All About that Bayes: Probability, Statistics, and the Quest to Quantify Uncertainty 

"Most people view statisticians as a hybrid between an accountant and a wizard, which is ridiculous, we have nothing in common with accountants." OMG, this woman.

I am in awe. This is my new favorite person ever.

Not many people could make this topic both funny and yet informative. I am so happy I found this video.

Can't believe I watched this just because I was randomly interested, AND I thoroughly enjoyed learning and watching the entire lecture. If only I could learn more things from her! A fantastic presentation with just the right amount of humor. Being an expert does not always mean being a good teacher. She clearly is both!

What a confident, smart and bright woman. The most amazing and enlightening lecture or class about bayesian and frequentist statistics ever.

There is lots of noise out there about Bayesian and Frequentist methods. This talk clearly lays out the different approaches. And she is hilarious to boot!

I came here expecting to learn about Bayes Theorem. I did not expect I'd fall in love.

I have been re-watching this for years now. I still get new insights from this tremendous hour. Over time I have come to believe that a sense of humor is perhaps the single most important tool in the Lennox toolbox.

This was an amazing talk. Thanks so much for making this available. Bring her back to discuss more topics.

Great talk! It is untrivial to find a knowledgeable person that knows how to communicate knowledge. There are plenty of smart people who can't explain things to less equipped people such as myself. There are also plenty of not so smart people who give 'entertaining' talks, but which don't translate any true information. Where smart meets the ability to communicate, therewithin lies gold.

This is the best stats talk I’ve ever seen !! I’m a fan

@Kristin Lennox - awesome job on this talk; clear presentation and juxtapositions on Bayesian and Frequentist Statistics, and a great example application on the successful search for the submarine 'Scorpion' in the Atlantic -- *thank you!*

She is definitely one of the best statistics speaker.

She talks fast to keep her audience tuned or because she knows what to say in and out. In any case she kept my attention for the entire lecture time.

Phenomenal talk! This should be added to the material for any statistics / probability course!

I love the descriptions of the pictures of Thomas Bayes

Brilliant lecture!

This is the best I've watched on this topic. Thank you!

Delightful. I came back to watch again and saw I had marked it with a thumbs down. I didn’t mean to do that! What’s not to like? A clear lecture, and with jokes.

Starting at 39:40: "De Finetti never actually worked with quantum physics...might of changed his mind." Lennox is talking about the belief that randomness as an objective reality does not exist and so probability based on the concept of randomness does not exist either but only probability as a description of our uncertainty in our beliefs or knowledge about a certain event. Lennox makes the statement that if De Finetti had met up with quantum physicists then he might have changed his mind because a lot of quantum physics has to do with fundamental randomness. The fundamental irony here is that in fact the opposite has occurred: there is now a branch of physics called quantum bayesianism - qbism for short - which has, in fact, followed De Finetti. Qbism believes that was is touted to be objective randomness of processes in quantum physics can be better explained by our (the observers) lack of certainty in what is going on at the quantum level. Although there are issues with this interpretation (as with any interpretation) it does provide intuitive - almost trivial - explanations for some highly non-intuitive - and literally incomprehensible - explanations in "classical" quantum physics including the concept of an instantly collapsing probability wavefront across all of space and the concept of quantum entanglement. This last concept has to do with the idea that if one particle is observed to have a particular property value then an entangled particle will instantly display a related property value no matter how far the particles are apart. Qbism states that all that is happening is our knowledge is being updated. So for example, if I have a pair of socks, one of which is red and one of which is blue and with my eyes closed I put one in one suitcase and the other in another suitcase and close the suitcases. I then send one suitcase to my cousin across the world. If I then open the suitcase I kept and see that the sock is blue then I instantly know that the sock in the other suitcase is red. In Qbism there is no randomness as to the color of the sock before being observed but simply the degree of certainty of our knowledge about the colors of the socks in each suitcase.

Really fantastic.

Amazing, amazing talk!

I wish I watched this lecture seven years ago

this is great

I think I'd really like to fall in love with someone through their lectures.

Really really nice presentation.

I'm a full-blown Bayesian, but I will look to priors derived from Frequentist techniques if I can't derive nor find one of my own that I deem reasonably believable.

6:40: Probability is a measure. Distribution, Parameter and Likelihood.

its credible stunning ..i love statistics being statistician

Great talk!

I'm going to take a Bayesian approach and say the probability that her next presentation is fantastic is greater than 0.5 and that all other predictions are ignorant.

8:00: Statisticians define distribution according to a thing called parameters.

17:00:The word frequentist referes to the long range frequency of experiments.

24:40:They calculate the conditional distribution of a parameter theta given the observed data X.

Laplace's 5,000 years for the Sun may be rooted in that time's belief that the Earth was created in 4004 BC.

purely awsome

4:40: The central difference between frequentist and bayesian is what they mean when they say that they are quantifying uncertainty.

This is epic.

43:00 Some people use probably as intermediate step. One example of bayesian search.

brilliant woman

great!

18:20: When I say I want to use. Bayesian is about a state of belief.

Thanks much. Can anyone use an analogy in the context of football match to explain Bayesian statistics for prediction purposes.

34:00: Bayesian: credible interval. Frequentist: confidence interval.

28:10: The confusion involving Bayesian statistics is you are calculating probability distributions on probabilities.

Even When you say that a “die is fair”, it is subjective, cause there is no way of knowing this in advance. You have to “believe it” for mathematical convenience.

42:40: We take the interpretation of probability very seriously. Because we have to. Statitisian deliver probability products. Any time you get a statistical interval, or a result of a statistical hypothesis test, that is wether explicity statistical probability or a function of a probability.

24:30: What bayesians do is to use bayesian theorem to perform inference about distribution of parameters.

27:17: The only way of doing inference on small data.

7:50: The way you allocate those fraction of probability, among individual events or a set of events, is call probably distribution. Distribution defines the measure of events.

(at 51:08) " . . . I was raised Frequentist . . ."

subjective =/= judgement. it means that uncertainty is a product of the subject: ignorance. As opposed to objective uncertainty of frequentism.

I don't see how throwing a dice and spinning a top are different?

😂 I like her. Good talk.

Why is the top subjective?

The introducer sounded like Owen Wilson the whole time.

There is a mistake on likelihood slide. It should be Pr(theta | x).

am I the only one who didn't quite get the difference between the blue die, and golden top? @17:15

33:40: Uncertainty of 5 %.

I have a crush in this lady :)

My thing.

There is no fight between frequentists and Bayesians; there is only Bayesians and the ignorant

Is she really confused about the words die and dice, or is she just trying to reflect most people’s problem deciding which is similar and which is plural?

If you're not fighting, are you really doing statistics?

You can’t assess if your hypothesis is true (accept H0) you can only not reject H0. It’s a fallacy to believe a hypothesis is true merely because it isn’t contradicted by facts.

_________________

40:26: All bayesians do subjective probability.

John kriek ww2

I don't like her, but she is freaking awesome ... By the way, smoking can cause cancer .. but cancer (a terminal one, for instance) could make you start smoking ...

то, что можно прочитать за 5(10) минут - пересказывать целый час... PR?

53:40 tells the story of why medical literature is total mess. If you don’t introduce science, the statistics will lead you astray

She's under a lot of stress.

Quantum mechanics isn't relevant in the macroscopic world. For anything outside the subatomic world, Laplace was correct and all uncertainty is ignorance

More of this silly Bayesian vs frequentist garbage.