How many standard deviations are typically involved in a 95% confidence level?

In statistical analysis, a 95% confidence level corresponds to a range that is expected to contain the true parameter (like a population mean) 95% of the time if we were to repeat the analysis multiple times. This range is typically represented in terms of standard deviations from the mean in a normal distribution.

For a normally distributed dataset, approximately 95% of the data falls within two standard deviations from the mean. This means that if you calculate the mean and then calculate the range by extending two standard deviations above and below that mean, you will capture about 95% of the possible values in your dataset. This concept is foundational in statistics, particularly in hypothesis testing and confidence interval estimation.

Thus, when referring to a 95% confidence level, it is understood that this corresponds to intervals covering two standard deviations from the mean, which effectively describes this central region in a standard normal distribution.