable sets; for example, theories with k = c; k = 2c; …; k = nc; …; k = ¥. Since any two different theories in this infinite sequence are logically inconsistent with each other, the sum of their probabilities probabilities cannot be greater than 1. From this it follows that Newton’s exceedingly well-corroborated theory with k = ¥ has a vanishing probability. (Therefore, the degree of corroboration cannot be a probability in the sense of the calculus of probabilities.) It would be interesting to hear what the theoreticians of induction - such as the Bayesians, for instance, who identify the degree of corroboration (or the “degree of rational belief”) with a degree of probability - would have to say about this simple refutation of their theory. That was all. @kavorka8855

[@paromita_ghosh]

Why deny science

[@paromita_ghosh]

Wtf

[@yesimyesim4710]

O i wish i could listen that beautiful lectures while being there😢 i wish i was great student and got a chance to go oxford.

[@aditya_visart]

I just tried to come up with a deduction as follows: Consider the statement, "80% chance of rain on this Friday". So, we perceive the following: a. the chance 80% is estimated from data statistically (i.e. a statistical estimate). b. an estimation is performed in a deterministic way, because it involves a computation technique. c. so, a statistical estimation is carried through measurement (or observation) using a computation technique. d. furthermore, a measurement involves measurement randomness due to computation approximation and measuring unit. Let me know, if the above points are having some discrepancies or not.

[@matiippolito5625]

I love maths and sometimes I dont, but Oxford lecturers do know how to explain things clearly. Humans have a hard time processing probability its not in our nature to be able to comprehend these types of concepts 😂.

[@yorha2b278]

Obviously he knows his subject very very well.

[@unidentified5390]

Hes reading of the paper I think

[@yorha2b278]

@@unidentified5390 For the blind, yes.

[@Fluoroantimonic09]

@@unidentified5390don't you see him clearly not reading the paper ?

[@unidentified5390]

@@Fluoroantimonic09 I did

[@wlmarvin]

aaaaaannnnddd... u got a first ✌️😎

[@SunitaSingh-fk1ck]

Very good teacher

[@AbdulDsouza]

Outstanding!!!

[@AbdulDsouza]

Thank God he chose to teach!!!!

[@GhulamNabiDar]

I want to get boards used here..... Beautiful lecture.....

[@AbdulDsouza]

Makes a parallel progress

[@ZaibiDesigner]

Hey sir, I just watched your video and I must say that it was really informative and well-made. I was wondering if I could help you edit your videos and also highly engaging thumbnails which will help your video to reach to a wider audience.

[@vansf3433]

If you put set difference as A\B, instead of A - B, it can also be interpreted as conditional probability, which means that the notation is ambiguous Statistics is subjective, because the same set of data can be interpreted in different ways.It depends on each individual's purposes how it's interpreted

[@HabibuMukhandi]

isn't conditional probability notated by A|B and not A\B?

[@ansmunir5277]

Can you please upload the full lecture series?

[@OxfordMathematics]

We'll be showing six lectures which are a self-contained set (though part of a bigger lecture series of 16).

[@ansmunir5277]

@OxfordMathematics That's great but why not all the 16 lectures? If you upload all the lectures, it will help us to understand the subject completely. Because all those students who can not get to oxford still want to learn from the top university. Thank you.

[@OxfordMathematics]

@@ansmunir5277 We want to give an introduction for people to then go away and find out more. We also have to consider our own students. There are some full courses on the channel including the Introduction to University Mathematics course

[@ansmunir5277]

Okay. Thank you.@@OxfordMathematics

[@srinivasadusumilli7881]

Thank you Oxford for these lectures @@OxfordMathematics

[@michaelkoch6863]

Nice run, but the basics are simple.

[@miguelgonzalezperez4832]

Excellent!

[@AzCode-ux3uv]

Hi, how can I love maths? How can I love a difficult thing like this. It's take my time to dive into but almost time I actually dont understand. Sometime, I got excited feeling when I undertstand some math's definition. I dont know how to love it, how to deal with it. How can I explore and dive into Math with positive feeling in almost time?

[@burnere633]

Who is the lecturer?

[@stephenmma]

Professor Matthias Winkel

[@burnere633]

@@stephenmma Thank you.

[@DanMusceac]

One who talks too much.

[@sarkarsubhadipofficial]

❤

[@aryan_71]

Any indians here who are watching this❤

[@jha-bhaskar]

Yup

[@mitsunam7001]

I think someone's brain is not braining right now..... 🤯 🧠

[@mehradmoini20]

Thanks so much for sharing these valuable lectures. I have two questions: 1- will you also kindly share the future lectures of this course on probability? 2- would you please also share which textbooks or references are being used for this course or alternatively is there a link to the course material one can use?

[@davidbock2863]

I'm not sure, but I think that's John Malkovich...

[@ΠετροςΝικου-β5δ]

20

[@Zlapped25]

I got 80% chances to get an ads on this video

[@toninotonnato7776]

For a second I thought that was John Malkovich

[@DeviousDevan-b1p]

I have Prob & Stats final exams in 2 days 😭😂

[@ibrahimcamur34]

Türkçe altyazı ekleyin.

[@zfg07]

Whya re they using white board

[@donaldhenderson5039]

Visual Reference for Everybody and to attach sub points to.

[@JessyP-u6q]

College statistics sir

[@JessyP-u6q]

Return Umbrellas Maths Debts Mortgage Scrap The data collected by your camera has recorded missing things of .......of my house so the probability of retrieval is impossible Random chance of watching the same rain ......is ............peculiar ......models ....... How the models appeared in the lobby of university .....how they got funds ???? AM

[@painpeace3619]

Too much writing.

[@sean.maloney]

You’ll fail no matter what. I feel bad for u