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A few members have suggested the below question as a possible answer.
https://stats.stackexchange.com/questions/26450/why-does-a-95-confidence-interval-ci-not-imply-a-95-chance-of-containing-the

Neither the above question nor the responses address the question I have asked. I have given steps of deduction to start from the truth and arrive at a misconception. I would like to know why that deduction is incorrect.

A few members have suggested the below question as a possible answer. Why does a 95% Confidence Interval (CI) not imply a 95% chance of containing the mean?

Neither the above question nor the responses address the question I have asked. I have given steps of deduction to start from the truth and arrive at a misconception. I would like to know why that deduction is incorrect.

Suppose we create a 95% CI from a sample in order to estimate the population mean. Let's say the 95% CI turned out to be [34.2, 36.7]

So, why can't a particular 95% CI have a 95% probability to contain the population mean?

NOTE

A few members have suggested the below question as a possible answer.
https://stats.stackexchange.com/questions/26450/why-does-a-95-confidence-interval-ci-not-imply-a-95-chance-of-containing-the

Neither the above question nor the responses address the question I have asked. I have given steps of deduction to start from the truth and arrive at a misconception. I would like to know why that deduction is incorrect.

Suppose we create a 95% CI from a sample in order to estimate the population mean. Let's say the 95% CI turned out to be [34.2, 36.7]

So, why can't a particular 95% CI have a 95% probability of containing the population mean?

3b) "The interval [34.2, 36.7] has a 95% probability to capture the true population mean"

3.5) "The interval [34.2, 36.7] has a 95% probability to capture the true population mean"