doex - Design and Analysis of Experiments

Python library for conducting design of experiments.

Installation

pip install doex

Online Demo

Try out doex in an online Jupyter Notebook -

Sample usage

import doex

exp = doex.OneWayANOVA(
    [24, 28, 37, 30], # Treatment 1
    [37, 44, 31, 35], # Treatment 2
    [42, 47, 52, 38], # Treatment 3
)

+---------------------+-----+----------------+---------------------+-------------+---------+
| Source of Variation | DOF | Sum of Squares | Mean Sum of Squares | F statistic | p value |
+---------------------+-----+----------------+---------------------+-------------+---------+
|      Treatments     |  2  |    450.6667    |       225.3333      |    7.0356   |  0.0145 |
|        Error        |  9  |    288.2500    |       32.0278       |             |         |
|        Total        |  11 |    738.9167    |                     |             |         |
+---------------------+-----+----------------+---------------------+-------------+---------+

Implementations

• Completely Randomized Design / One-Way ANOVA

• Randomized Complete Block Design / Two-Way ANOVA

• Latin Square Design

• Graeco-Latin Square Design

• Randomized Complete Block Design with missing values

• Balanced Incomplete Block Design (TODO)

• Factorial Designs (TODO)

Documentation

• Examples
  • Completely Randomized Design
    • Example 1 - CRD
    • Example 2 - OneWayANOVA
  • Randomized Complete Block Design
    • Example 1 - RCBD
    • Example 2 - RCBD
    • Example 3 - TwoWayANOVA
  • Randomized Complete Block Design With Missing Values
    • Example 1 - RCBD One Value Missing
    • Example 2 - RCBD One Value Missing
    • Example 3 - RCBD Two Values Missing
  • Latin Square Design
    • Example 1 - LSD
    • Example 2 - LSD With Missing Value
  • Graeco-Latin Square Design
• Reference
• Contributing
  • Our Community Values
  • Setting up Your Development Environment
    • Cloning the doex Repository
    • Install an Editable Version
    • Running Tests Locally
    • Building Documentation
  • Raise a pull request
    • Run Tests Locally
    • Push Changes to Forked Repo
    • Create Pull Request
• Changelog
  • 0.0.7
  • 0.0.6
  • 0.0.5
  • 0.0.4
  • 0.0.3
  • 0.0.2
  • 0.0.1
• GitHub Repository

Acknowledgements

• Adapted from https://github.com/pawanaichra/doe.