# Statistics > Hypothesis Tests > 2-Population Proportions

This utility performs calculations for testing claims about the difference of two population proportions. A normal distribution is used for approximation. The null hypothesis of a claim about the difference of two population proportions p1 and p2 is p1 = p2. The alternative hypothesis can be one of the following: p1 < p2, p1 > p2, or p1 ≠ p2.

The user has the option of using a pooled estimate of the sample proportions p1 = x1 / n1 and p2 = x2 / n2. The pooled esimate is given by:

The test statistics z, calculated using the pooled estimate is:

where is the sample proportion, p is the hypothesized population proportion, and n is the sample size.

The test statistics calculated without using the pooled estimate is given by:

### Dialog Inputs

The sample data of the population must be of only two categories. They can be provided in one of three ways:

- Samples in one column: The population labels of samples are in one column of the Datasheet, and the individual samples are in another column.
- Samples in two columns: The samples of the two population are in two separate columns.
- Summarized sample data: The number of events and the number of trials of each of the two populations are provided (instead of individual sample values).

The Significance Level or Confidence Level must be between 0 and 1. For example, enter 0.95 for a 95% confidence level.

The Alternative Hypothesis can be one of the following forms: Less than (p1 < p2), Not Equal to (p1 ≠ p2), or Greater than (p1 > p2). Enter the Hypothesized Proportion Difference (p1 - p2) in the provided text box.

Select the Use pooled estimate check box if the pooled estimate is appropriate for combining the samples.