Interval Estimate vs Point Estimate

A point estimate gives you one number, which is almost certainly a little off; an interval estimate admits that by attaching a reach on each side. The general form is $\text{point estimate} \pm \text{margin of error}$, and a confidence interval is the version that comes with a stated confidence level. For example, if 62% of a sample supports a measure and the margin of error is 4 percentage points, the interval estimate runs from 58% to 66%. Wider intervals are more likely to capture the parameter but tell you less about where it sits.

A point estimate is your one-number summary of a parameter before you attach any margin of uncertainty. Common ones are the sample mean $\bar{x}$ (read x-bar) for the population mean $\mu$ (the Greek letter mu), and the sample proportion $\hat{p}$ (read p-hat) for the population proportion $p$. For example, if 63 of 200 sampled voters approve, the point estimate of the population approval rate is $\hat{p} = 63/200 = 0.315$. A point estimate alone hides sampling variability, so it is usually paired with a margin of error to form a confidence interval.