Guida degli insegnamenti

Syllabus

Partially translatedTradotto parzialmente
[66010] - BUSINESS STATISTICSBUSINESS STATISTICS
Mariateresa CIOMMI
Lingua di erogazione: INGLESELessons taught in: ENGLISH
Laurea Magistrale - [EM07] INTERNATIONAL ECONOMICS AND COMMERCE (Curriculum: BUSINESS ORGANIZATION AND STRATEGY) Master Degree (2 years) - [EM07] INTERNATIONAL ECONOMICS AND COMMERCE (Curriculum: BUSINESS ORGANIZATION AND STRATEGY)
Dipartimento: [040002] Dipartimento Scienze Economiche e SocialiDepartment: [040002] Dipartimento Scienze Economiche e Sociali
Anno di corsoDegree programme year : 1 - Secondo Semestre
Anno offertaAcademic year: 2022-2023
Anno regolamentoAnno regolamento: 2022-2023
Obbligatorio
Crediti: 6
Ore di lezioneTeaching hours: 44
TipologiaType: B - Caratterizzante
Settore disciplinareAcademic discipline: SECS-S/01 - STATISTICA

LINGUA INSEGNAMENTO LANGUAGE

INGLESE

English


PREREQUISITI PREREQUISITES



Univariate and bivariate descriptive statistics. Most relevant inferential concepts (samples, statistics, estimators).


MODALITÀ DI SVOLGIMENTO DEL CORSO DEVELOPMENT OF THE COURSE



The course will be taught through theoretical lessons and hands-on classes, during which the students analyse and synthesize a number of datasets focused on economic and business research. Computer-based analyses will be also performed in the PC-lab using the open-source software R and gretl.


RISULTATI DI APPRENDIMENTO ATTESI LEARNING OUTCOMES



Conoscenze e comprensione.




Capacità di applicare conoscenze e comprensione.




Competenze trasversali.






Knowledge and Understanding.

Students will acquire a good understanding of the statistical tools covered in the course as well as the ability to analyze economic and business datasets using appropriate statistical techniques.


Capacity to apply Knowledge and Understanding.

Students must be able to study and to understand how to use statistical software for dataset analysis and report preparation.


Transversal Skills.

The discussions as well as the practical applications that will take place during the course will enable students to enhance their autonomy and their analytical and communicative skills



PROGRAMMA PROGRAM



The program will be focused on:
- Inferential statistics: point estimators, confidence intervals, hypothesis testing, p-value
- Multivariate linear regression
- Factor analysis
- Cluster analysis


MODALITÀ DI SVOLGIMENTO DELL'ESAME DEVELOPMENT OF THE EXAMINATION



Criteri di misurazione dell'apprendimento.






Learning Evaluation Methods.

Written exam concerning the methodological issues discussed during the course and a computer-based practical assignment (not mandatory) based on the analysis of a real data set.

Class participation: Weekly computer-based exercises will be also performed in the PC-lab. Weekly home-works will be assigned.

For students with disabilities or Specific Learning Disability (SLD) who have contacted the University Disability/SLD Info Point to request support for the specific curricular exam, please note that the way the exam is taken can be adapted in accordance with the University Guidelines (https://www.univpm.it/Entra/Accoglienza_diversamente_abili).


Learning Evaluation Criteria.

Students will be evaluated in their knowledge and understanding of the most relevant statistical tools for business analysis as well as in their ability to apply them to empirical problems and settings.


Learning Measurement Criteria.

Positive grades: from 18 to 30. Cum laude can be bestowed to outstanding performance.


Final Mark Allocation Criteria.

The final grade will be obtained throught a written exam with practical and theoretical questions.



TESTI CONSIGLIATI RECOMMENDED READING



- P. Newbold, W. Carlson, B. Thorne “Statistics for Business and Economics”, Prentice Hall (Chapters: 7-8-9)
- R.A. JOHNSON, D.W. WICHERN “Applied multivariate statistical analysis” Pearson International Edition (Chapters: 1, 2, 4, 7, 9, 11, 12)

Additional material will be available in the e-learning web page


E-LEARNING E-LEARNING






Scheda insegnamento erogato nell’A.A. 2022-2023
Le informazioni contenute nella presente scheda assumono carattere definitivo solo a partire dall'A.A. di effettiva erogazione dell'insegnamento.
Academic year 2022-2023

 


Università Politecnica delle Marche
P.zza Roma 22, 60121 Ancona
Tel (+39) 071.220.1, Fax (+39) 071.220.2324
P.I. 00382520427