Add test

Author: rhettinger

Lib/statistics.py

@@ -1041,7 +1041,7 @@ def correlation(x, y, /, *, by_rank=False):
         raise StatisticsError('correlation requires that both inputs have same number of data points')
     if n < 2:
         raise StatisticsError('correlation requires at least two data points')
-    if ranked:
+    if by_rank:
         x = _rank(x)
         y = _rank(y)
     xbar = fsum(x) / n

Lib/test/test_statistics.py

@@ -2565,6 +2565,19 @@ def test_different_scales(self):
         self.assertAlmostEqual(statistics.covariance(x, y), 0.1)
 
 
+    def test_correlation_spearman(self):
+        # https://statistics.laerd.com/statistical-guides/spearmans-rank-order-correlation-statistical-guide-2.php
+        # Compare with:
+        #     >>> import scipy.stats.mstats
+        #     >>> scipy.stats.mstats.spearmanr(reading, mathematics)
+        #     SpearmanrResult(correlation=0.6686960980480712, pvalue=0.03450954165178532)
+        # And Wolfram Alpha gives: 0.668696
+        #     https://www.wolframalpha.com/input?i=SpearmanRho%5B%7B56%2C+75%2C+45%2C+71%2C+61%2C+64%2C+58%2C+80%2C+76%2C+61%7D%2C+%7B66%2C+70%2C+40%2C+60%2C+65%2C+56%2C+59%2C+77%2C+67%2C+63%7D%5D
+        reading = [56, 75, 45, 71, 61, 64, 58, 80, 76, 61]
+        mathematics = [66, 70, 40, 60, 65, 56, 59, 77, 67, 63]
+        self.assertAlmostEqual(statistics.correlation(reading, mathematics, by_rank=True),
+                               0.6686960980480712)
+
 class TestLinearRegression(unittest.TestCase):
 
     def test_constant_input_error(self):