# Statistics > Confidence Intervals > 1-Population Proportion

This utility computes the confidence intervals for a population proportion in one population using normal approximation. The confidnece intervals are calculated using the following formula:

where
n = sample size
= sample proportion
= inverse cumulative probability of the z distribution at 1 - α/2.
If the conditions for normal approximation (, ) are not met, a warning will be shown along with the results of the computation.
To use the utility, select Statistics > Confidence Intervals > 1-Population Variance.

- You can provide sample data in a column of the Datasheet or provide summary data. If you provide sample data, put sample values of at most two categories in a column in the Datasheet. Select the Samples in column: radio button, and select the column name in the given drop-down menu.
- If individual sample data is not available, you can provide summary information of the sample data. In this case, select the Summarized sample data radio button. Enter the number of trials and the number of events in the provided text boxes.
- Enter the confidence level (between 0 and 1) in the Confidence level: text box.
- Click OK to compute the confidence interval. The results will be shown in the log window.

The number of trials, number of events, and proportion in the sample are displayed, along with the resulting the margin of error and the confidence interval for the population proportion. Here is an example:
Confidence Interval - One population proportion: confidence level = 0.95
Input: Summary data

Number of trials | Number of Events | Sample proportion | Margin of Error | 95.00%CI
100 | 10 | 0.100 | 0.059 | (0.0412, 0.1588)