As @John notes, the state of a coin may not at first seem similar to the question of whether a confidence interval covers the true mean. However, instead of a coin, we can understand this abstractly as a realized value drawn from a BernouliBernoulli distribution with parameter $p$. In the coin situation, $p=.5$, whereas for a 95% CI, $p=.95$. What's important to realize in making the connection is that the important part of the metaphor isn't the $p$ that governs the situation, but rather that the flipped coin or the calculated CI is a realized value, not a random variable.
As @John notes, the state of a coin may not at first seem similar to the question of whether a confidence interval covers the true mean. However, instead of a coin, we can understand this abstractly as a realized value drawn from a Bernouli distribution with parameter $p$. In the coin situation, $p=.5$, whereas for a 95% CI, $p=.95$. What's important to realize in making the connection is that the important part of the metaphor isn't the $p$ that governs the situation, but rather that the flipped coin or the calculated CI is a realized value, not a random variable.
As @John notes, the state of a coin may not at first seem similar to the question of whether a confidence interval covers the true mean. However, instead of a coin, we can understand this abstractly as a realized value drawn from a Bernoulli distribution with parameter $p$. In the coin situation, $p=.5$, whereas for a 95% CI, $p=.95$. What's important to realize in making the connection is that the important part of the metaphor isn't the $p$ that governs the situation, but rather that the flipped coin or the calculated CI is a realized value, not a random variable.
It is important for me to note at this point that all of this is the case within a Frequentist conception of probability. The Bayesian perspective does not violate the law of non-contradiction, it simply starts from different metaphysical assumptions about the nature of reality (more specifically about probability). Others on CV are much better versed in the Bayesian perspective than I am, and perhaps they may explain why the assumptions behind your question do not apply within the Bayesian approach, and that in fact, there ismay well be a 95% probability of the mean lying within a 95% credible interval, under certain conditions including (among others) that the prior used was accurate (see the comment by @DikranMarsupial below). However, I think all would agree, that once you state you are working within the Frequentist approach, it cannot be the case that the probability of the true mean lying within any particular 95% CI is .95.
It is important for me to note at this point that all of this is the case within a Frequentist conception of probability. The Bayesian perspective does not violate the law of non-contradiction, it simply starts from different metaphysical assumptions about the nature of reality (more specifically about probability). Others on CV are much better versed in the Bayesian perspective than I am, and perhaps they may explain why the assumptions behind your question do not apply within the Bayesian approach, and that in fact, there is a 95% probability of the mean lying within a 95% credible interval. However, I think all would agree, that once you state you are working within the Frequentist approach, it cannot be the case that the probability of the true mean lying within any particular 95% CI is .95.
It is important for me to note at this point that all of this is the case within a Frequentist conception of probability. The Bayesian perspective does not violate the law of non-contradiction, it simply starts from different metaphysical assumptions about the nature of reality (more specifically about probability). Others on CV are much better versed in the Bayesian perspective than I am, and perhaps they may explain why the assumptions behind your question do not apply within the Bayesian approach, and that in fact, there may well be a 95% probability of the mean lying within a 95% credible interval, under certain conditions including (among others) that the prior used was accurate (see the comment by @DikranMarsupial below). However, I think all would agree, that once you state you are working within the Frequentist approach, it cannot be the case that the probability of the true mean lying within any particular 95% CI is .95.
It is important for me to note at this point that all of this is the case within a Frequentist conception of probability. The Bayesian perspective does not violate the law of non-contradiction, it simply starts from different metaphysical assumptions about the nature of reality (more specifically about probability). Others on CV are much better versed in the Bayesian perspective than I am, and perhaps they may explain why the assumptions behind your question do not apply within the Bayesian approach, and that in fact, there is a 95% probability of the mean lying within a 95% credible interval. However, I think all would agree, that once you state you are working within the Frequentist approach, it cannot be the case that the probability of the true mean lying within aany particular 95% CI is .95.
It is important for me to note at this point that all of this is the case within a Frequentist conception of probability. The Bayesian perspective does not violate the law of non-contradiction, it simply starts from different metaphysical assumptions about the nature of reality (more specifically about probability). Others on CV are much better versed in the Bayesian perspective than I am, and perhaps they may explain why the assumptions behind your question do not apply within the Bayesian approach, and that in fact, there is a 95% probability of the mean lying within a 95% credible interval. However, I think all would agree, that once you state you are working within the Frequentist approach, it cannot be the case that the probability of the true mean lying within a 95% CI is .95.
It is important for me to note at this point that all of this is the case within a Frequentist conception of probability. The Bayesian perspective does not violate the law of non-contradiction, it simply starts from different metaphysical assumptions about the nature of reality (more specifically about probability). Others on CV are much better versed in the Bayesian perspective than I am, and perhaps they may explain why the assumptions behind your question do not apply within the Bayesian approach, and that in fact, there is a 95% probability of the mean lying within a 95% credible interval. However, I think all would agree, that once you state you are working within the Frequentist approach, it cannot be the case that the probability of the true mean lying within any particular 95% CI is .95.
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