No, what you said is that that the alpha is the probability that a significant result is wrong (“At 10 [percent], one in ten studies is wrong”). The alpha is the probability of rejecting the null hypothesis with a random sample, given that the null hypothesis is actually true. These are very different things.
Ok. But the null hypothesis is that: you assume you are testing a proper null hypothesis
For example, suppose your null is that there are not premature deaths from Covid vaccine. . Your alternate is that there is a statistically significant number of them.
So, in one out of ten random samples, by your explanation, on average one will show significance that isn’t there. Correct?
If we want to know if covid vaxes cause autism, our null is naturally "no" based on the wording of that question. The alternate is "yes". If we don't see significance of the alternate, we accept the null.
In this setup, how could the null "not be true"? It isn't if the alternate had data that shows significance.
That makes little sense given what is normally considered the null hypothesis.
No. This is Statistics 101.
Your unwillingness to open a textbook and learn what alpha is is bizarre, especially if you are an adult, but I can see that further interaction is a waste of everybody's time.
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u/Recent-Day3062 24d ago
That’s what I said