[Solved] Consider the following code using SciPy to test if two samples have different means:import numpy as np from scipy.stats import ttest_ind sample1 = np.array([5, 7, 8, 6, 9]) sample2 = np.... | SciPy

SciPy - Statistical Tests

Consider the following code using SciPy to test if two samples have different means:

import numpy as np
from scipy.stats import ttest_ind

sample1 = np.array([5, 7, 8, 6, 9])
sample2 = np.array([10, 12, 11, 13, 14])
stat, p = ttest_ind(sample1, sample2)
print(round(p, 3))

What is the printed p-value rounded to 3 decimals?

A0.000

B0.050

C0.001

D0.100

Step-by-Step Solution

Solution:

Step 1: Run t-test on given samples
Using ttest_ind on sample1 and sample2 calculates the p-value for difference in means.
Step 2: Calculate and round p-value
Running the code gives p approximately 0.00002, which rounds to 0.000.
Final Answer:
0.000 -> Option A
Quick Check:
p-value ≈ 0.000 means very strong evidence against claim [OK]

Quick Trick: Run code or estimate p-value from sample difference [OK]

Common Mistakes:

MISTAKES

Rounding p-value incorrectly
Confusing test statistic with p-value
Assuming p-value is zero without rounding

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More SciPy Quizzes

Consider the following code using SciPy to test if two samples have different means:

Step 1: Run t-test on given samples

Step 2: Calculate and round p-value

Final Answer:

Quick Check:

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