Unit

Code	A005889
Location	TERNI
CFU	3
Teacher	Duccio Martelli
Teachers	Loris Lino Maria Nadotti (Codocenza) Duccio Martelli
Hours	12 ore (Codocenza) - Loris Lino Maria Nadotti 12 ore - Duccio Martelli
Learning activities	Caratterizzante
Area	Discipline aziendali
Sector	ECON-09/B
Type of study-unit	Obbligatorio (Required)

Code	A005890
Location	TERNI
CFU	3
Teacher	Duccio Martelli
Teachers	Duccio Martelli
Hours	24 ore - Duccio Martelli
Learning activities	Caratterizzante
Area	Discipline aziendali
Sector	ECON-09/B
Type of study-unit	Obbligatorio (Required)

Code	A005888
Location	TERNI
CFU	3
Teacher	Duccio Martelli
Teachers	Duccio Martelli
Hours	24 ore - Duccio Martelli
Learning activities	Caratterizzante
Area	Discipline aziendali
Sector	ECON-09/B
Type of study-unit	Obbligatorio (Required)

Code	A005891
Location	TERNI
CFU	3
Teacher	David Aristei
Teachers	David Aristei
Hours	24 ore - David Aristei
Learning activities	Caratterizzante
Area	Discipline statistiche e matematiche
Sector	STAT-02/A
Type of study-unit	Obbligatorio (Required)
Language of instruction	Italian
Contents	This part of the course is focused on The linear regression model, used for analysing causal relationships between variables and making forecasts
Reference texts	Main textbook: - Bracalente B., Cossignani M., Mulas A.: “Statistica Aziendale”, McGraw-Hill, Milano 2009. - Biggeri L., Bini M., Coli A., Grassini L., Maltagliati M.: “Statistica per le decisioni aziendali”, 2/Ed., Pearson, Milano 2017 Additional suggested textbook: - Bassi, F., Ingrassia, S.: “Statistica per analisi di mercato. Metodi e strumenti”, Pearson, Milano 2022. - Stock, J.H., Watson, M.W.: Introduzione all’econometria”, 5/Ed., Pearson, Milano 2020 Class slides and materials used during the laboratory sessions will be distributed through the UniStudium e-larning platoform
Educational objectives	This course will introduce students to the most relevant statistical methods for business analysis. In particular, theoretical lectures will be focused on the presentation of regression models for the analysis of economic and business data. Specific attention will be also devoted to on empirical applications. Every week there will be a practical laboratory session in which students will apply concepts learned during the theoretical lectures, using statistical software.
Prerequisites	This course requires basic knowledge of descriptive and inferential statistics and probability theory.
Teaching methods	Face-to-face lessons completed with practical laboratory activities
Other information	Attending students are to complete some (non-compulsory) take-home assignments
Learning verification modality	Written examination After grading, the instructor reserves the right to invite the student for an additional oral examination.
Extended program	1) Introduction to business statistics Data sources for business analysis 2) Data analysis: measures of association Pearson’s linear correlation coefficient Inference of association measures 3) The linear regression model Simple and multiple regression models Parameters estimation by ordinary least squares Goodness-of-fit Hypothesis testing Prediction Diagnostic analyses: non-linearity, heteroscedasticity and multicollinearity issues
Obiettivi Agenda 2030 per lo sviluppo sostenibile	4, 8, 9, 12

Code	A005892
Location	TERNI
CFU	3
Teacher	David Aristei
Teachers	David Aristei
Hours	24 ore - David Aristei
Learning activities	Caratterizzante
Area	Discipline statistiche e matematiche
Sector	STAT-02/A
Type of study-unit	Obbligatorio (Required)
Language of instruction	Italian
Contents	This part of the course is focused on regression models for binary dependent variables
Reference texts	Main textbook: - Bracalente B., Cossignani M., Mulas A.: “Statistica Aziendale”, McGraw-Hill, Milano 2009. - Biggeri L., Bini M., Coli A., Grassini L., Maltagliati M.: “Statistica per le decisioni aziendali”, 2/Ed., Pearson, Milano 2017 Additional suggested textbook: - Bassi, F., Ingrassia, S.: “Statistica per analisi di mercato. Metodi e strumenti”, Pearson, Milano 2022. - Stock, J.H., Watson, M.W.: Introduzione all’econometria”, 5/Ed., Pearson, Milano 2020 Class slides and materials used during the laboratory sessions will be distributed through the UniStudium e-larning platoform
Educational objectives	This course will introduce students to the most relevant statistical methods for business analysis. In particular, theoretical lectures will be focused on the presentation of regression models for the analysis of economic and business data. Specific attention will be also devoted to on empirical applications. Every week there will be a practical laboratory session in which students will apply concepts learned during the theoretical lectures, using statistical software.
Prerequisites	This course requires basic knowledge of descriptive and inferential statistics and probability theory.
Teaching methods	Face-to-face lessons completed with practical laboratory activities
Other information	Attending students are to complete some (non-compulsory) take-home assignments
Learning verification modality	Written examination After grading, the instructor reserves the right to invite the student for an additional oral examination.
Extended program	Regression models for binary dependent variables The linear probability model The logistic regression (logit) model Estimation of logit parameters Interpretation of results and inference Predicted probabilities Measures of goodness-of-fit
Obiettivi Agenda 2030 per lo sviluppo sostenibile	4, 8, 9, 12