Descriptive statistics are techniques used to summarize, organize and interpret a set of data. They describe the main characteristics of the data, also known as parameters, such as central tendency, dispersion, shape of distribution and relationships between variables. These statistics provide a quantitative overview of the data, making it easier to understand.
In an industrial context, descriptive statistics are widely used to analyze data from a variety of sectors. Here are a few examples of industrial applications:
In production, these statistics are used to analyze the dimensional variability of electronic components, helping to optimize processes and guarantee high quality standards.
In a customer satisfaction context, descriptive statistics are used to evaluate survey responses. The mean of responses provides an overall view of satisfaction levels, while the interquartile range indicates the dispersion of opinions, helping companies to target areas requiring improvement. Here's an example of how this can be represented Ellistat Data Analysis :
