[Solved] What will be the p-value output of this code?from scipy.stats import ks_2samp import numpy as np np.random.seed(0) sample1 = np.random.normal(0, 1, 100) sample2 = np.random.... | SciPy

SciPy - Statistical Tests

What will be the p-value output of this code?

from scipy.stats import ks_2samp
import numpy as np
np.random.seed(0)
sample1 = np.random.normal(0, 1, 100)
sample2 = np.random.normal(0, 1, 100)
result = ks_2samp(sample1, sample2)
print(round(result.pvalue, 3))

A0.001

B0.500

C0.900

D0.050

Step-by-Step Solution

Solution:

Step 1: Understand test on similar normal samples
Both samples come from the same normal distribution, so p-value should be high, indicating no significant difference.
Step 2: Check typical p-value range
Running the code yields a p-value around 0.9, showing strong evidence samples are from same distribution.
Final Answer:
0.900 -> Option C
Quick Check:
High p-value means no difference [OK]

Quick Trick: Similar samples yield high p-value near 1 [OK]

Common Mistakes:

MISTAKES

Expecting low p-value for similar samples
Confusing statistic with p-value
Not setting random seed causing different results

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What will be the p-value output of this code?

Step 1: Understand test on similar normal samples

Step 2: Check typical p-value range

Final Answer:

Quick Check:

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