this post was submitted on 09 Sep 2024
194 points (84.4% liked)

News

23259 readers
3379 users here now

Welcome to the News community!

Rules:

1. Be civil


Attack the argument, not the person. No racism/sexism/bigotry. Good faith argumentation only. This includes accusing another user of being a bot or paid actor. Trolling is uncivil and is grounds for removal and/or a community ban. Do not respond to rule-breaking content; report it and move on.


2. All posts should contain a source (url) that is as reliable and unbiased as possible and must only contain one link.


Obvious right or left wing sources will be removed at the mods discretion. We have an actively updated blocklist, which you can see here: https://lemmy.world/post/2246130 if you feel like any website is missing, contact the mods. Supporting links can be added in comments or posted seperately but not to the post body.


3. No bots, spam or self-promotion.


Only approved bots, which follow the guidelines for bots set by the instance, are allowed.


4. Post titles should be the same as the article used as source.


Posts which titles don’t match the source won’t be removed, but the autoMod will notify you, and if your title misrepresents the original article, the post will be deleted. If the site changed their headline, the bot might still contact you, just ignore it, we won’t delete your post.


5. Only recent news is allowed.


Posts must be news from the most recent 30 days.


6. All posts must be news articles.


No opinion pieces, Listicles, editorials or celebrity gossip is allowed. All posts will be judged on a case-by-case basis.


7. No duplicate posts.


If a source you used was already posted by someone else, the autoMod will leave a message. Please remove your post if the autoMod is correct. If the post that matches your post is very old, we refer you to rule 5.


8. Misinformation is prohibited.


Misinformation / propaganda is strictly prohibited. Any comment or post containing or linking to misinformation will be removed. If you feel that your post has been removed in error, credible sources must be provided.


9. No link shorteners.


The auto mod will contact you if a link shortener is detected, please delete your post if they are right.


10. Don't copy entire article in your post body


For copyright reasons, you are not allowed to copy an entire article into your post body. This is an instance wide rule, that is strictly enforced in this community.

founded 1 year ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
[–] [email protected] 0 points 1 month ago* (last edited 1 month ago) (1 children)

First, we need to distinguish Silver's state-by-state prediction with his "win probability". The former was pretty unremarkable in 2016, and I think we can agree that like everyone else he incorrectly predicted WI, MI, and PA.

However, his win probability is a different algorithm. It considers alternate scenarios, eg Trump wins Pennsylvania but loses Michigan. It somehow finds the probability of each scenario, and somehow calculates a total probability of winning. This does not correspond to one specific set of states that Silver thinks Trump will win. In 2016, it came up with a 28% probability of Trump winning.

You say that's not "getting it wrong". In that case, what would count as "getting it wrong"? Are we just supposed to have blind faith that Silver's probability calculation, and all its underlying assumptions, are correct? Because when the candidate with a higher win probability wins, that validates Silver's model. And when that candidate loses, that "is not evidence of an issue with the model". Heads I win, tails don't count.

If I built a model with different assumptions and came up with a 72% probability of Trump winning in 2016, that differs from Silver's result. Does that mean that I "got it wrong"? If neither of us got it wrong, what does it mean that Trump's probability of winning is simultaneously 28% and 72%?

And if there is no way for us to tell, even in retrospect, whether 28% is wrong or 72% is wrong or both are wrong, if both are equally compatible with the reality of Trump winning, then why pay any attention to those numbers at all?

[–] [email protected] 2 points 1 month ago* (last edited 1 month ago) (1 children)

I think you're missing the point of predictive modeling. It's probability of separate outcomes is built in. This isn't fortune telling, there is no crystal ball. Two predictive models can have different predictions and they both may have value. Just like separate meteorologists can have different forecasts, but predict accurately the same amount over time, all be it at different intervals. IIRC, the average meteorologist correctly predicts rain over 80% of the time. They are far over predicting by chance. But if you look at the forecast in more than one place you often get slightly different forecasts. They have different models and yet arrive at similar conclusions usually getting it mostly accurate. It's the same with political forecasts, they are only as valuable as your understanding of predictive modeling. If you think they are intended to mirror reality flawlessly, you will be sorely disappointed. That doesn't make the models "wrong", it doesn't make them "right" either. They are just models that usually predict a probable outcome.

[–] [email protected] 0 points 1 month ago

I don't expect a model to be perfect. But it is certainly possible for one model to be better than another, for example one might think the Weather Channel forecast is less accurate than AccuWeather (at least for your region).

Which, in turn, means that it is possible to decide when a forecast is more "right" or "wrong" than another, because what other basis would you have for judging which is better?