system
Given the following post, respond as if you're commenting on Reddit:
human
CMV: Political polls are easy to manipulate, political in nature (not 100% unbiased), and are generally used more for "spin" than to actually relay anything factual.

Some of you will say no shit Sherlock, but political polling has become so politicized in the current environment, that now is almost completely unreliable information, and I believe it's main purpose is to influence undecided voters to vote one way or another. i'll make a few points:

* Hacking voting booths, outright cheating and gerrymandering have muddied the waters so much politically...how in the world could a poll be THAT accurate

* It is known that polls can be "skewed" to make a point seem more valid. For example, asking a polling question about Hillary at a Republican or Trump rally will get you a certain set of results. Conversely If someone was asking Trump questions in San Francisco, where most voters are Democrat, it would show an unfavorable result for Trump

* Even more, the actual results of a poll can be reported any way they want you to see them. Meaning if there's an unfavorable aspect to a candidate in the results, but more favorable in another aspect, then the pollsters will highlight the good fact, but make no mention of the other fact. Polling organizations are supposed to be neutral and just conduct the research. 

This post came about because political advocates LOVE to tout a poll that supports their view, but then point to all of the inconsistencies when they don't like the results. The last general election in the US proved that between cheating and spin, no polls can really be trusted. My little caveat to add is that we should all have done enough personal research to know who we want to vote for, regardless of some inaccurate and biased poll.
gpt
> The last general election in the US proved that between cheating and spin, no polls can really be trusted.

That is the wrong conclusion to make based on the 2016 results.  First, polls have an error margin and the actual results were largely inside the error margins for the polls.

Next, there was a mistake that pollsters made which was not adjusting for education level and they've fixed that going forward.  If they sample 100 people and 60 of them are women and 40 men, but they know the demographics of the area they're targeting is 51% women and 49% men, what they'll do is their weight the responses of the sampled women by the ratio of 60 to 51.  They use this to adjust for gender, race, age, but traditionally have not used education level to weight their results.  In the 2016 election where one particular candidate got a huge response among voters with low levels of education it makes your polls very susceptible to error especially if you're polls don't happen to capture a perfectly representative amount of people at each education level.

They've learned from this and have made polls better going forward.  But it isn't necessarily possible to adjust for every possible factor and part of it is just learning as we go and respecting that that is part of why polls have error margins.

And especially when you have sources like 538 that takes the polling data and:

* Figures out if the polling company has historical bias and adjusts for that
* Figures out how reliable the polling company is and gives them extra weight or diminished weight based on historical accuracy
* Aggregates the polls together to assemble a result with a much larger number of sampled people.

And, at the end of the day, 538 used that data to come to the conclusion that Trump had a 30% chance of winning.  And that is exactly what happened.  People often jump on them saying they got it wrong.  But if the candidate you say has a 70% chance of winning wins every time, that isn't what a 70% chance looks like. 

I'll grant you that if their underlying data had been better and had adjusted for education levels, they would've had an even better prediction that likely would've had Trump at a higher percentage chance.  But that is why they also consider historical accuracy when making their models.  They know exactly how often polls get it wrong and to exactly what degree they got it wrong and use that as a basis for their calculation going forward.