What is Numerical Analysis
In modern data analytics, numerical analysis is the use of algorithms to solve continuous mathematical problems arising from real-world applications. These applications may be associated with fields like natural sciences, medicine, engineering, social sciences, business, and so on. The variables that are manipulated in numerical analysis vary continuously.

Why is Numerical Analysis required
In the 20th century, there has been an exponential rise in computational power and its potential to solve complex mathematical problems. As such, the use of mathematical algorithms for solving highly sophisticated and intricate mathematical models has also increased manifold. The variety and magnitude of data being generated in the world today are beyond human analytical capacity. Hence, numerical analysis is required to tackle this numerical data efficiently and with precision.

How is Numerical Analysis done in rubiscape
In rubiscape, there is a classified set of products to cater to the analysis of numerical data. The entire bouquet of algorithms for numerical analysis is placed under Model Studio.
In Model Studio, for numerical analysis, we have

• Data Preparation section, where there are several algorithms for cleaning and transforming raw data into analyzable data.
• Statistical Analysis section, where there are several algorithms to perform various statistical operations like correlation detection, hypothesis testing, and so on to draw inferences.
• Code Fusion section, where users can build their data analytical models in Python and R and integrate them in rubiscape.

Model Studio provides various algorithms to perform numerical analysis. These algorithms are categorized as,

• Data Preparation
• Statistical Analysis
• Code Fusion

In the task pane, click Model Studio.

For more information, refer to Model Studio.