If you’re calculating the Confidence Interval manually, use the CI = Sample Mean (x) +/- Confidence Level Value (Z) * (Sample Standard Deviation (S) / Sample Size (n)) formula. To find the Sample Mean, add all the sample values together and divide them by the number of samples.

The Z value can be found using the Mean (x) +/- Z value * (Standard Deviation (S) / √Number of Observations (n)) formula or simply by checking it in the Z value table.

To find the Standard Deviation, insert values in the √ (Summ of ((Each value from the population – Population mean) * (Each value from the population – Population mean)) / The size of population). The ‘’n’’ value is simply the number of your samples. Google Sheets calculates the Confidence Interval easier and faster.

Type in your samples and their values to a spreadsheet and use the =TINV(1-.95, n(Sample Size)-1)*STDEV/SQRT(n) formula.

Confidence Intervals are used to determine how far the Sample Mean is from an actual Population Mean. In other words, it displays the error interval between these two means, or the upper and lower error limit around the sample mean.

For example, if you calculate a 90% Confidence Interval, you can be 90% sure that the Population Mean lies in your Sample Mean interval. Most often, 95% and 99% Confidence Intervals are used, as they allow to calculate the lowest error percentage. However, sometimes 80%, 85%, and 90% Confidence Intervals are applied.

The Sample Size of a Confidence Interval is the total number of your samples. For example, if you have a table consisting of 25 samples and their values, the Sample Size is 25. In Google Sheets, you can calculate the Sample Size by entering the =SUM(value set) formula and highlighting all of your samples.