I'm an undergrad going for a major in statistics and minors in computer science and philosophy. I also read a lot of philosophy and cognitive science on the side. I don't have the patience to read through all of the LW sequences. Which LW sequences / articles do you think are important for me to read that I won't get from school or philosophy reading?

Some political predictions (Edited for formatting):

• Another stock market slump within the next year: 50% (70% within two years)
• Cor: Average stock value collapse, given slump, of 70%, +- 10%: 90%
• Trump to get Republican nomination: 65%
• Cruz to get Republican nomination: 35%
• Hillary to get Democratic nomination: 30%
• Rel: Hillary to be indicted on criminal charges: 50%
• Sanders to get Democratic nomination: 60%
• Republicans to win 2016 presidential race, regardless of nomination: 80%
• Republicans to win moderate majority in both houses in 2016: 80%
• Republicans to keep moderate majority in congress in 2018 given economic crash: 60%
• Republicans to keep at least parity in congress in 2018 given economic crash: 80%
• Republicans to keep moderate majority in congress in 2018 without economic crash: 30%
• Republicans to keep at least parity in congress in 2018 without economic crash: 60%
• Democrats to win 2020 presidential election without economic crash: 40%
• Democrats to win 2020 presidential election with economic crash: 10%
• Democrats to win 2024 presidential election, given loss of 2020 presidential election, without economic crash: 80%
• Democrats to win 2024 presidential election, given loss of 2020 presidential election, with economic crash: 70%
• US National Health Database goes online in next ten years: 30%
• WHO to change Health Index ranking rules substantially given the US national health database goes online: 60%
• WHO to change Health Index ranking rules substantially given the US national health database doesn't go online: 10%
• Average global temperatures to warm by more than .7 degrees (Celsius) over the next ten years: 0%
• Average global temperatures to warm by more than .5 degrees (Celsius) over the next ten years: 0%
• Average global temperatures to warm by more than .3 degrees (Celsius) over the next ten years: 10%
• Average global temperatures to warm by more than .1 degrees (Celsius) over the next ten years: 20%
• Average global temperatures to warm by more than .07 degrees (Celsius) over the next ten years: 30%
• Average global temperatures to warm by more than .04 degrees (Celsius) over the next ten years: 70%
• Major military conflict between two first world nations over the next ten years: 10%
• Threat of major military conflict between two first world nations over the next ten years: 70%

Moderately.

On the plus side it's forcing people to acknowledge the uncertainty involved in many numbers they use.

On the minus side it's treating everything as a normal (Gaussian) distribution. That's a common default assumption, but it's not necessarily a good assumption. To start with an obvious problem, a lot of real-world values are bounded, but the normal distribution is not.

Link: Introducing Guesstimate, a Spreadsheet for Things That Aren’t Certain

How useful do you think this actually is?

"Everydayrationalism."

Absolutely agree it is important for scientists to know about cognitive biases. Francis Bacon, the father of the empirical method, explicitly used cognitive biases (he called them "idols," and even classified them) as a justification for why the method was needed.

I always said that Francis Bacon should be LW's patron saint.

I don't have any problem with Bayesian epistemology at all. You can have whatever epistemology you want.

What I do have a problem with is this "LW myopia" where people here think they have something important to tell to people like Ed Witten about how people like Ed Witten should be doing their business. This is basically insane, to me. This is strong evidence that the type of culture that gets produced here isn't particularly sanity producing.

Solomonoff induction is useless to know about for anyone who has real work to do (let's say with actual data, like physicists). What would people do with it?

jacob_cannell above seems to think it is very important for physicists to know about Solomonoff induction.

Solomonoff induction is one of those ideas that keeps circulating here, for reasons that escape me.

If we are talking about Bayesian methods for data analysis, almost no one on LW who is breathlessly excited about Bayesian stuff actually knows what they are talking about (with 2-3 exceptions, who are stats/ML grad students or up). And when called on it retreat to the "Bayesian epistemology" motte.

Bayesian methods didn't save Jaynes from being terminally confused about causality and the Bell inequalities.