PDR normality

scripts/normality.py

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+from scipy import stats
+import numpy as np
+import scipy.stats
+import pandas as pd
+import os
+import numpy as np
+import matplotlib.pyplot as plt
+
+curdir = os.getcwd()
+path_delim = '/'
+df = pd.read_excel(curdir + path_delim + "data/tests_28_10_2023_19_16.xlsx", sheet_name="data")
+
+# Generating a sample dataset
+np.random.seed(0)  # For reproducibility
+sample_data = np.random.normal(loc=0, scale=1, size=100)  # Generating 100 samples from a normal distribution
+
+# Performing the Shapiro-Wilk test
+statistic, p_value = stats.shapiro(df['calculatedRatio'])
+
+# Printing the results
+print(f"Shapiro-Wilk test statistic: {statistic}")
+print(f"P-value: {p_value}")
+
+alpha = 0.05  # Set the significance level
+if p_value > alpha:
+    print("Sample looks Gaussian (fail to reject H0 - null hypothesis)")
+else:
+    print("Sample does not look Gaussian (reject H0 - null hypothesis)")