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Purpose and design

The mosaic package is designed to facilitate the use of R instatistics and calculus instruction by providing a number of functionsthat (a) make many common tasks fit into a common template, and (b)simplify some tasks that would otherwise be too complicated forbeginners.

Installation

You install from CRAN using

install.packages("mosaic")

or from github with

devtools::install_github("ProjectMOSAIC/mosaic",build_vignettes =TRUE)

If you want to try out our developmental code (the beta branch),use

devtools::install_github("ProjectMOSAIC/mosaic",ref="beta")

Some features of the mosaic package have been split off intoauxiliary packages. These include:

• mosaicModel – implements high-level systems for working withstatistical models: effect-size calculation, bootstrapped confidenceintervals, prediction error, graphics for models with multiple inputs.The package contains an introductory vignette.
• mosaicCalc – provides the calculus components of mosaic, includingintegration, differentiation, and differential equation solving.

Install these packages usinginstall.packages(c("mosaicCalc", "mosaicModel")) or fromGitHub as described above.

Updates to the master github repository are more frequent than CRANupdates. Our beta branch is where we implement bug fixes most quicklyand develop new features. We try to keep it pretty stable, but there maybe a few rough edges, missing documentation, etc. while things are inprogress.

If you discover a problem with any version of the package, be sure tolet us know so that we can address it. Post an issue on github or sendemail toRpkgs@mosaic-web.org.

Getting Started with mosaic

The package includes several vignettes to help you get started. Oneof these vignettes (ResourcesRelated to the mosaic package) includes a list of manyresources, both within the package and external to it. That’s a goodplace to start.

Getting Help

Need help? Try posting a question on Stack Overflow using the tagr-mosaic.

Project MOSAIC

Project MOSAIC is a community of educators working to develop a newway to introduce mathematics, statistics, computation and modeling tostudents in colleges and universities.

Our goal: Provide a broader approach to quantitative studies thatprovides better support for work in science and technology. The focus ofthe project is to tie together better diverse aspects of quantitativework that students in science, technology, and engineering will need intheir professional lives, but which are today usually taught inisolation, if at all.

• Modeling. The ability to create, manipulate and investigate usefuland informative mathematical representations of a real-worldsituations.
• Statistics. The analysis of variability that draws on our ability toquantify uncertainty and to draw logical inferences from observationsand experiment.
• Computation. The capacity to think algorithmically, to manage dataon large scales, to visualize and interact with models, and to automatetasks for efficiency, accuracy, and reproducibility.
• Calculus. The traditional mathematical entry point for college anduniversity students and a subject that still has the potential toprovide important insights to today’s students.

The name MOSAIC reflects the first letters — M, S, C, C — of theseimportant components of a quantitative education. Project MOSAIC ismotivated by a vision of quantitative education as a mosaic where thebasic materials come together to form a complete and compellingpicture.

Find out more about Project MOSAIC at[http://www.mosaic-web.org].