Use scipy.stats t-distribution for confidence interval in day6_samples.py

[Copilot]

scipy.stats was imported but unused — the confidence interval relied on a hardcoded z-score (1.96) instead of leveraging the library.

Changes

• Replace hardcoded z-score with t-critical value via stats.t.ppf(0.975, df=len(data) - 1), making the import meaningful and statistically appropriate for small samples
• Correct variance formula from population variance (/ len(data)) to sample variance (/ (len(data) - 1))

# Before
z_score = 1.96
variance = sum((x - mean) ** 2 for x in data) / len(data)

# After
t_crit = stats.t.ppf(0.975, df=len(data) - 1)
variance = sum((x - mean) ** 2 for x in data) / (len(data) - 1)

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[EimanTahir071]

implement suggestions

[Copilot]

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