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The confidence interval for a population parameter is calculated based on a specific percent level of confidence.

This percentage—which can be 90%, 95%, or 99%—is arbitrarily decided for a given population parameter or sampling distribution.

The level at which the confidence interval is calculated is called the confidence coefficient, degree of confidence, or confidence level.

It is calculated simply by 1-ɑ, where ɑ; is the area under the curve distributed equally on both tails of the curve. This area also indicates the level of statistical significance.

In other words, the confidence level is the probability 1−α that the calculated confidence intervals would contain the population parameter. Here, it is assumed that the parameter values are obtained through unbiased sampling conducted a sufficient number of times.

If the confidence level is decided to be at 0.95—where α is 0.05—we are confident that 95% of all the calculated confidence intervals would contain the true population parameter value.

An appropriate confidence coefficient is crucial, without which, the confidence limits cannot be calculated or interpreted.