⚡ Adds absence Kendall-tau

analyze_absence.py

@@ -0,0 +1,25 @@
+import numpy as np
+from scipy.stats import kendalltau
+
+dataset = np.load("clean.npy")
+print(f"dataset shape: {dataset.shape}, analyzing column 11 (absence)")
+print("\tinteger value")
+print("")
+
+
+def analyze_absence(name: str, col: np.ndarray):
+    absence_col = dataset[:, 11]
+    tau, p = kendalltau(absence_col, col)
+    print(f"ken-tau for {name}: {tau}")
+    print(f"p-value for {name}: {p}")
+
+    if p > 0.05:
+        print("statistically insignificant\n")
+    else:
+        print("statistically significant\n")
+
+
+analyze_absence("gpa", dataset[:, 2])
+analyze_absence("math", dataset[:, 3])
+analyze_absence("slovak", dataset[:, 4])
+analyze_absence("english", dataset[:, 5])