This is a solid implementation for anyone doing quantitative research or academic work. It handles the statistical fundamentals you actually need: sample size calculations for power analysis, multiple randomization schemes for experimental design, and the standard hypothesis tests with effect sizes built in. The code includes things like block and stratified randomization, multiple testing corrections, and proper effect size calculations like Cohen's d and Hedges' g. It's Python heavy with scipy and statsmodels, so you'll want those dependencies ready. Best for researchers who need to design experiments, analyze results, or understand statistical approaches rather than just run black box tests. The structure is clear enough that you can adapt the methods to your specific research context.

skills.sh installs
253
GitHub stars
44
last updated
Aug 21, 2026

Install

$ npx -y skills add personamanagmentlayer/pcl --skill research-expert --agent claude-code

Installs into .claude/skills of the current project.

Files

Research Methodology Expert

Expert guidance for research methodology, experimental design, statistical analysis, and academic writing.

Core Concepts

Research Design

  • Experimental vs observational studies
  • Randomized controlled trials (RCTs)
  • Cross-sectional, longitudinal, cohort studies
  • Case-control studies
  • Systematic reviews and meta-analysis
  • Sample size determination

Statistical Analysis

  • Descriptive statistics
  • Hypothesis testing
  • Confidence intervals
  • Regression analysis
  • ANOVA and t-tests
  • Non-parametric tests
  • Multiple testing correction

Academic Writing

  • Literature review
  • Research proposals
  • Manuscript structure (IMR AD)
  • Citation management
  • Peer review process
  • Publishing ethics

Experimental Design

from dataclasses import dataclass
from typing import List, Optional
import numpy as np
from scipy import stats

@dataclass
class Study:
    name: str
    design_type: str  # 'RCT', 'observational', 'cohort'
    sample_size: int
    groups: List[str]
    primary_outcome: str
    secondary_outcomes: List[str]

class SampleSizeCalculator:
    """Calculate required sample size for studies"""

Sponsors

Details

Repository
github.com/personamanagmentlayer/pcl
Categories
Documentation, Data Science & ML
First seen
Jun 3, 2026

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