One proportion z-test

When to consider it

• Compare a proportion against a reference using the large-sample z approximation.

Assumptions and scope

• Observations must be independent between subjects; repeated rows from one subject are not independent samples.
• Normal approximation requires adequate expected success/failure counts. Use the exact binomial or Fisher branch when appropriate.

Required inputs

• Successes — Enter the method parameter described above.
• Trials — Enter the method parameter described above.
• Null proportion — Enter the method parameter described above.

Review missing values and data coding before running. Sample inputs are synthetic teaching examples.

Implementation

Lifescio validates inputs and formats results; listed functions are the principal calculation routines, not an exhaustive transitive dependency list.

• statsmodels 0.14.4: statsmodels.stats.proportion.proportions_ztest

These are pinned library versions; saved results record the versions actually used at runtime.

Library references

• SciPy statistical methods
• statsmodels models and statistical tests
• scikit-learn clustering
• lifelines survival comparisons