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If You Say Something Is “Likely,” How Likely Do People Think It Is?

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Re: If You Say Something Is “Likely,” How Likely Do People Think It Is?

#51

Post by ehrman »

tinalumfoil wrote: post #35
roter wrote: post #27

For what it is worth, the Intergovernmental Panel on Climate Change uses the following definitions[0]: virtually certain: 99-100% extremely likely: 95-100% very likely: 90-100% likely: 66-100% about as likely as not: 33-66% more likely than not: >50-100% more unlikely than likely: 0- unlikely: 0-33% very unlikely: 0-10% extremely unlikely: 0-5% exceptionally unlikely: 0-1% [0]: https://ipcc.ch/pdf/assessment-report/a…

> virtually certain: 99-100% Hopefully whoever wrote that never works in a data center, builds cars, sells insurance, gambles, works on crypto, does scientific computing, or is ever responsible for someone's life.

If you're talking the realm of five 9s, etc, that's in reference to service availability at some given point in time throughout the course of a year. If you discuss the probability there will be an outage once during a year, the answer is somewhere in the middle, around "more likely than not".

You could use this same probability around a pacemaker. The device is virtually certain (99%) to function at a given point throughout the year, but the probability that the device will not fail over the course of the year is not 99%. If the pacemaker had a 99% chance of not failing once during the course of a year, it would be virtually certain it would not fail during that year.

Re: If You Say Something Is “Likely,” How Likely Do People Think It Is?

#52

Post by ScottBurson »

pacificpendant wrote: post #12

When people say things like "serious possibility" they are not merely intending to alter the perception of the likelihood but also attempting to impress upon the listener the gravity of the event. In cold war era America would people have felt any different knowing that a Russian invasion was only 20% likely rather than 30%? For something so /serious/ any non-zero probability is something that should be prepared for.

Yes, I had the same thought. A "serious possibility" of global thermonuclear war is 1% (maybe smaller). A "serious possibility" of a hangnail is 80%.

Re: If You Say Something Is “Likely,” How Likely Do People Think It Is?

#53

Post by evandijk70 »

crispyambulance wrote: post #11

It depends on the context. Hillary Clinton had a >70% of winning the US presidential election according to the most responsible analyses (see 538: https://projects.fivethirtyeight.com/2016-election-forecast/ ). Most folks took 70% to mean that she would certainly win and were bitterly disappointed the morning after. On the other hand no sane person would (willingly) play Russian roulette with a 70% or even 5 of 6 cha…

Most people, bookmakers and statisticians thought Hillary Clinton had more than 90% chance to win the electronisch - Nate Silver was aan outlier

Re: If You Say Something Is “Likely,” How Likely Do People Think It Is?

#54

Post by arendtio »

crispyambulance wrote: post #11

It depends on the context. Hillary Clinton had a >70% of winning the US presidential election according to the most responsible analyses (see 538: https://projects.fivethirtyeight.com/2016-election-forecast/ ). Most folks took 70% to mean that she would certainly win and were bitterly disappointed the morning after. On the other hand no sane person would (willingly) play Russian roulette with a 70% or even 5 of 6 cha…

> In everyday life, one conflates probability with severity of outcome.

My everyday example for that is the weather forecast and the question 'will it rain' often answered with a precipitation probability?

- Probability: How likely is it that I will be hit by at least one rain drop

- Severity: How many rain drops will hit me

It sounds a little abstract, but whenever I see some everyday weather forecast I wonder what they are trying to tell me. At least 0% seems unambiguous to me :-)

Re: If You Say Something Is “Likely,” How Likely Do People Think It Is?

#55

Post by safgasCVS »

"Lesson 1: Use probabilities instead of words to avoid misinterpretation."

Probabilities are meaningless unless it’s a repeatable experiment otherwise its a ludic fallacy eg "There's a 70% chance of Hillary winning". This is an un-provable statement. Either she wins and prediction was right, or she loses and it counts as part of the 30%. This is Nate Silver's get-out-of-jail-free card so even when he's wrong he comes off as being right.

i.e. this statement makes sense in a casino and nowhere else.

"Lesson 2: Use structured approaches to set probabilities."

Probabilities are meaningless by themselves. Path dependency matters a great deal to actual humans but not to business professors. A strategy that works well for the ensemble wont necessarily work well for the individual.

e.g. if you save for retirement for the average life expectancy then 50% of the people would be screwed and 50% of the people would have saved too much.

i.e. The cost of being right/wrong is what matters and not the probability.

Re: If You Say Something Is “Likely,” How Likely Do People Think It Is?

