The information told to my niece
Gabriele Stoppa: The information in my opinion.
Last updated
Gabriele Stoppa: The information in my opinion.
Last updated
Copiright © 2024 Gabriele Stoppa | blog.gabriele.pro | Tutti i diritti riservati.
My name is Gabriele Stoppa and I teach Quality Control at the Economics Faculty at the University of Trento. More than 600 students have attended my course over the last 10 years.
The purpose of my blog is to study the quality of the quantitative instruments used in scientific research in order to start off the process of data analysis renewal and to propose more effective innovative instruments.
This Blog can also be considered as an introduction to Data Analysis putting forward the idea that can be called the Paradox of Data Science.
A paradox is a phrase or a statement that seems acceptable but actually is not, so it surprises the reader. The term paradox derives from para=against and doxa=opinion. Therefore: contrary to popular opinion, contrary to the evidence, contrary to intuition. This paradox is linked to the concept of variability which is suggested as a complement to the concept of growth. The latter term is a special type of variability, where a quantum (of variability) is also filled by a sensum, the meaning of which relates to the context.
While traditional variability implies the shakiness of a series around a barycentre (without considering the objectives of the analyses or what occurs at other magnitudes involved, growth expresses how the series progresses along its path from a minimum to a maximum point and this makes it possible to involve the context, to assess the qualitative contribution of the series to the analyses in a way as to be able to assess the effects on other involved magnitudes. This is something that traditional variability is unable to do.
The Paradox of Data Science is as follows:
The path that you will follow in these pages will take you to The Data Science Paradox.
"The quantitive data series referred to the sizechosen carefully and correctly collected has the right credentials (what it takes) to rightfully be part of the analyses".
