Visualize Variance is an intuitive 'shiny' applications tailored for agricultural research data analysis, including one-way and two-way analysis of variance, correlation, and other essential statistical tools. Users can easily upload their datasets, perform analyses, and download the results as a well-formatted document, streamlining the process of data analysis and reporting in agricultural research.The experimental design methods are based on classical work by Fisher (1925) and Scheffe (1959). The correlation visualization approaches follow methods developed by Wei & Simko (2021) and Friendly (2002) <doi:10.1198/000313002533>.
Version: 1.0.0 Imports: agricolae, bslib, corrplot, flextable, ggcorrplot, ggplot2, officer, patchwork, shiny, tibble, tidyr, rlang, dplyr, DT, readxl, htmltools, utils, stats, graphics, grDevices Suggests: testthat (≥ 3.0.0), writexl, shinytest2, extrafont Published: 2024-11-14 DOI: 10.32614/CRAN.package.visvaR Author: Ramesh Ramasamy [aut, cre, cph], Mathiyarasi Kulandaivadivel [ctb], Tamilselvan Arumugam [ctb] Maintainer: Ramesh Ramasamy <ramesh.rahu96 at gmail.com> BugReports: https://github.com/rameshram96/visvaR/issues License: AGPL (≥ 3) URL: https://github.com/rameshram96/visvaR, https://rameshram96.github.io/visvaR/ NeedsCompilation: no Materials: README NEWS CRAN checks: visvaR results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=visvaR to link to this page.
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