Syntax Agility, R Language vs. esProc, which will win?

By definition the true agile syntax only requires users to memorize a small number of basic functions to implement a great many of advanced functions through simple processing on the basic functions. The said simple processing is a programming style of lightweight effort that is far easier and simpler to grasp than the common programming. As the advantage of agile syntax, the number of basic functions will be reduced to alleviate the learning effort and cost of users, providing users with the simple-and-easy syntax to implement the more advanced functions.

People need to use statistical tools for analytics computing and statistical computing. No matter business experts or the technicist, they both needs a application with agile Syntax. Both R language and esProc are good at agile syntax. Their differences can be illustrated with the examples below:

Take computing the quadratic sum of various vector members for example. Although both R and esProc provide some functions to compute the quadratic sum, we are not going to use the existing functions in this example. Instead, the most fundamental functions will be adopted to implement this function.

R solution:

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[Dhruv Bindhani]

The provided text introduces "agile syntax" as a key concept in programming, particularly relevant for statistical and analytics computing. It defines agile syntax as a language design philosophy aimed at reducing the user's memorization burden. Instead of a large set of specific functions, agile syntax enables the implementation of advanced functions through simple processing of a small number of basic functions. This "simple processing" is described as a lightweight and easily understandable programming style, simpler than common programming paradigms. The primary benefit of agile syntax is to alleviate the learning effort and cost for users, offering an intuitive way to achieve complex tasks.

The text posits that both R language and esProc exemplify agile syntax, making them suitable tools for both business experts and technicians in the fields of analytics and statistical computing. The article then states its intention to illustrate the differences between R and esProc's approaches to agile syntax by demonstrating how they would compute the "quadratic sum of various vector members" using only their most fundamental functions, rather than pre-existing, higher-level functions for this specific task. While the detailed code examples are not provided in this excerpt, the intention is to showcase how each language achieves conciseness and ease of use through its core building blocks.