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WeibullR.learnr: An Interactive Introduction to Life Data Analysis

Welcome to WeibullR.learnr! This package contains a set of interactive learning modules for life data analysis, focusing on reliability, availability, and maintainability (RAM). It is designed for beginners, including university students and early-career professionals.

Motivation

Life data analysis is the study of how things function over time, from machines to people. Although many learning resources exist, most reference proprietary software, which may be expensive and inaccessible to students or those new to the field. WeibullR.learnr is an open-source alternative, introducing basic concepts and tools for life data analysis using R.

Installation Instructions

WeibullR.learnr is written in R and is built using WeibullR by David Silkworth and Jurgen Symynck (2022), a R package for Weibull Analysis, and learnr by Garrick Aden-Buie et al. (2023), a framework for building interactive learning modules in R.

To install WeibullR.learnr in R:

install.packages('WeibullR.learnr')

To install the development version:

devtools::install_github('paulgovan/weibullr.learnr')

Usage

Currently, three primary learning modules exist. These modules can be taken in either order and can be taken separately or together. The learning modules are designed to be plug-and-play, but changes can be made by forking the software repository and modifying the fork.

The modules can also be accessed in a browser at WeibullR.learnr and RAMR.learnr, TestR.learnr

Several helper functions for common RAM calculations are also included:

Code of Conduct

Please note that the WeibullR.learnr project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

More resources

WeibullR.plotly is a package for building interactive Weibull models.

WeibullR.shiny is a web application for life data analysis.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.