A 99% confidence interval estimate is a range of values that is likely to include the true population mean with a confidence level of 99%. This means that if the same sample were to be taken multiple times, 99% of the confidence intervals calculated would contain the true population mean.
To calculate a 99% confidence interval estimate, you need a sample mean, sample standard deviation, sample size, and a critical value from a t-distribution table. The formula for calculating the confidence interval is: sample mean ± (critical value * (sample standard deviation/sqrt(sample size))).
The 99% confidence level represents the level of certainty or accuracy in which we can say that the true population mean falls within the calculated confidence interval. In other words, we can be 99% confident that the true population mean is within the calculated range.
A 99% confidence interval estimate should be used when we want to have a high level of confidence in our estimate of the population mean. This level of confidence is typically used in scientific research and studies.
The difference between a 95% and 99% confidence interval estimate is the level of confidence. A 95% confidence interval estimate means we can be 95% confident that the true population mean falls within the calculated range, while a 99% confidence interval estimate means we can be 99% confident. The higher the confidence level, the wider the range of values in the confidence interval.