Metadata-Version: 2.1
Name: nightingale
Version: 1.2
Summary: Python library for simplifying statistical analysis and making it more consistent
Home-page: https://github.com/idin/nightingale
Author: Idin
Author-email: py@idin.ca
License: MIT
Platform: UNKNOWN
Requires-Python: ~=3.6
Description-Content-Type: text/markdown
Requires-Dist: statsmodels
Requires-Dist: scipy
Requires-Dist: pandas

# *Nightingale*

I named this package *Nightingale* in honour of 
[Florence Nightingale](https://en.wikipedia.org/wiki/Florence_Nightingale), 
[The lady with the data](https://thisisstatistics.org/florence-nightingale-the-lady-with-the-data/).

# Installation

You can use pip to install Nightingale:

```bash
pip install nightingale
```

# Usage

## Population Proportion

```python
from nightingale import get_sample_size, PopulationProportion, get_z_score

print('z-score for 0.95 confidence:', get_z_score(confidence=0.95))
print('sample size:', get_sample_size(confidence=0.95, error_margin=0.05, population_size=1000))
print('with 10% group proportion:', get_sample_size(confidence=0.95, error_margin=0.05, population_size=1000, group_proportion=0.1))

population_proportion = PopulationProportion(sample_n=239, group_proportion=0.5)
print('error:', population_proportion.get_error(confidence=0.95))
```

## Ordinary Least Squares (OLS)


## *ANOVA*


# References
z-score: https://stackoverflow.com/questions/20864847/probability-to-z-score-and-vice-versa-in-python



