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Create Fermi Estimates and Perform Monte Carlo Estimates

Home Page: http://getguesstimate.com/

License: MIT License

JavaScript 64.37% CSS 35.54% TypeScript 0.08%

guesstimate-app's Introduction

#Explanation Guesstimate is a tool for performing estimates using monte carlo experiments. It can be used similarly to excel, but provides the option of providing ranges and distributions as values instead of individual points. Other metrics can do mathematical operations on these cells/metrics. After each new input is added or changed, a set of 5000 samples is randomly generated from each input and goes through the specified operations to produce confidence intervals in the output.

#Using Guesstimate See GetGuesstimate.com to use.

##Create a Collection create_collection

##Create a Metric with a Guess create_guess You can enter individual numbers or ranges. There are a few ways of entering ranges.

  • 30/5: This means '30' with a standard deviation of 5 on each side.
  • 30+-5: Same as above.
  • 25->35: A 2-standard-distribution confidence interval between 25 and 35.

Currently all ranges are converted into normal distributions.

##Create a Metric with a Function input create_function Use the = sign as the first character of a guesstimate input to make it a function (similar to Excel and Google Sheets). Each metric has a variable name which is made of two randomly chosen letters. When the function input is selected, you can either type a metric's symbol to use it in a calculation, or simply click on it.

The functions are processed using Math.js. As such, it has several mathematical constants and functions that are useable.

##Different Visualization Methods visualizations

###Metric Visualizations There are a few different ways of visualizing metrics. These are the following:

  • Normal: A view with metric names, basic distribution stats (mean & std deviation), and a picture of the distribution in the background.
  • Basic: The same as normal, but without the distribution image. This helps speed up calculations.
  • Scientific: The same as normal, but the distribution image is larger and there are a few extra statistics. Mean and standard deviation are labeled with more detail.
  • Debugging: This is used for making the system, and is a view of the React props that each metric component contains. This may be interesting to you, but is not that useful for general use.

###Arrows Arrows between metrics can be turned on or off. They can be useful, but also add complication to the UI. In the future the arrow layout may improve significantly.

##Distribution View distributions Click on Metrics to see more information about their distributions. The Distribution shows a large view of the Distribution, information about different percentiles, and a portion of the samples that make up the distribution.

##Limitations There are many things that will be improved. Some of the more important limitations include:

  1. Normal distributions are the default for guesses, and flat distributions are possible using math.js =random(3,9). Lognormal, power, and other kinds of distribution should be standard/possible.
  2. Everything is public.
  3. Only the creator of a collection is allowed to save edits to that collection.
  4. The distribution view displays all negative samples as '0' for some reason.
  5. Metrics can't be shared between collections.
  6. Distributions are all +- 1 standard deviation. Having everything be a 90% confidence interval would probably be better.

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