2.2. Statistical treatments and operations

There are many different kinds of operations that can be applied on an existing set of data (disregarding their origin, i.e. whether they come from experiments, simulations…). They are all listed below and the main ones are described in more details in the following subsections. For the sake of simplicity, the input variable is called \(x\) leading to an output variable called \(y\). The dataset contains \(N\) points and \(i\) is be an iterator that goes from 0 to \(N-1\). In few words, here what’s easily calculable with Uranie:

• The normalisation of variable, in Normalising the variable

• The ranking of variable, in Computing the ranking

• The elementary statistic computation, in Computing the elementary statistic

• The quantile estimation, in The quantile computation

• The correlation matrix determination, in Correlation matrix

• 2.2.1. Normalising the variable
• 2.2.2. Computing the ranking
• 2.2.3. Computing the elementary statistic
• 2.2.4. The quantile computation
  • 2.2.4.1. Empirical computation
  • 2.2.4.2. Wilks-quantile computation
• 2.2.5. Correlation matrix