Which programming language is widely used for statistics and data visualization?

R is widely used for statistics and data visualization due to its extensive collection of packages and libraries specifically designed for these purposes. It was developed primarily for statistical analysis, making it the preferred choice among statisticians and data analysts. The language provides a rich ecosystem with tools such as ggplot2 for advanced data visualization, dplyr for data manipulation, and caret for machine learning, among many others.

The language’s syntax and structure are well-suited for performing complex statistical analyses and visualizing the results effectively. Additionally, R has strong community support, which contributes to its continuous development and the availability of adaptive resources tailored for novice and expert users alike.

Other programming languages mentioned might be used for data analysis or visualization but do not match R's specialized capabilities in statistics. Python, for instance, is indeed popular for data science and includes libraries like Pandas and Matplotlib, but R remains the go-to for focused statistical tasks. Java and C++, while powerful for general programming and certain applications, are not primarily associated with statistical and visualization tasks, making R the standout choice for these specific needs.