CODE  48384 

ACADEMIC YEAR  2022/2023 
CREDITS 

SCIENTIFIC DISCIPLINARY SECTOR  SECSS/01 
LANGUAGE  Italian 
TEACHING LOCATION 

SEMESTER  2° Semester 
TEACHING MATERIALS  AULAWEB 
Introduction to Statistical Inference
a) To provide an introduction to concepts and techniques from statistical inference which are fundamental to provide a probabilistic measure of the error committed when estimation is based on a sample from a large population. b) To deal with theoretical and practical elements of the design, analysis and inference of survey data obtained by probabilistic sampling.
At the end of the course students will be able:
Mathematical Analysis: function of a variable, integral calculus.
Algebra: elements of vector and matrix algebra.
Probability: elementary probability
Combination of traditional lectures (40 hours) and exercises sessions (24 hours)
Estimation. Populations, samples, sources of uncertainty and point estimators. Properties of point estimators. Some point estimators and their probability distributions. Confidence intervals.
Hypothesis tests. How to define and use a statistical test (hypotheses, errors of the first and second type, critical region). Parametric tests. Tests of large samples. Comparative tests. Some nonparametric tests.
Statistics and tests for linear multiple models. Confidence intervals for the parameters, estimated values and residuals, "studentized" residuals, test of hypotheses on single coefficients and on subsets of coefficients. Forecast.
1. Casella G., Berger R.L. (2002), Statistical Inference, Pacific Grove, CA: Duxbury
2. Mood A.M., Graybill F.A., Boes D.C. (1991), Introduction to the Theory of Statistics, McGrawHill, Inc.
3. Ross S.M. (2003), Probabilità e statistica per l’ingegneria e le scienze, Apogeo, Milano
4. Wasserman L. (2005), All of Statistics, Springer
Office hours: By appointment arranged by email <riccomagno@dima.unige.it>
Office hours: by appointment
EVA RICCOMAGNO (President)
GABRIELE MOSAICO
SARA SOMMARIVA (President Substitute)
GIACOMO LANCIA (Substitute)
According to the academic calendar
All class schedules are posted on the EasyAcademy portal.
The exam consists of a written and a oral part.
During the semester there will be three (not evaluated) mock exams. The lecture after each mock exam will start with a 15minute closedbook written examination.
The first two closedbook examinations are evaluated at most 3 marks and the third one at most 2 marks, for a maximum total of 8 marks.
For the students who attempted all of the three closedbook examinations, the final written examination consists of a 2hour open book examination, which is evaluated at most 23 marks to be added to the marks of the three oncourse closedbook examinations.
For the students who did not attempt the three closedbook examinations, the final written examination consists of two parts: a 45minute closedbook examination and a 2hour openbook examination. The closedbook part is evaluated at most 8 points, the openbook part is evaluated at most 23 points.
The oncourse examination and the closedbook part of the final examination test the comprehension of the theory.
The twohour openbook examination evaluates the acquired ability to apply the theoretical ideas for simple data analysis.
Date  Time  Location  Type  Notes 

23/01/2023  09:00  GENOVA  Scritto  riservato agli studenti iscritti a.a.2021/2022 e anni accademici precedenti 
16/02/2023  09:00  GENOVA  Scritto  riservato agli studenti iscritti a.a.2021/2022 e anni accademici precedenti 
19/06/2023  09:00  GENOVA  Scritto  
20/07/2023  09:00  GENOVA  Scritto  
18/09/2023  09:00  GENOVA  Scritto 
Students with DSA, disability or other special educational needs are recommended to contact the teacher at the beginning of the course, in order to organize teaching and assessment, taking in account both the class aims and the student's needs and providing suitable compensatory instruments.
Upon request by the students, the lectures and/or the exam can be held in English.