Statistics and confidence intervals.
I have two good statistics books that differ.
Book 1 says: When we talk about a 95% confidence interval for a mean we mean that the probability is 0.95 that the confidence interval will contain the true population mean.
Book 2 says: When the 95% confidence interval for the mean has been established we are NOT stating that the probability is 0.95 that the particular interval we have calculated contains the mean. We can only say that if repeated samples are drawn 95% of them will give interval estimates that include the mean.
3) My personal argument is that if 95% of the samples drawn give estimates that include the mean then we are 95% sure that our particular sample that we draw does give an interval that includes the true mean (I agree with book 1). MY QUESTION: Does an Expert have an opinion on whether we can say our particular interval estimate has a 95% chance of including the mean?
Outside United States
You're getting two different answers to this question. However, I believe you need to careful when talking about the probabilities of what you sampled and what you may sample in the future. The 95% confidence interval refers to what you sampled; it does not infer a 95% probability of an event in the future. They are not the same thing.
Obviously you will find experts who disagree with me so it's your choice.