# One-Sample Proportions

The One-Sample Proportions procedure provides tests and confidence intervals for individual binomial proportions. The data are assumed to be from a simple random sample, and each hypothesis test or confidence interval is a separate test or individual interval, based on a binomial proportion. Output includes the observed proportion, the estimate of the difference between the population proportion and the hypothesized population proportion, asymptotic standard errors under null and alternative hypotheses, specified test statistics with two-sided probabilities, and specified confidence intervals for proportions.

- Example
- Statistics
- Agresti-Coull, Anscombe, Clopper-Pearson (Exact), Jeffreys, Logit, Wald, Wald (continuity corrected), Wilson Score, Wilson Score (continuity corrected), Exact Binomial, Mid-p Adjusted Binomial, Score, Score (continuity corrected).

## Data considerations

- Data
- The procedure displays requested test statistics and two-sided probabilities, confidence intervals for differences of proportions, as well as proportions, standard errors, and counts for each group or variable. The procedure is limited to maximum of one test value.
- Assumptions

## Obtaining One-Sample Proportions tests

This feature requires the Statistics Base option.

- From the menus choose:
- Select one or more quantitative test variables.
- Optionally, you can:
- Select success criteria settings under the Define
Success section:
- Last Value
- The last or highest value among the sorted distinct values in the data is used. This applies to numeric or string variables. This is the default setting.
- First Value
- The first or lowest value among the sorted distinct values in the data is used. This applies to numeric or string variables.
- Value(s)
- One or more parenthesized specific values. Multiple values must be separated by spaces. This applies to numeric or string variables. String variable values should be enclosed in single quotes.
- Midpoint
- Values at or above the middle of the range of observed values in the data. This applies only to numeric data.
- Cut Point
- Values at or above a specified value. This applies only to numeric data.

- Click Confidence Intervals... to specify which types of confidence intervals are displayed, or to suppress all confidence intervals.
- Click Tests... to specify which types of test statistics are displayed, or to suppress all tests.
- Click Missing Values... to control the treatment of missing data.
- Click Bootstrap... for deriving robust estimates of standard errors and confidence intervals for estimates such as the mean, median, proportion, odds ratio, correlation coefficient or regression coefficient.

- Select success criteria settings under the Define
Success section:
- Click OK.

This procedure pastes PROPORTIONS command syntax.