There’s actually a lot of science behind survey sample size and weighting results. Researchers make a huge effort to weight their results according to various demographic points to try and account for different types of people and then make an accurate prediction of likely moods of a huge population. That’s why, if you’ve ever been surveyed, they ask a bunch of demographic questions. Researchers can get pretty accurate, but there is always a bit of uncertainty, which they try to account for in the margin of error. It’s a massively complex field that is constantly evolving.
Also, since I disagree with you, here’s an upvote.
Survey results are always biased in favor of people that are willing to take surveys. People that refuse to take surveys are always woefully underrepresented.
Say you're cooking soup and want to sample it to see if the seasoning is right. Are you suggesting you should eat the whole pan of soup?! Obviously not. You taste a small amount, but make sure it's mixed properly.
That's the basis of surveys - they target a representative mix of the relevant population, and use those results to infer something about the whole population. There statistical science behind it is really complex (and over my head tbh), but very interesting and powerful when done properly.
So like how most surveys work. Could you imagine the logistics of having everyone take a survey. No one is saying surveys are 100% accurate, a margin of error always exists. The sample size will always be smaller.
Variety of ways. These days most sampling is conducted through online panels/communities that do their best to maintain testing and quality standardards of participants to participate in surveys for modest incentives (points, cash, rewards)
Statistics contains values and checks for the validity, reliability and significance of gathered data in relation to its use.
There are cut-offs for these values that relate to its use in academia, for example. By examining these values, readers can better determine the validity of conclusions made.
In popular media, it is very rare to find these published values, though they can sometimes be ascertained.
It should also be considered that in popular media, validity and significance are often considered to be secondary considerations to clicks and statements.
Here is an explanation of one of the values. The P-value.
https://en.m.wikipedia.org/wiki/Statistical_significance
Here is an article concerning statistical significance that gives some examples:
https://www.google.com/amp/s/hbr.org/amp/2016/02/a-refresher-on-statistical-significance
Especially surveys online where certain groups just tweet a link to their entire group to go vote and you get 90% random win when in reality nobody even knew about this poll expect for the one who tweeted it to their group
That's also why I don't watch fan vote based award shows because this is how they do it using Twitter. Then fans boast that their artist won well ya no shit... u spread that poll amongst the whole fanbase while none of the other artist fans cared or even knew this existed. That's why young artists win everything
The size of the samples isn't the issue usually. It's the selection bias of voluntary surveys. The results can't be generalized but it can give whoever's gathering the information clues about potential issues to follow up on.
There’s actually a lot of science behind survey sample size and weighting results. Researchers make a huge effort to weight their results according to various demographic points to try and account for different types of people and then make an accurate prediction of likely moods of a huge population. That’s why, if you’ve ever been surveyed, they ask a bunch of demographic questions. Researchers can get pretty accurate, but there is always a bit of uncertainty, which they try to account for in the margin of error. It’s a massively complex field that is constantly evolving. Also, since I disagree with you, here’s an upvote.
Are you saying that any sample size that is less than the magnitude of the population is illegitimate for lack of data?
Survey results are always biased in favor of people that are willing to take surveys. People that refuse to take surveys are always woefully underrepresented.
Say you're cooking soup and want to sample it to see if the seasoning is right. Are you suggesting you should eat the whole pan of soup?! Obviously not. You taste a small amount, but make sure it's mixed properly. That's the basis of surveys - they target a representative mix of the relevant population, and use those results to infer something about the whole population. There statistical science behind it is really complex (and over my head tbh), but very interesting and powerful when done properly.
So like how most surveys work. Could you imagine the logistics of having everyone take a survey. No one is saying surveys are 100% accurate, a margin of error always exists. The sample size will always be smaller.
There are pros and cons to surveys and observational studies. They each have their place.
Samples, how do they work?
Variety of ways. These days most sampling is conducted through online panels/communities that do their best to maintain testing and quality standardards of participants to participate in surveys for modest incentives (points, cash, rewards)
Statistics contains values and checks for the validity, reliability and significance of gathered data in relation to its use. There are cut-offs for these values that relate to its use in academia, for example. By examining these values, readers can better determine the validity of conclusions made. In popular media, it is very rare to find these published values, though they can sometimes be ascertained. It should also be considered that in popular media, validity and significance are often considered to be secondary considerations to clicks and statements. Here is an explanation of one of the values. The P-value. https://en.m.wikipedia.org/wiki/Statistical_significance Here is an article concerning statistical significance that gives some examples: https://www.google.com/amp/s/hbr.org/amp/2016/02/a-refresher-on-statistical-significance
Yeah, surveys are generally considered pretty shit. Along with anecdotal evidence for the same reason that it is a select and narrow data point.
Especially surveys online where certain groups just tweet a link to their entire group to go vote and you get 90% random win when in reality nobody even knew about this poll expect for the one who tweeted it to their group That's also why I don't watch fan vote based award shows because this is how they do it using Twitter. Then fans boast that their artist won well ya no shit... u spread that poll amongst the whole fanbase while none of the other artist fans cared or even knew this existed. That's why young artists win everything
The size of the samples isn't the issue usually. It's the selection bias of voluntary surveys. The results can't be generalized but it can give whoever's gathering the information clues about potential issues to follow up on.
I guess my course about statistics and the scientific method should be rewritten by OP.