Statistical Power Analysis FAQs

Question 1

What does the Statistical Power Analysis skill do?

Accepted Answer

This skill calculates statistical power and determines optimal sample sizes for various research designs. It ensures your experiments are scientifically rigorous and meet specific funding or publication standards, such as NIH rigor and reproducibility requirements.

Question 2

When should I use this skill in my workflow?

Accepted Answer

Use it during the pre-study phase to justify sample sizes for grant proposals, design efficient experiments, or document plans for pre-registration. It is also valuable post-study for conducting sensitivity analyses to help interpret null results.

Question 3

What statistical tests are supported by this skill?

Accepted Answer

It supports a wide range of common designs, including independent and paired t-tests, one-way ANOVA, chi-square tests for categorical data, Pearson correlations, and multiple regression models, including effect size guidance for each.

Question 4

How does it help with NIH grant applications?

Accepted Answer

The skill generates NIH-compliant justification sections. It provides rationales for effect sizes based on literature or pilot data, accounts for expected participant attrition, and performs sensitivity analyses to demonstrate study adequacy across a range of effects.

Question 5

How does this skill improve my research efficiency?

Accepted Answer

It automates complex statistical formulas and provides immediate code snippets for R (pwr) and Python (statsmodels). This eliminates manual calculation errors and speeds up the transition from experimental design to implementation and documentation.

Statistical Power Analysis

Statistical Power Analysis

주요 기능

사용 사례

주요 기능

사용 사례