Identify the error in this code for calculating a 95% confidence interval:

medium📝 Debug Q6 of 15

SciPy - Curve Fitting and Regression

from scipy.stats import t
sample = [4, 5, 6, 7, 8]
mean = sum(sample)/len(sample)
std_err = (sum((x - mean)**2 for x in sample)/len(sample))**0.5 / len(sample)**0.5
df = len(sample) - 1
ci = t.interval(0.95, df, loc=mean, scale=std_err)
print(ci)

At.interval requires scale to be variance, not standard error

BStandard error calculation uses population variance denominator instead of sample

CDegrees of freedom should be len(sample), not len(sample) - 1

DMean calculation is incorrect

Step-by-Step Solution

Solution:

Step 1: Check standard error formula
Standard error should use sample variance denominator (n-1), not n.
Step 2: Identify denominator in variance calculation
Code uses len(sample) instead of len(sample)-1, causing bias.
Final Answer:
Standard error calculation uses population variance denominator instead of sample -> Option B
Quick Check:
Variance denominator error = Standard error calculation uses population variance denominator instead of sample [OK]

Quick Trick: Use n-1 for sample variance in std error [OK]

Common Mistakes:

Using population variance denominator
Confusing degrees of freedom
Misusing scale parameter

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More SciPy Quizzes

Identify the error in this code for calculating a 95% confidence interval:

Step 1: Check standard error formula

Step 2: Identify denominator in variance calculation

Final Answer:

Quick Check:

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