I think my favourite analogy for this is weather prediction We can predict which days will be rainy with some sort of percentage estimate, but ultimately the outcome is binary - either it does or doesn't rainhttps://twitter.com/kaz_yos/status/1059435637496074240 …
So we have a certain confidence in the statement that it will rain on a particular day, but ultimately that statement is either right or wrong
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Similarly, a confidence interval either does or doesn't contain the true effect size
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