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CHEMIOMETRICS

CODE 42396
ACADEMIC YEAR 2022/2023
CREDITS
  • 5 cfu during the 4th year of 8451 CHIMICA E TECNOLOGIA FARMACEUTICHE (LM-13) - GENOVA
  • 3 cfu during the 3nd year of 8451 CHIMICA E TECNOLOGIA FARMACEUTICHE (LM-13) - GENOVA
  • 4 cfu during the 4th year of 8452 FARMACIA (LM-13) - GENOVA
  • 6 cfu during the 5th year of 8452 FARMACIA (LM-13) - GENOVA
  • SCIENTIFIC DISCIPLINARY SECTOR CHIM/01
    LANGUAGE Italian
    TEACHING LOCATION
  • GENOVA
  • SEMESTER 2° Semester
    MODULES This unit is a module of:

    OVERVIEW

    The course covers the basic techniques of multivariate analysis applied to the extraction of information from complex chemical data, including: exploratory analysis (PCA: Principal Component Analysis) to visualize the structure of multivariate data; classification and modelling methods to identify a sample as belonging to a previously defined sample group; regression methods to determine the amount of a component, a property or other value from the X block of the measured variables.

    AIMS AND CONTENT

    LEARNING OUTCOMES

    Provide students with the necessary tools to process complex chemical data and to extract useful information from them.

     

    AIMS AND LEARNING OUTCOMES

    Students will acquire the knowledge necessary to process complex chemical data. In particular, they will be able to develop predictive classification or regression models using the multivariate analysis software (CAT).

    TEACHING METHODS

    The lessons will be partly theoretical and partly practical. During the theoretical lessons the main methods of multivariate analysis (PCA, LDA, PLS, etc.) will be presented. The practical lessons will take place on the computer and students will learn how to use chemometric software (CAT) to process chemical data.

    SYLLABUS/CONTENT

    Exploratory Analysis (PCA) to visualize the structure of multivariate data; classification and modelling methods to identify a sample as belonging to a previously defined sample group (LDA: Linear Discriminant Analysis); regression methods to determine the amount of a component, property, or other value from the X block of measured variables (PLS: Partial Least Square regression). Software for multivariate analysis: CAT.

    TEACHERS AND EXAM BOARD

    Exam Board

    BRUNO TASSO (President)

    ELEONORA RUSSO

    LESSONS

    LESSONS START

    Second semester.

    Class schedule

    All class schedules are posted on the EasyAcademy portal.

    EXAMS

    EXAM DESCRIPTION

    Students will be provided with a set of chemical data that they will have to process using the appropriate multivariate analysis tools. They will then prepare a power point presentation with the main results obtained to be presented to the Commission.