Skip to content
store
statistical-power

Self-hosted alternatives to statistical-power

5 self-hosted AI Skills apps to use instead, best rated first.

Top picks

  1. C

    claude-to-deerflow

    Launch

    claude-to-deerflow is an agent skill that lets an assistant send messages and questions to a running DeerFlow instance through its HTTP API. DeerFlow is an AI agent platform built on LangGraph that orchestrates sub-agents for research, code

    Self-hosted

  2. O

    open-notebook

    Launch

    open-notebook is an agent skill for organising research with Open Notebook, a self-hosted alternative to NotebookLM. It arranges sources, notes and AI conversations into research notebooks. Sources can be PDFs, web pages, audio, video and O

    Self-hosted

  3. R

    Reactive Resume

    Launch

    Reactive Resume is a free and open-source resume builder for writing resumes and cover letters, checking the work, and tracking job applications. You create a free account, import an existing resume or start from scratch, and see the finish

    Open sourceSelf-hosted

  4. S

    self-hosted-funnel-launch

    Launch

    Self-hosted funnel launch is an agent skill that takes a funnel from an empty install to published on infrastructure you control, using the Autonnel funnel builder, which is licensed Apache-2.0. The result covers a landing page, checkout, a

    Self-hosted

  5. G

    get-convex/convex-backend

    Launch

    Convex is an open-source reactive database for web app developers. It combines a database, a place to write server functions in pure TypeScript, and client libraries that keep the app's data live, so screens update as the data changes. Beca

    Self-hosted

About statistical-power

S

statistical-power

Calculates sample sizes and statistical power for study planning

statistical-power is an agent skill for planning studies by calculating sample sizes and statistical power. It answers how many independent experimental units are needed to detect an effect of scientific importance, or what effects a feasible sample could detect. The skill says to choose the inferential goal first, because precision, equivalence, non-inferiority and sequential monitoring each need their own calculations that the bundled superiority-test helpers do not cover. For any given test, four quantities are linked: sample size, effect size, significance level and power. Fixing three of them lets you solve for the fourth, when a solution exists, for a fixed design, analysis and nuisance parameters. The skill covers analytical calculations, which are exact under standard assumptions and approximate otherwise, and simulation or Monte Carlo methods, which need a credible data-generating process and a calibrated planned analysis. It also helps you choose and convert effect sizes, which is often the hardest part. Use it when someone asks how many subjects, samples or replicates are needed, or wants an a priori power analysis.

View statistical-powerAll AI Skills apps
Price
Free
Made by
k-dense-ai
Category
AI Skills
Website
github.com/k-dense-ai/scientific-agent-skills/statistical-power