Statistics
A.Y. 2024/2025
Learning objectives
The course aims to provide students with the basic principles of descriptive statistics to enable them to independently carry out simple data analysis and to interpret tables, graphs and the summary indicators commonly reported in journals, periodicals and books.
The course will cover various types of data analysis by constructing frequency tables and their graphical representations. Teaching will also look at the main summary indicators (mean, mode and median) while also emphasising the importance of introducing other indicators in order for students to be able to interpret them.
The course will also deal with the detection and synthesis of two real phenomena (by means of contingency tables). Besides analysing each phenomenon separately, students will explore the dependence between both phenomena, since in many practical contexts (including the economic and legal context) it is important to be able to determine whether and to what extent a given phenomenon is dependent on another (e.g. for forecasting purposes).
Teaching will combine practical exercises with theory to enable students to acquire the necessary data analysis skills.
The course will cover various types of data analysis by constructing frequency tables and their graphical representations. Teaching will also look at the main summary indicators (mean, mode and median) while also emphasising the importance of introducing other indicators in order for students to be able to interpret them.
The course will also deal with the detection and synthesis of two real phenomena (by means of contingency tables). Besides analysing each phenomenon separately, students will explore the dependence between both phenomena, since in many practical contexts (including the economic and legal context) it is important to be able to determine whether and to what extent a given phenomenon is dependent on another (e.g. for forecasting purposes).
Teaching will combine practical exercises with theory to enable students to acquire the necessary data analysis skills.
Expected learning outcomes
Upon completion of the course, students will understand the basic principles of descriptive statistics. More specifically, they will be able to summarise the information contained in a given data set through the use of frequency tables, graphs, and the appropriate indicators, and should be able to adequately interpret the summaries produced. Students will also be able to determine whether two real phenomena are dependent on one another and to provide future forecasts of a phenomenon of interest. This latter capability is fundamental at a practical level.
Similarly, students will understand the most common indicators reported in the media and will be able to accurately interpret information presented in tables and charts. These skills will enable students to give a more critical reading of commonly used statistical indicators and will allow them to make decisions with a greater sense of awareness.
By gaining an in-depth understanding of the concepts outlined during teaching and by performing exercises in data analysis, students will have the opportunity to acquire skills valuable for their further education and professional development.
Similarly, students will understand the most common indicators reported in the media and will be able to accurately interpret information presented in tables and charts. These skills will enable students to give a more critical reading of commonly used statistical indicators and will allow them to make decisions with a greater sense of awareness.
By gaining an in-depth understanding of the concepts outlined during teaching and by performing exercises in data analysis, students will have the opportunity to acquire skills valuable for their further education and professional development.
Lesson period: Third trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
A-K
Responsible
Lesson period
Third trimester
Course syllabus
Statistics: definition and fields of application.
The classification of statistical phenomena and the concept of statistical reference population.
The description of the statistical data.
Summary of data in tables and their graphic representation.
Position indices: mode, median, quantiles, arithmetic mean.
Dispersion indices: range of variation, variance and standard deviation, coefficient of variation.
Mutability indices.
The index numbers.
Analysis of the association between categorical variables (contingency tables, chi-square index).
Dependence on average.
Deterministic regression model.
Concentration indices.
The classification of statistical phenomena and the concept of statistical reference population.
The description of the statistical data.
Summary of data in tables and their graphic representation.
Position indices: mode, median, quantiles, arithmetic mean.
Dispersion indices: range of variation, variance and standard deviation, coefficient of variation.
Mutability indices.
The index numbers.
Analysis of the association between categorical variables (contingency tables, chi-square index).
Dependence on average.
Deterministic regression model.
Concentration indices.
Prerequisites for admission
No prior knowledge is required
Teaching methods
Theoretical lectures and exercises.
During lectures the professor uses both the blackboard and some slides to be projected from a PC. The lectures focus on the more theoretical issues but are always accompanied by numerical examples.
During the exercises the professor, after having possibly recalled the theoretical references presented in the lectures, solves numerical exercises, which require the use of a scientific calculator.
During lectures the professor uses both the blackboard and some slides to be projected from a PC. The lectures focus on the more theoretical issues but are always accompanied by numerical examples.
During the exercises the professor, after having possibly recalled the theoretical references presented in the lectures, solves numerical exercises, which require the use of a scientific calculator.
Teaching Resources
Statistica di Base III ed., Fulvia Mecatti
McGraw Hill
McGraw Hill
Assessment methods and Criteria
Written test.
The written exam consists of multiple choice questions of which only one is correct; and numerical exercises. The structure of the exam allows you to verify the theoretical and practical skills learned by students during lessons and exercises.
The written exam consists of multiple choice questions of which only one is correct; and numerical exercises. The structure of the exam allows you to verify the theoretical and practical skills learned by students during lessons and exercises.
SECS-S/01 - STATISTICS - University credits: 6
Lessons: 40 hours
Professor:
Tommasi Chiara
Shifts:
Turno
Professor:
Tommasi ChiaraL-Z
Responsible
Lesson period
Third trimester
Educational website(s)
Professor(s)
Reception:
Wednesday from 9:00 to 12:00
Via Conservatorio, III floor, Room n. 35