The purpose of taking a random sample from a lot or population and computing a statistic, such as the mean from the data, is to approximate the mean of the population. ... A confidence interval addresses this issue because it provides a range of values which is likely to contain the population parameter of interest.

Why do we use 95 confidence interval instead of 99?

For example, a 99% confidence interval will be wider than a 95% confidence interval because to be more confident that the true population value falls within the interval we will need to allow more potential values within the interval. The confidence level most commonly adopted is 95%.

What is an approximate 95% confidence interval?

For a 95% confidence interval, we use z=1.96, while for a 90% confidence interval, for example, we use z=1.64. ... Figure 32: The relationship between the confidence level and the value of z in the formula for an approximate confidence interval.