#56

Post by arendtio »

roter wrote: post #27

For what it is worth, the Intergovernmental Panel on Climate Change uses the following definitions[0]: virtually certain: 99-100% extremely likely: 95-100% very likely: 90-100% likely: 66-100% about as likely as not: 33-66% more likely than not: >50-100% more unlikely than likely: 0- unlikely: 0-33% very unlikely: 0-10% extremely unlikely: 0-5% exceptionally unlikely: 0-1% [0]: https://ipcc.ch/pdf/assessment-report/a…

Sounds like it is 'exceptionally unlikely' that the police will find alcohol in my blood after I drank 3 bottles of wine ;-)

(Yes, I am mixing things up here)

Re: If You Say Something Is “Likely,” How Likely Do People Think It Is?

#57

Post by musage »

Depending on context, I just might ignore it as the padding it is. Same with the negative "I'm not entirely sure X is true" which is either becoming more common, or which I notice more and more. Hiding goal posts in a swamp is worse than moving them.

Re: If You Say Something Is “Likely,” How Likely Do People Think It Is?

#58

Post by TTPrograms »

OscarCunningham wrote: post #34
DINKDINK wrote: post #31

Earlier quoted context omitted.

>Hillary Clinton had a >70% of winning the US presidential election Probabilities without confidence intervals[1] are by-and-large meaningless (She has a 90% chance of of winning with a confidence interval of +11% -100%). No amount of d3.js on 538's blog will change this. https://en.wikipedia.org/wiki/Confidence_interval

From a Bayesian perspective, or from a betting one, it doesn't make sense to put probabilities in a confidence interval. You might be uncertain about the world, but you can be certain about how much uncertainty you have, since it's a property of your own mind.

It might be of some general interest to note that there exist such objects - distributions over distributions, or metaprobabilities. They have practical use - for example, if you are playing a game with uncertainty, you might observe something in the next step that changes your belief, or distribution over world state, b = P(s). If you have some expected distribution of next observations then you can talk about the probability of having some belief in the next state. Roughly P(b'|b) = P(P(s')|P(s)). You can collapse this into simple probabilities if you just care about your new observations, P(obs'|b) = \sum_s P(obs'|s)P(s|b).

I could imagine some frameworks where confidence intervals in this way would be useful - ex. I have 3 fairly different world models that I think are equally likely, each has a P(election), what's the P(election|world) and get confidence intervals across world models rather than just summing over them to P(election). But I agree that for most common approaches that simple probabilities are most useful and clear.

Re: If You Say Something Is “Likely,” How Likely Do People Think It Is?

#59

Post by computerphage »

DINKDINK wrote: post #31
crispyambulance wrote: post #11

It depends on the context. Hillary Clinton had a >70% of winning the US presidential election according to the most responsible analyses (see 538: https://projects.fivethirtyeight.com/2016-election-forecast/ ). Most folks took 70% to mean that she would certainly win and were bitterly disappointed the morning after. On the other hand no sane person would (willingly) play Russian roulette with a 70% or even 5 of 6 cha…

>Hillary Clinton had a >70% of winning the US presidential election Probabilities without confidence intervals[1] are by-and-large meaningless (She has a 90% chance of of winning with a confidence interval of +11% -100%). No amount of d3.js on 538's blog will change this. https://en.wikipedia.org/wiki/Confidence_interval

> Probabilities without confidence intervals are by-and-large meaningless.

That's just not true. If I believe that my team has a 20% chance to win and you offer me a bet with anything better than 5-to-1 odds I should take the bet. If you offer me anything worse than 5-to-1, then I should not take the bet. There's no fuzz factor necessary; no confidence interval that I need to use to make the decision.

Perhaps you're getting at the idea of calibration? That it's difficult for a person to know what a 20% chance feels like? But there are still a lot of situations where it's not up to human judgement.

Re: If You Say Something Is “Likely,” How Likely Do People Think It Is?

#60

Post by OscarCunningham »

fragsworth wrote: post #38
OscarCunningham wrote: post #34

Earlier quoted context omitted.

From a Bayesian perspective, or from a betting one, it doesn't make sense to put probabilities in a confidence interval. You might be uncertain about the world, but you can be certain about how much uncertainty you have, since it's a property of your own mind.

How do we quantify the difference between coin tosses, which we are very certain is 50% likely to end up heads, from political elections, where we only have a few examples to go off of?

Good question.

The difference is how the probability changes in response to new information. Learning more about the coin won't change the probability of heads from 50%, but doing more exhaustive polls would have likely improved our prediction about the election.

However I don't think there's as much of a difference as you think. If we learnt more about how the coin was going to be flipped then that would certainly improve our estimate of the outcome. If we found out the exact way it would be flipped we could calculate the outcome exactly.

So we can't really compare the two situations quantitatively, since there's no way to match up like-for-like the information we could receive. But we can say, for each possible piece of information we could receive, how much we expect it to change our probability.

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