17.3.7.1 The One-Sample Proportion Test Dialog Box

Contents

Supporting Information

To open the One-Sample Proportion Test Dialog:

  1. With a worksheet active, click Statistics: Hypothesis Testing: One-Sample Proportion Test...

See Also:


Input

Input Data Form
  • Summarized
Perform the test using summary statistics that you enter into the dialog box manually.
  • Raw
Perform the test using a dataset composed of "success" or "failure" values. The dataset must contain no more than two distinct values.
Input Data

(Summarized)

  • Number of Events
The observed number of events.
  • Sample Size
The total number of observations.
Input Data

(Raw)

  • Sample
Define a sample data range.
  • Event
The dataset value that denotes event.

Proportion Test

Test Proportion The hypothetical proportion to be tested.
Null Hypothesis The null hypothesis to be tested (Sample Proportion = Test Proportion).
Alternative Hypothesis Options:
Proportion <> Test Proportion
A two-tailed proportion test that seeks to answer whether the sampled proportion = Test Proportion.
Proportion > Test Proportion
An upper-tailed proportion test that seeks to answer whether the sampled proportion is larger than the Test Proportion.
Proportion < Test Proportion
A lower-tailed proportion test that seeks to answer whether the sampled proportion is less than the hypothetical proportion .
Significance Level The significance level of the test.
Confidence Interval(s) Compute confidence interval for the true (population) proportion.
Confidence Level(s) in % Specifies the confidence levels for which the confidence intervals will be computed. This option is only available when Confidence Interval(s) is selected.
Test Methods Origin uses two methods for computing p values and confidence intervals for one-sample proportion tests (for documentation of Normal Approximation and Binomial test, see the algorithms page)
  • Normal Approximation
The Normal Approximation is always calculated. Generally gives a satisfactory result when successes is ≥ 10 and when sample size - successes is ≥ 10. The quality of the approximation tends to improve as sample size increases.
  • Binomial Test
Use Binomial Test.

Test Methods

Normal Approximation The Normal Approximation is always calculated. Generally gives a satisfactory result when successes is ≥ 10 and when sample size - successes is ≥ 10. The quality of the approximation tends to improve as sample size increases.
Binomial Test Use Binomial Test.

Power Analysis

Minimal Difference of Interest Specify the minimum difference from the Test Mean you are interested in. Once you enter a value in this box, the Power Anlysis graph will show the minimum sample size to detect this difference in the different powers.
Actual Power Compute the power of the test (the probability of rejecting the null hypothesis when it is false).
Significance Level Only available when Hypothetical Power and/or Actual Power are checked. This is the significance level (alpha value) for power computation.
Hypothetical Power Compute the power of the test at various sample sizes.
Hypothetical Sample Size(s) Only available when Hypothetical Power is checked. Specify hypothetical sample size(s) for power computation.

Output

For help with the range controls, see: Output Results

Results Log Output Select to output results to the Results Log.
Graphical Summary Report Specify whether to display the graphical summary report
Graphical Power Analysis Report Specify whether to display the graphical Power Analysis report. The power curve shows how the statistical power of the test changes as the difference in proportions varies. Power is the probability of rejecting the null hypothesis when the true difference differs from 0.
Output Results Specify the worksheet for output of test results
Output Plot Data Specify the worksheet for output the plot datasets.