I 'm a big fan of Python for data analysis, but even I get curious about what else is available. R has long been the go-to language for statistics, but the "Tidyverse" has given the language a serious ...

Overview: Data analysis software makes sense of large amounts of information quickly.Tools like R, Python, and SPSS simplify research and statistical studies.Vi ...

Designed to introduce students to quantitative methods in a way that can be applied to all kinds of data in all kinds of situations, Statistics and Data Visualization Using R: The Art and Practice of ...

We describe how to conduct a regression analysis for competing risks data. The use of an add-on package for the R statistical software is described, which allows for the estimation of the ...

In studies on HSCT Kaplan–Meier (KM) estimates of survival curves and Cox proportional hazard models are widely used to describe survival trends and identify significant prognostic factors. All these ...

But data science is a specific field, so while Python is emerging as the most popular language in the world, R still has its place and has advantages for those doing data analysis. Hoping to settle ...

The R system consists of a scripting language, an interactive command shell and a large library of mathematical functions that can be used for data analysis. Although R has been around for many years, ...

The table below shows my favorite go-to R packages for data import, wrangling, visualization and analysis — plus a few miscellaneous tasks tossed in. The package names in the table are clickable if ...

Before you start analyzing, you might want to take a look at your data object’s structure and a few row entries. If it’s a 2-dimensional table of data stored in an R data frame object with rows and ...