direkt zum Inhalt springen

direkt zum Hauptnavigationsmenü

Sie sind hier

TU Berlin

Page Content



Software for simplified statistical analysis

Julian Ariza Alvarez
(PhD; Industrial Engineering);
Johannes Schober
(Dr.-Ing.; Industrial Engineering);
Stephan Siek
(Dipl.Inf; Computer Science)

Manufacturing, Quality Management

Prof. Dr.-Ing. Roland Jochem

Faculty V - Mechanical Engineering and Transport Systems,
Institute of Machine Tools and Factory Management,
Chair of Quality Science

EXIST-Gründerstipendium, Dez. 2018 – Nov. 2019

Data driven process optimization


Our idea

Statistance assists manufacturing companies in selecting and performing appropriate statistical analyses for data-driven process optimization, allowing an easy interpretation of the results.

Employees are currently overpromoted with the data analysis common in quality management. This is currently done using statistics software (e.g. Mintitab, SPSS, JMP, etc.). Existing statistics software requires time-consuming and cost-intensive training from its users, both in statistics and in the operation of the software. All this is omitted with Statistance. Statistical statements are consistently translated into an understandable language through dialogue-based method selection and application.


Zusatzinformationen / Extras

Quick Access:

Schnellnavigation zur Seite über Nummerneingabe

Auxiliary Functions

This site uses Matomo for anonymized webanalysis. Visit Data Privacy for more information and opt-out options.