An unbiased point estimate is not always sufficient to accurately predict a given population parameter—for instance—population proportion or mean. So, to get a better judgment of a population parameter, a range of values can be drawn from the sample data distribution to estimate the true value of the population parameter. This range is called Interval Estimate, more commonly known as the Confidence Interval. Unlike the point estimate, the confidence interval generates a range of values within two limits—one lower and one upper—generally referred to as the confidence limits. The confidence interval for the population proportion can be represented by writing the calculated lower limit—followed by population proportion—followed by the calculated upper limit. In this equation, is sample proportion, is population proportion, and E is the margin of error. In simpler terms, it may also be expressed as ± E. The confidence interval indicates the uncertainty in the parameter estimate predicting the true value of the population parameter. In other words, the narrower the confidence interval, the more accurate the estimate is.