Design rigorous scientific experiments with power analysis and controls. Use when: user needs to plan an experiment, calculate sample sizes, or set up controls. NOT for: running experiments or analyzing collected data.
Design rigorous, reproducible experiments across scientific disciplines.
| Design | When to Use | Strengths | Weaknesses |
|---|---|---|---|
| RCT | Causal inference needed | Gold standard causality | Expensive, ethical limits |
| Factorial | Multiple factors | Tests interactions | Complex analysis |
| Crossover | Within-subject comparison | Reduced variability | Carryover effects |
| Quasi-experimental | Randomization impossible | Practical feasibility | Weaker causality |
| Observational (cohort) | Long-term outcomes | Natural setting | Confounding |
| Case-control | Rare outcomes | Efficient for rare events | Recall bias |
# Sample size calculation template (using scipy/statsmodels)
from statsmodels.stats.power import TTestIndPower
analysis = TTestIndPower()
n = analysis.solve_power(
effect_size=0.5, # Cohen's d (small=0.2, medium=0.5, large=0.8)
alpha=0.05, # Significance level
power=0.80, # Statistical power (commonly 0.80 or 0.90)
ratio=1.0, # Ratio of group sizes (n2/n1)
alternative='two-sided'
)
print(f"Required sample size per group: {int(n) + 1}")
Key parameters:
## Experimental Design: [Title]
**Research Question**: [Clear question]
**Design Type**: [RCT/Factorial/etc.]
### Participants/Samples
- Population: [target population]
- Inclusion: [criteria]
- Exclusion: [criteria]
- Sample Size: N=[total] ([n] per group) — Power=[X], alpha=[X], effect=[X]
### Groups
- Experimental: [treatment description]
- Control: [control description]
- Blinding: [single/double/triple/none]
### Variables
- IV: [variables]
- DV: [primary + secondary outcomes]
- Controls: [confounds and how addressed]
### Procedure
1. [Step-by-step protocol]
### Analysis Plan
- Primary: [statistical test]
- Secondary: [additional analyses]
- Multiple comparison correction: [method]
### Timeline
- [Phase 1]: [duration]
- [Phase 2]: [duration]
### Ethics
- IRB/IACUC requirements: [details]
- Consent procedure: [details]