[Solved] What is the output of the following code?import numpy as np from scipy.stats import t data = np.array([5, 7, 8, 6, 9]) mean = np.mean(data) se = np.std(data, ddof=1) / np.sqrt(len(data)) interval = t.... | SciPy

SciPy - Curve Fitting and Regression

What is the output of the following code?

import numpy as np
from scipy.stats import t

data = np.array([5, 7, 8, 6, 9])
mean = np.mean(data)
se = np.std(data, ddof=1) / np.sqrt(len(data))
interval = t.interval(0.95, len(data)-1, loc=mean, scale=se)
print(tuple(round(x, 2) for x in interval))

A(5.00, 9.00)

B(4.50, 9.30)

C(6.00, 7.00)

D(5.04, 8.96)

Step-by-Step Solution

Solution:

Step 1: Calculate mean and standard error
Mean = (5+7+8+6+9)/5 = 7.0; sample std dev ≈ 1.58; SE = 1.58 / sqrt(5) ≈ 0.71.
Step 2: Calculate 95% confidence interval using t-distribution
Degrees of freedom = 4; t critical ≈ 2.776; interval = mean ± t * SE = 7.0 ± 2.776*0.71 ≈ (5.04, 8.96).
Final Answer:
(5.04, 8.96) -> Option D
Quick Check:
Mean ± t*SE = (5.04, 8.96) [OK]

Quick Trick: Calculate mean, SE, then apply t.interval [OK]

Common Mistakes:

Using population std dev instead of sample
Wrong degrees of freedom
Rounding errors

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More SciPy Quizzes

What is the output of the following code?

Step 1: Calculate mean and standard error

Step 2: Calculate 95% confidence interval using t-distribution

Final Answer:

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