While we might never be able to have 100% of our code strict, we can at
the very least do it for all of our tests. This ensures that our tests
are using our API with the types as intended by the test author, and not
silently be cast to what our API requires.
* First steps toward refactoring Statistical Distributions into smaller classes: BETA() and GAMMA() (and related functions) to start with... they all need a lot of tidying up, and more testing; but it's a start
* Add basic datatype validations to Beta and Gamma Excel function implementations
* Switch to using a trait with the validation methods to provide easier sharing between distribution classes
* Additional unit tests for Beta and Gamma functions, including unhappy path for validations
* Extract ChiSquared functions
* Additional argument validation checks with unit tests for Chi Squared functions
* Extract Fisher
* Move MEDIAN() and MODE() to the Averages class
* Extract filters for Median and Mode for common usage
* `GAUSS()` and `GAMMA()`, `NORM.S.DIST()`, `LOGNORM.DIST()` and `F.DIST()` function implementations, and further unit tests for a number of the statistical functions
Co-authored-by: Adrien Crivelli <adrien.crivelli@gmail.com>
Adrien Crivelli
Mark Baker