Results for “experimental-design”

Design, prioritize, and evaluate product experiments with clear hypotheses and defensible decisions, including A/B testing, sample size estimation, and statistical interpretation.

Design product experiments around hypotheses, audience, metrics, guardrails, and decisions.

基于已摄取文献和本地数据，生成经管实证研究设计：问题、机制、变量、模型、识别、机制、异质性、稳健性

Designs an A/B test or experiment with clear hypothesis, variants, success metrics, sample size, and duration. Use when planning experiments to validate product changes or test hypotheses.

Create museum-quality visual art through design philosophy. Generate original visual designs, posters, and artwork as PDFs or PNGs using sophisticated aesthetic movements and expert-level craftsmanship.

A B Testing Based Design Skill

Generates multiple radically different interface designs for a module, compares them, and synthesizes the best approach.

Creates editorial-minimalist web prototypes with warm monochrome canvas, serif display and grotesque body typography, hairline borders, and ambient micro-motion.

Building interactive experiences that engage, challenge, and delight playersUse when "game, gamedev, game development, phaser, unity, unreal, godot, gameplay, game loop, sprites, collision, physics, player, level, tilemap, games, gamedev, interactive, gameplay, physics, engines, performance, player-experience" mentioned.

Transforms A/B test and product experiment data into actionable readouts with hypothesis, metrics, interpretation, and decision.

Provides design engineering guidance focused on animation principles, UI review, and interface craftsmanship.

Build reproducible ML experiment plans with hypotheses, metrics, and ablations. Use when: (1) planning experiments, (2) comparing variants, (3) defining acceptance thresholds. NOT for: long-running experiment execution.

Mobile-first design and engineering doctrine for iOS and Android apps. Covers touch interaction, performance, platform conventions, offline behavior, and mobile-specific decision-making. Teaches pr...

Design shotgun: generate multiple AI design variants, open a comparison board, collect structured feedback, and iterate. (gstack)

Designs chaos experiments, creates failure injection frameworks, and facilitates game day exercises for distributed systems — producing runbooks, experiment manifests, rollback procedures, and post-mortem templates.

Shared vocabulary for designing deep modules — a small interface hiding a lot of behavior. Use when designing or improving a module's interface, deciding where a seam belongs, deciding whether to extract or merge modules, or making code more testable.

Design shotgun: generate multiple AI design variants, open a comparison board, collect structured feedback, and iterate. Standalone design exploration you can run anytime. Use when: "explore designs", "show me options", "design variants", "visual brainstorm", or "I don't like how this looks". Proactively suggest when the user describes a UI feature but hasn't seen what it could look like. (gstack)

Evaluate scientific claims and evidence quality by assessing experimental design, identifying biases and confounders, and applying evidence grading frameworks like GRADE and Cochrane Risk of Bias.