In ProjectMOSAIC/mosaic: Project MOSAIC Statistics and Mathematics Teaching Utilities

require(mosaic)   # Load additional packages here 
require(ggformula)

# Some customization.  You can alter or delete as desired (if you know what you are doing).
trellis.par.set(theme = theme.mosaic()) # change default color scheme for lattice
theme_set(theme_bw())                   # change default theme for ggformula
knitr::opts_chunk$set(
  tidy = FALSE,     # display code as typed
  size = "small")   # slightly smaller font for code

Introduction

This document is intended to help users of the mosaic package migrate their lattice package graphics to ggformula. The mosaic package provides a simplified and systematic introduction to the core functionality related to descriptive statistics, visualization, modeling, and simulation-based inference required in first and second courses in statistics.

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\vspace*{.10in} Originally, the mosaic package used lattice graphics but now support is also available for the improved ggformula system. Going forward, ggformula will be the preferred graphics package for Project MOSAIC.

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Histograms

### Histograms (ggformula) wzxhzdk:1 ### Histogram options (ggformula) wzxhzdk:2

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### Histograms (lattice) wzxhzdk:3 ### Histogram options (lattice) wzxhzdk:4

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Density Plots

### Density plots (ggformula) wzxhzdk:5 ### Overlaid density plots (ggformula) wzxhzdk:6 ### Density over histograms (ggformula) We can use stacked layers to add a density curve based on a maximum likelihood fit or a kernel density estimate (see also `gf_dist()`) wzxhzdk:7

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### Density plots (lattice) wzxhzdk:8 ### Overlaid density plots (lattice) wzxhzdk:9 ### Density over histograms (lattice) `mosaic` makes it easy to add a fitted distribution to a histogram. wzxhzdk:10

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Side by side boxplots

### Side by side boxplots (ggformula) wzxhzdk:11 ### Faceted side by side boxplots (ggformula) wzxhzdk:12 ### Horizontal boxplots (ggformula) wzxhzdk:13

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### Side by side boxplots (lattice) wzxhzdk:14 ### Faceted side by side boxplots (lattice) wzxhzdk:15 ### Horizontal boxplots (lattice) wzxhzdk:16

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Scatterplots

### Basic scatterplot (ggformula) wzxhzdk:17 ### Overlaid scatterplot with linear fit (ggformula) wzxhzdk:18 ### Overlaid scatterplot with linear fit (lattice) wzxhzdk:19

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### Faceted scatterplot with smooth fit (ggformula) wzxhzdk:20

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## Faceted scatterplot with smooth fit (lattice) wzxhzdk:21 ## More options for scatterplot with linear fit (lattice) wzxhzdk:22

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Refining graphs

### Log scales (ggformula) wzxhzdk:23 ### Custom Colors (ggformula) wzxhzdk:24

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### Log scales (lattice) wzxhzdk:25 ### Custom Colors (lattice) wzxhzdk:26

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Want to explore more?

Within RStudio, after loading the mosaic package, try running the command mplot(ds) where ds is a dataframe. This will open up an interactive visualizer that will output the code to generate the figure (using lattice, ggplot2, or ggformula) when you click on Show Expression.

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References

More information about ggformula can be found at https://www.mosaic-web.org/ggformula.

More information regarding Project MOSAIC (Kaplan, Pruim, and Horton) can be found at http://www.mosaic-web.org. Further information regarding the mosaic package can be found at https://www.mosaic-web.org/mosaic and https://journal.r-project.org/archive/2017/RJ-2017-024.

Examples of how to bring multidimensional graphics into day one of an introductory statistics course can be found at https://escholarship.org/uc/item/84v3774z.

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ProjectMOSAIC/mosaic documentation built on Feb. 21, 2024, 2:11 a.m.