Shapiro-Francia normality test
Project description
# Shapiro-Francia normality test
## Description:
The statistical test of Shapiro-Francia considers the squared correlation between the ordered sample values and the (approximated) expected ordered quantiles from the standard normal distribution. The p-value is computed from the formula given by Royston (1993).
This function performs the Shapiro-Francia test for the composite hypothesis of normality, according to Thode Jr. (2002).
## Install
pip install sfrancia
## Usage
from sfrancia import shapiroFrancia import pandas as pd
df = pd.read_csv(‘fake_table.csv’)
# any array, series or list of numeric values shapiroFrancia(df[‘column’])
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## References:
Royston, P. (1993). A pocket-calculator algorithm for the Shapiro-Francia test for non-normality: an application to medicine. Statistics in Medicine, 12, 181-184.
Thode Jr., H. C. (2002). Testing for Normality. Marcel Dekker, New York.
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