In general when creating what is called a confidence interval, we wish to obtain a range of plausible values for a quantity concerning the population, a parameter. Typically the population mean, μ, or proportion, π, is the parameter, but not always. Also, it is often desired determine a plausible range between two groups/samples to each other, such as comparing the average salary of men, say μ1, to the average salary of women, say μ2. A (1 -α) × 100% confidence interval is the probability of obtaining the parameter of interest under what is known as a Bayesian approach and is often the way a confidence interval is explained. Bayesian’s consider the parameter of interest a random variable. The author is a frequentist, and the author considers the parameter to be an unknown constant. Under the frequentist approach, a (1 - α) × 100% is the percent of confidence intervals that are expected to contain the true value of the parameter of interest. This is assuming an infinite number of samples taken of the same size, under a simple random sample. Of course, in reality only a single sample is taken in practice. The confidence interval is thus often considered the range of plausible values the parameter might be, what it is, is unknown in reality though and may or may not be within the interval.