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CODE 90289
ACADEMIC YEAR 2020/2021
CREDITS
SCIENTIFIC DISCIPLINARY SECTOR CHIM/01
LANGUAGE Italian
TEACHING LOCATION
  • GENOVA
SEMESTER 2° Semester
MODULES Questo insegnamento è un modulo di:
TEACHING MATERIALS AULAWEB

OVERVIEW

In the laboratories advanced instrumental techniques  (such as NIR spectroscopy and UV_Vis ..) are currently employed not only with analytical purposes but also for on-line monitoring of production processes. These modern instruments are capable of performing analysis in a short time, but they provide a huge amount of data that can be processed only with the use of appropriate chemometric techniques. This course aims to provide the basis to extract useful information from multivariate data.

AIMS AND CONTENT

AIMS AND LEARNING OUTCOMES

The aim of the course is to provide the students with simple and powerful tools for basic multivariate data analysis. Among the possible applications of multivariate statistical analysis to chemical data, it will be shown how multivariate quality control can detect "bad" samples (i.e., not complying with the product specifications).

TEACHING METHODS

All lessons are composed of a first theoretical part where the theory of chemometrics (without going into much detail of mathematical algorithms) is explained and a part of computer exercises. In this second part, a specific problem and the related data set are described to the students, that must try to extract the desired information using a statistical software.

SYLLABUS/CONTENT

Exploratory data analysis (Principal Component Analysis) to visualize the data structure; classification methods to identify a sample as belonging to one or more groups of previously-classified samples; regression methods to determine the amount of a component, property, or other value based on the measured X-block variables. PCA diagnostics.

TEACHERS AND EXAM BOARD

Exam Board

ELEONORA RUSSO (President)

BRUNO TASSO (President)

LESSONS

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The exam takes place at the computer. Students are provided with a data set and they have to extract the information useful for the problem by using different techniques of multivariate analysis (PCA, LDA, SIMCA ...) implemented on a statistical software used during the lessons.