One of my graduate degrees is in information science. It's time to stop talking down to me like I have no idea what you're trying to say.

You are not "sampling" a population through VAERS data, because you cannot confirm literally anything about the VAERS population. Samples must be verifiable, and VAERS submissions are not verified.

Law of large numbers states that the larger the number, the more represented the outlier cases.

Which means that you are correct that IF the vaccine is capable of causing damage, then it will be represented in a large enough sample.

What you haven't established, and cannot establish, is what percentage of that sample population will represent outliers.

It may take a hundred million cases to even find a single vaccine injury. It'll be represented in a large population, but it'll still be a vanishingly small risk.

I can give you a bag of 1,000 coins, and you might feel pretty good about the representation of coins in there. Is there a good chance there's a gold dollar? Sure. A fifty-cent piece? Sure. They're rare, but they might be there.

But what about a buffalo penny? What about a misprinted quarter? Just because I have a large population of coins doesn't mean I have any reason to assume these very rare coins are present in the population. I can't make many assumptions about how many there are.

If I have 100,000 coins, or 100,000,000 coins, then I have a better chance of finding a very rare coin, but it'll still be a very small number of them compared to the total number of coins.

You're looking at VAERS data and assuming that if people are submitting, then at least SOME must have a legitimate vaccine injury.

This is incorrect.

There is no reason to believe this outside of the fact that you ALREADY believe that the vaccine causes injury. You are permitting that conclusion to taint how you are evaluating your data and guide your assumptions.

You assume the vaccine is hurting people and it's being covered up, therefore, 95% of the VAERS reports must be legitimate, despite what the actual verified data suggests.

But there is no reason to assume only 5% of the data is garbage. None. Nothing empirical you can provide. The law of large numbers only states that existing outliers will be represented in a large enough sample, not that you can make any assumptions about the proportion of the outliers to the total population based on that data alone.

One of my graduate degrees is in information science. It's time to stop talking down to me like I have no idea what you're trying to say.

You are not "sampling" a population through VAERS data, because you cannot confirm literally anything about the VAERS population. Samples must be verifiable, and VAERS submissions are not verified.

Law of large numbers states that the larger the number, the more represented the outlier cases.

Which means that you are correct that IF the vaccine is capable of causing damage, then it will be represented in a large enough sample.

What you haven't established, and cannot establish, is what percentage of that sample population will represent outliers.

It may take a hundred million cases to even find a single vaccine injury. It'll be represented in a large population, but it'll still be a vanishingly small risk.

I can give you a bag of 1,000 coins, and you might feel pretty good about the representation of coins in there. Is there a good chance there's a gold dollar? Sure. A fifty-cent piece? Sure. They're rare, but they might be there.

But what about a buffalo penny? What about a misprinted quarter? Just because I have a large population of coins doesn't mean I have any reason to assume these very rare coins are present in the population. I can't make many assumptions about how many there are.

You're looking at VAERS data and assuming that if people are submitting, then at least SOME must have a legitimate vaccine injury.

This is incorrect. There is no reason to believe this outside of the fact that you ALREADY believe that the vaccine causes injury. You are permitting that conclusion to taint how you are evaluating your data and guide your assumptions.

There is no reason to assume only 5% of the data is garbage. None. Nothing empirical you can provide. The law of large numbers only states that existing outliers will be represented in a large enough sample, not that you can make any assumptions about the proportion of the outliers to the total population based on that data alone.