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Medical biostatistics hypothesis testing toolkit: t-tests, ANOVA, chi-square, Fisher exact, Mann-Whitney, Kruskal-Wallis, sample size calculation, power analysis, multiple testing correction, survival analysis, and clinical trial biostatistics.
Passed 21 of 22 test cases with the skill, and 18 of 22 without it.
3 fixed18 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
I am writing a script to calculate the N per group for a clinical trial. I want to print the final rounded number in a formatted string that says 'N per group: [number]'. Provide the exact print statement.
| Checked | Without skill | With skill |
|---|---|---|
| Uses the :.0f format specifier | Missed | Passed |
The instructions your model reads when the skill loads.
Medical biostatistics for hypothesis testing, clinical trial design, and survival analysis. Covers t-tests, ANOVA, chi-square, Fisher exact, Mann-Whitney, Kruskal-Wallis, sample size calculation, power analysis, and multiple testing correction.
uv pip install scipy statsmodels
import numpy as np
from scipy import stats
# Two-sample t-test
t_stat, p = stats.ttest_ind(np.random.normal(100, 15, 30), np.random.normal(110, 15, 30))
# Mann-Whitney
u_stat, p = stats.mannwhitneyu(np.random.normal(100, 15, 30), np.random.normal(110, 15, 30))
# Chi-square
chi2, p, dof, _ = stats.chi2_contingency(np.array([[30, 10], [20, 40]]))
from statsmodels.stats.power import TTestIndPower
n = TTestIndPower().solve_power(effect_size=0.5, power=0.80, alpha=0.05)
print(f"N per group: {np.ceil(n):.0f}")
test cases passed, vs 18 / 22 without
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