Guesstimation

1 Entry level: Fermi calculations

Fermi calculations are rough estimates, named after the physicist Enrico Fermi. The Wikipedia page is a portal of sorts to the whole field.

Many people have written fun guides to Fermi calculations. (Harte 1988; Mahajan 2010; Swartz 2003).

Relatively few address the problem of uncertainty in the inputs, but Hubbard (2014) does, and I recommend it highly.

2 Guesstimate

Guesstimate is a probabilistic spreadsheet, which does Monte Carlo error estimation. (source, Blog post).

For a good worked example, see Elizabeth’s blog.

3 Squiggle

3.1 What Squiggle Is

• A simple programming language for doing math with probability distributions.
• An embeddable language that can be used in Javascript applications.
• A tool to encode functions as forecasts that can be embedded in other applications.

3.2 What Squiggle Is Not

• A complete replacement for enterprise Risk Analysis tools.[…]
• A probabilistic programming language. Squiggle does not support Bayesian inference.
• A tool for substantial data analysis. (See programming languages like Python or Julia)
• A programming language for anything other than estimation.
• A visually-driven tool. (See Guesstimate and Causal)

The listed strengths are:

• Simple and readable syntax, especially for dealing with probabilistic math.…
• Optimized for using some numeric and symbolic approaches, not just Monte Carlo.
• Embeddable in Javascript.

The last one sounds useful.

It looks like this:

//Here, you’re expressing a 90% confidence that the value is between 8.1 and 8.4 Million.
populationOfNewYork2022 = 8.1M to 8.4M

proportionOfPopulationWithPianos = {
  // This is a block.
  percentage = 0.2 to 1 // Block body can declare local variables.
  percentToRatio = 0.01
  percentage * percentToRatio // Final expression of a block is the block’s value.
}

pianoTunersPerPiano = {
  pianosPerPianoTuner = 2k to 50k
  1 / pianosPerPianoTuner
}

totalTunersIn2022 = populationOfNewYork2022 * proportionOfPopulationWithPianos *
pianoTunersPerPiano

4 References