![]() ![]() These tools allow researchers to create informative and visually appealing graphics, helping to better communicate research findings. Data visualization: R provides a variety of tools for data visualization, including ggplot2, lattice, and plotly.Some popular libraries for statistical analysis in R include ggplot2, dplyr, tidyr, and tidymodels. Statistical analysis: R offers a vast range of statistical functions and libraries, allowing researchers to perform complex analyses and produce meaningful results.Data manipulation: R provides a wide range of functions and packages for data manipulation, making it easier to clean, transform, and organize large datasets for analysis.Here are some of the key ways that R can help on analytical Research: R programming is a powerful programming tools that can greatly aid analytical research in a variety of ways.
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