Create probability models with interactive formulas and simulation
Enter Formula
Quick examples:
Variables & Breakdown
Variable Distributions
No formula parsed yet
0 parameters0 total
Monte Carlo Simulation
Simulation Results
Example: For "revenue", you might break it down as "customers * price_per_customer"
Hover over options for usage guidance
Import Template Example
Copy this JSON template to create your own setups:
Calculated Parameters
50% of values will be below this (realistic starting point)
90% of values will be below this (moderate skew ratio ~2.5x)
⚠️ Use log-normal for: Multiplicative processes, city populations, company valuations, file
sizes ❌ Don't use for: Stock prices, predictable revenues, anything that can be negative
Average expected value
Std dev / mean (0.2 = controlled, 0.5 = variable, 1.0 = highly variable)
⚠️ Use gamma for: Processing times with known patterns, positive continuous values with
flexibility ❌ Avoid for: Simple waiting times (use exponential), symmetric data (use normal)
Most likely proportion/percentage
How much data supports your estimate?
⚠️ Use beta for: Actual survey results, conversion rates with real data, completion
percentages ❌ Don't use for: Pure guesses without data, anything outside 0-1 range
Expected average (mean)
What type of process are you modeling?
⚠️ Use exponential for: Truly memoryless processes, radioactive decay, random system
failures ❌ Don't use for: Transaction sizes, queue times, wear-out failures, bathtub curve processes