Data Analysis
A.Y. 2021/2022
Learning objectives
The main objective of the course is to promote the knowledge, understanding and use of basic and advanced classical statistical methods, and to show how these can face research problems in various fields, and in particular how these techniques can improve problem solving techniques. The course is dedicated both to the analysis of individual features and to the identification and evaluation of any existing relationships between them, always addressing both the descriptive and the inferential scope. The importance of formulating interpretative hypotheses as an essential starting point for any qualitative and quantitative analysis of the data will be emphasized. The various theoretical topics will also be addressed operationally, using real dataset and using IT tools, both generic as Microsoft Excel and for specific statistical analysis as IBM SPSS Statistics.
Expected learning outcomes
The course aims to provide a good knowledge of classical data analysis techniques. At the end of the course the student will be able to carry out an analysis of real data, starting from the choice of the data source and of the most appropriate analysis techniques, up to a conscious interpretation of the results obtained.
Lesson period: First trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Lesson period
First trimester
For the training activity in the academic year 2021/22, more specific information will be provided in the coming months, based on the evolution of the public health situation.
Course syllabus
The main objective of the course is to promote the knowledge, understanding and use of basic and advanced classical statistical methods, and to show how these can face research problems in various fields, and in particular how these techniques can improve problem solving techniques. The course is dedicated both to the analysis of individual features and to the identification and evaluation of any existing relationships between them, always addressing both the descriptive and the inferential scope. The importance of formulating interpretative hypotheses as an essential starting point for any qualitative and quantitative analysis of the data will be emphasized. The various theoretical topics will also be addressed operationally, using real dataset and using IT tools, both generic as Microsoft Excel and for specific statistical analysis as IBM SPSS Statistics.
Prerequisites for admission
The knowledge of the statistics elements provided in an introductory course and the basics of using the PC are required.
Teaching methods
The course also includes some lectures in the laboratory that aim to introduce student with Excel and SPSS applications.
Teaching Resources
The following text is recommended:
Agresti A., Finlay B. - Metodi statistici di base e avanzati per le scienze sociali, Pearson, ISBN 9788865189498
(https://www.pearson.it/opera/pearson/0-7113-metodi_statistici_di_base_e_avanzati)
Recalls of univariate statistics: chapters 1-2-3-4-5-6.
Joint analysis of two characters: chapters 7-8-9.
Multivariate analysis: chapters 10-11-12-13-14.
The detailed program, with precise details of the paragraphs to be studied, will be made available during the course on the Ariel University platform (http://ariel.unimi.it/)
Another statistics manual can be used, chosen by the student, which covers the proposed program.
The reference material for the activities carried out in the laboratory will be made available during the course on the Ariel University platform (http://ariel.unimi.it/).
Agresti A., Finlay B. - Metodi statistici di base e avanzati per le scienze sociali, Pearson, ISBN 9788865189498
(https://www.pearson.it/opera/pearson/0-7113-metodi_statistici_di_base_e_avanzati)
Recalls of univariate statistics: chapters 1-2-3-4-5-6.
Joint analysis of two characters: chapters 7-8-9.
Multivariate analysis: chapters 10-11-12-13-14.
The detailed program, with precise details of the paragraphs to be studied, will be made available during the course on the Ariel University platform (http://ariel.unimi.it/)
Another statistics manual can be used, chosen by the student, which covers the proposed program.
The reference material for the activities carried out in the laboratory will be made available during the course on the Ariel University platform (http://ariel.unimi.it/).
Assessment methods and Criteria
The final exam consists in questions and numerical exercises, having as their object the analysis of data to be carried out also with Excel and SPSS applications, aimed at ascertaining the acquired skills and autonomy of judgment in the interpretation of the results, as well as the knowledge of the theoretical foundations supporting the analyzes carried out. A facsimile of the test will be made available on the Ariel platform.
SECS-S/01 - STATISTICS - University credits: 9
Lessons: 60 hours
Professor:
Siletti Elena