What is Statistical Analysis
Statistical analysis is a major component in data analysis that applies statistical tools to the test data, analyzes it, and effectively draws useful inferences and future trends.
Statistical analysis is of two types— descriptive and inferential.
Descriptive statistics simply summarizes the data in a meaningful way, in the form of charts and tables. It is an easy way to understand, interpret, and visualize data.
Inferential statistics helps the user to go beyond this and help to test a hypothesis (null hypothesis) and draw conclusions and insights from the data.

Why is Statistical Analysis required
Statistical analysis is at the core of data analysis. All algorithms and models are built with the intention to execute statistical operations on the data and draw inferences and insights from it.

How is Statistical Analysis done in rubiscape
In rubiscape, there is an exhaustive set of algorithms for statistical analysis of numerical data. There are algorithms for the determination of correlation and hypothesis testing. Thus, statistical analysis in rubiscape becomes profound in terms of its descriptive and inferential nature. Users can not only visualize the data but also draw inferences from it, which can be used for decision-making and predicting future trends.
In rubiscape, the Statistical Analysis methods are,

• Parametric Distribution Fitting
• Process Capability Analysis
• Shapiro-Wilk Test
• Correlation
• ANOVA Analysis
• Hypothesis Test

In the task pane, click Model Studio, and then click Statistical Analysis.

For more information, refer to Statistical Analysis.