The Art of Statistics | David Spiegelhalter


May 20th, 2022

1 hr 1 min 40 secs

Season 19

Your Host

About this Episode

Support the show:
Find David online:
Read David's article "Will I live longer than my cat?":
Watch the video of this episode:

Memorable Quotes from the show:

[00:23:36] "...essentially what probability theory allows us to do is to make assumptions about how the world works, how the data is generated, and turn it and flip it around after we observe some data into statements about our uncertainty about underlying features of the world. We can do that, which of course is very explicit based on work indeed, where after processing data or uncertainty and it turns into uncertainty about the underlying quantities."

Hightlights of the show:

[00:01:29] Guest Introduction

[00:03:08] Talk to us about how you first got interested in statistics and what was it that drew you to this field?

[00:04:55] Why is it that it seems like mathematicians tend to dislike teaching statistics?

[00:08:27] What is statistical science and what is it all about?

[00:09:46] You talk about in your book, The Art of Statistics, how to handle problems and approach problems in statistics. You call the P, p, b, a C cycle. Tell us about that framework.

[00:15:03] You mentioned in the book that statistics is to blame for the reproducibility and replication crises in science. Why? Why is that?

[00:18:23] When we talk about induction and inductive inference, should the philosopher in us get worried at all about the problem of induction in statistics?

[00:19:40] Tell our audience about the 'normal distribution'.

[00:20:34] Do you have any examples of when inductive inference has failed in statistics that you could share with us?

[00:22:15] Why do we need probability theory when we're doing statistics?

[00:26:25] I think pouring into the Bayesian stuff is kind of taking a step back here, maybe first principles. But what is probability? How do we measure it? It seems like such a strange epistemological concept.

[00:28:27] Can we say there's a at least some type of difference between epistemic probability and some physical or I believe you say aleatory?

[00:30:03] Would there be a difference in the way that a philosopher or a statistician would interpret probability?

[00:38:32] What's the Bayesian approach all about and why is it that courts in the UK are banning it or have banned it?

[00:40:16] How is this (Bayesian approach) different from the frequentist approach to viewing probability? What's the central difference?

[00:44:55] It seems like the prior distribution is something that makes base them so controversial. Why is that?

[00:46:18] It seems like Bayes Theorem is the scientifically correct way to change your mind when you get new evidence, right?

[00:48:18] David Deutsch mentioned lately about the Bayesian-ism, and he's having some qualms with Bayesian ism. He says that Bayesian-ism becomes controversial when you try to use it as a way to generate new ideas or judge one explanation against another. How do we reconcile that when we're faced with some epistemic.

[00:49:51] About using it to help us in our everyday lives to make better decisions. How can we use Bayes in that context?

[00:53:15] It is 100 years in the future. What do you want to be remembered for?

Random Round

[00:54:17] What do you believe that other people think is crazy?

[00:55:02] What are you most curious about right now?

[00:55:55] What are you currently reading?

[00:58:33] What do you like most about your family?

[00:58:53] What was your best birthday?

Don't forget to register for regular office hours by The Artists of Data Science:
Register for Sunday Sessions here:
Listen to the latest episode:

The Artists of Data Science Social links:
Support the show:

Episode Comments