[Solved] What will be the output of this code?from scipy.stats import spearmanr x = [3, 1, 4, 2, 5] y = [10, 20, 30, 40, 50] result = spearmanr(x, y) print(round(result.correlation, 2)) | SciPy

SciPy - Statistical Tests

What will be the output of this code?

from scipy.stats import spearmanr
x = [3, 1, 4, 2, 5]
y = [10, 20, 30, 40, 50]
result = spearmanr(x, y)
print(round(result.correlation, 2))

A0.90

B0.70

C-0.90

D1.00

Step-by-Step Solution

Solution:

Step 1: Understand Spearman correlation
It measures the monotonic relationship between ranks of variables.
Step 2: Rank the variables
x ranks: [3,1,4,2,5] -> ranks [3,1,4,2,5]; y ranks: [10,20,30,40,50] -> ranks [1,2,3,4,5]
Step 3: Calculate correlation of ranks
Ranks of x and y are positively correlated but not perfectly, resulting in about 0.9.
Final Answer:
0.90 -> Option A
Quick Check:
Monotonic increasing but not perfect [OK]

Quick Trick: Spearman correlates ranks, not raw values [OK]

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