Use case 01
You ran more than two variants in one experiment.
Data ScientistExperimentationIntermediateSingle prompt
Multivariate Test Analysis AI Prompt
This prompt evaluates A/B/n tests where multiple variants compete simultaneously. It is useful when you need a disciplined workflow that first checks for any overall difference and then controls false positives during pairwise comparisons. It also highlights outright harmful variants.
Prompt text
Analyze the results of this multivariate (A/B/n) test with {{num_variants}} variants.
1. Check for sample ratio mismatch across all variants
2. Run omnibus test first: is there any significant difference across all variants? (chi-squared or ANOVA)
3. If significant, run pairwise comparisons between all variant pairs using:
- Bonferroni correction for multiple comparisons
- Report adjusted p-values and whether each pair is significant at α=0.05 after correction
4. Compute the effect size for each variant vs control: Cohen's d (continuous) or relative lift (proportions)
5. Plot: mean metric value per variant with 95% confidence intervals
6. Identify the winning variant — highest metric value with statistical significance vs control
7. Flag any variants that are significantly worse than control (degradation alert)When to use this prompt
Use case 02
You need omnibus and pairwise testing with correction.
Use case 03
You want effect sizes and confidence intervals by variant.
Use case 04
You need a clear winner and degradation alerts.
What the AI should return
A multivariate experiment report including SRM results, omnibus test outcome, corrected pairwise comparisons, effect sizes, confidence-interval plot, winning variant decision, and any degradation warnings.
How to use this prompt
1
Open your data context
Load your dataset, notebook, or working environment so the AI can operate on the actual project context.
2
Copy the prompt text
Use the copy button above and paste the prompt into the AI assistant or prompt input area.
3
Review the output critically
Check whether the result matches your data, assumptions, and desired format before moving on.
4
Chain into the next prompt
Once you have the first result, continue deeper with related prompts in Experimentation.
Frequently asked questions
What does the Multivariate Test Analysis prompt do?+
It gives you a structured experimentation starting point for data scientist work and helps you move faster without starting from a blank page.
Who is this prompt for?+
It is designed for data scientist workflows and marked as intermediate, so it works well as a guided starting point for that level of experience.
What type of prompt is this?+
Multivariate Test Analysis is a single prompt. You can copy it as-is, adapt it, or use it as one step inside a larger workflow.
Can I use this outside MLJAR Studio?+
Yes. The prompt text works in other AI tools too, but MLJAR Studio is the best fit when you want local execution, visible Python code, and reusable notebooks.
What should I open next?+
Natural next steps from here are A/B Test Analysis, Bayesian A/B Analysis, Causal Inference Analysis.