Answer 1

R

R is used in the development of the SACS software , as well as the C++ bindings to SAS, SAS Professional, and SASX. R provides numerous useful facilities in statistical inference, including support for various types of statistics, including Bayesian and non-Bayesian methods, matrix and array types, decision trees and regression trees, statistics for multiple regression, and special functions for statistical computing. R is also used as a development environment and training environment for statistical software products including SAS and SASR. The following are the key characteristics of R: R is a programming language that has been extensively used in the data science community (Bruce et al., 2020).

R packages can be created and used directly from the RStudio IDE. Data are represented graphically by plotting, plotting, ggplot2, bar charts, plots, scatter plots and the like. It is easy to write efficient, general.and extensible R code. R code is a powerful tool for data analysis but there are some significant downsides to using R as a data analysis tool. The most obvious one is that R code is difficult to write. While it is possible to write a program that will parse raw CSV files, very few people are actually comfortable with such programming languages. Other aspects of R programming include the limitations of being able to manipulate data in the way a machine program could. These limitations are well known and are sometimes hard to accept (Mainlund, 2019).

Python

The language is designed to be both fast and flexible, both for its programmers and its users. Most of the language was designed for text-based applications, although a small number of language features were designed specifically for graphics. Like any language, programming in Python has its own set of tools and facilities available to allow for various tasks. The following sections describe the tools available and provide a brief example of what can do with Python in a typical day-to-day project. Python is easy to learn, and powerful. To understand the importance of programming in a business environment, consider a scenario that is common in today’s companies: In the last quarter of a decade, the company is planning to build an online store. This online store provides products and software in a convenient and interactive format—a website for people to sell things to each other. Unfortunately, the problem is that the online shop’s business requires extensive documentation to allow (Bruce et al., 2020).

References

Bruce, P., Bruce, A., & Gedeck, P. (2020). Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python. O’Reilly Media.

Mainlund, T. (2019). Domain-specific languages in R: Advanced statistical programming. Place of publication not determined: APRESS.

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Answer 2

SQL

SQL uses tables to organize data in a way that supports queries and provides a method for resolving database conflicts.The syntax of SQL is simple. The SQL code is enclosed in square brackets([,]).to communicate with server-side applications on the client side. It is used in the Web browser and in most operating systems. Microsoft has a free version of SQL that can run on most Windows systems or on any Unix-like system, but the free version will not run on Linux, macOS, or other systems. Although most Linux distributions have the SQL software installed.It defines the syntax for describing data objects and for defining their relationship with each other. It uses a relatively simple concept of variables with a set of keywords (Ozgur et al., 2017).

SAS

In particular, it is used for defining the mathematical concepts in the SAS data management system. SAS is a general purpose statistical package with a wide range of statistical support and application to a wide range of statistical problem areas. SAS includes several packages. The data management functions in the SAS data management system include: creating, transforming and searching data; creating summary statistics; creating descriptive statistics and summary statistics (statistical summary tables); creating exploratory data analysis; performing descriptive statistics; creating multivariate and multivariate descriptive statistics; performing descriptive analysis; and summarizing the data. The SAS data management system will also support the creation of tabular data visualizations, visual reports, and report formatting tools. SAS provides tools to manipulate data and generate reports, although its emphasis on the statistical analysis is usually best illustrated through the toolbars. To make a simple and intuitive graphical presentation of the data (Lu, 2018).

It is based on Microsoft SQL and uses the Microsoft R programming language. SAS is also known for being one of the most popular statistical software packages that are offered by the SAS Research Foundation (RSF). The R programming language was developed by IBM to provide an application for analyzing complex data sets and using a standardized interface. This data manipulation tool is extremely powerful and has become the de facto statistical language of the SAS Research Foundation. SAS Statistics Model A SAS model (Lu, 2018).

REFERENCES
Lu, P.-P. (2018). Optimization Design of ASME Large Diameter and High Pressure Class Non-standard Flange. Petrochemical Equipment. 47. 47-50. 10.3969/j.issn.1000-7466.2018.06.009.

Ozgur, C., Colliau, T., Rogers, G., & Hughes, Z. (2017). MatLab vs. Python vs. R. Journal of Data Science, 15(3), 355-371.