Used to calculate Confidence intervals
Project description
proportion
Python package for proportion
Multiple procedures to obtain an interval estimate for an unknown proportion (p) based on binomial sampling. It is known that approximations are poor when the true p is close to zero or to one. So we provide alternative procedures with better properties. Non-iterative methods widely discussed in literature for computing a (central) two-sided interval estimate for p are implemented in terms of coverage probability and expected length.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file binomcikit-0.0.1.tar.gz.
File metadata
- Download URL: binomcikit-0.0.1.tar.gz
- Upload date:
- Size: 28.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
5a0b48899c92d15c5c3685b1ee9cb91bc4d5a231510ccc5c9fb1c9770d02596c
|
|
| MD5 |
52162abffb15f4c3c267ed4284d593fb
|
|
| BLAKE2b-256 |
583109bfaf5741ccf7e318ed57e2b92b896d112c79fb62e4491ca535b0181d4c
|
File details
Details for the file binomcikit-0.0.1-py3-none-any.whl.
File metadata
- Download URL: binomcikit-0.0.1-py3-none-any.whl
- Upload date:
- Size: 36.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9a26168735c4975e5d607762bd250569f581075649f03434b98af8cf9e9d34ae
|
|
| MD5 |
38586828f0c800d60377ee1f9f22b7db
|
|
| BLAKE2b-256 |
066d5a230fc802f4ab0197aec42b2e7d755e2d21bf1d8529c9235e9f583516cf
|