Python package that helps you analyze ordinal data.
Ordinal scale data is common. Companies and governments can quickly perform large-scale research with surveys. Usually, a survey output is placed on the Likert scale, where answers are ordered to describe a person's feelings about the survey's topic. A typical example of a survey is when a person is asked to agree with a statement with answers on a five-level scale:
Should the law protect your personal data?
1. Strongly disagree.
2. Rather disagree.
3. I don't know.
4. Rather agree.
5. Strongly agree.
The order between categories makes analysis complex, and the fact that answers are polarized between opposing states. Moreover, a border between categories is subjective and depends on the person's experiences, feelings, and knowledge about a surveying topic.
Classical measurements of central tendency do not fit well with ordinal data [ADD BIBLIOGRAPHY]. We encourage you to use the ordinal-scale-stats package to analyze survey responses.
With ordinal-scale-stats, you can:
- visualize differences between surveyed groups,
- measure polarization within a group,
- measure polarization between groups,
- measure ...