Statistics, Economics, and Social Sciences

Activity type

Discipline Statistiche, Statistiche Applicate e Demografiche

SSD

SECS-S/01

Year

2nd year

Semester

2nd semester

CFU

3

Hours distribution

27 classroom hours

Lecturers

CRISTINA MOLLICA
CRISTINA MOLLICA

Activity type

Discipline Statistiche, Statistiche Applicate e Demografiche

SSD

SECS-S/01

Year

2nd year

Semester

2nd semester

CFU

9

Hours distribution

72 classroom hours

Lecturers

LUCA TARDELLA
LUCA TARDELLA

Learning goals.
The primary educational objective of the course is students' learning of the main problems and methods of statistical Inference and its different alternative theoretical approaches.
Students must also be able to solve the analytical problems necessary to apply the above methods and be able to interpret the results that derive from their application to real data.
Knowledge and understanding.
After attending the course the students know and understand the main inferential problems (point and interval parametric estimation and hypothesis testing of the most important univariate statistical models) and the main methods to be used to solve these problems (for example: maximum likelihood estimation, confidence intervals, parametric tests).
Applying knowledge and understanding.
At the end of the course the students are able to formalize real problems in terms of inferential problems and to apply the specific methods of the discipline to solve them.
They are also able to process the most important statistical models (with one or two unknown parameters) and to apply the methods to models not covered in the lessons.
Finally, they are able to apply the methods to the data and to interpret the results.
Making judgements.
Students develop critical skills through the application of inferential methodologies to a wide range of statistical models.
They also develop the critical sense through the comparison between alternative solutions to the same problem obtained using different inferential logics.
They learn to critically interpret the results obtained by applying the procedures to real data sets.
Communication skills.
Students acquire by means of theoretical study and by solving practical exercises, the technical-scientific language of the discipline, which must be properly used both in the intermediate and final written tests and in the oral axam.
Communication skills are also developed through group activities stimulated during labs and participation to a public discussion forum Learning skills.
Students who pass the exam have learned a method of analysis that allows them to tackle, in future more advanced courses, the study of the formal properties of inferential procedures in more complex modeling contexts.

Module: LABORATORY
N/D
Module: STATISTICAL INFERENCE
N/D

Module: LABORATORY
N/D
Module: STATISTICAL INFERENCE
N/D

Module: LABORATORY
N/D
Module: STATISTICAL INFERENCE
N/D

Module: LABORATORY
N/D
Module: STATISTICAL INFERENCE
N/D

Module: LABORATORY
N/D
Module: STATISTICAL INFERENCE
N/D

Module: LABORATORY
N/D
Module: STATISTICAL INFERENCE
N/D

Module: LABORATORY
N/D
Module: STATISTICAL INFERENCE
N/D

Module: LABORATORY
N/D
Module: STATISTICAL INFERENCE
N/D

Module: LABORATORY
N/D
Module: STATISTICAL INFERENCE
N/D

Module: LABORATORY
N/D
Module: STATISTICAL INFERENCE
N/D