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Single discipline educational activity
Course Sheet Academic Year of enrolment:
Professor and Collaborators:
Hours of classroom activity:
Prerequisites:
Knowledge of general mathematics and descriptive statistics is recommended.
Objectives
Contents The course is divided into the following points:
Statistical information for firms.
Index numbers.
Sample surveys.
Data matrix and preliminary data analysis.
Probability and inference.
Multivariate statistical analysis for business data and company business performances.
Measures of firm efficiency.
Extended Syllabus - Statistical information for firms: data sources, statistical information quality.
- Index numbers: fixed base index, mobile base index, composite indexes.
- Sample surveys: different steps, sample design, questionnaire.
- Data matrix and preliminary data analysis.
- Probability and inference: discrete and continuous random variables, point estimation, confidence intervals, hypothesis testing.
- Multivariate statistical analysis for business data and company business performances: multiple linear regression model (hypothesis, estimation, inference, case studies).
- Measures of firm efficiency. Different approaches to efficiency measurement: parametric and non-parametric methods.
Recommended Bibliography - Cicchitelli G., D’Urso P., Minozzo M. Statistica: principi e metodi. Pearson, Milano
(for the following topics: probability and inference).
- Bracalente B., Cossignani M., Mulas A. Statistica aziendale. Mc-Graw-Hill, Milano.
Other supporting material provided by teacher will be available on the e-learning page.
Methods of Provision
Teaching Methods The course includes 72 hours of lessons divided into 3 weekly lessons and will be organized in frontal lessons, exercises, case studies.
Frequency is recommended.
Evaluation methods Verification of learning:
The assessment of the learning level will be carried out with the use of a written test.
The written examination consists of: i) both open and multiple choice questions about topics covered during the course; ii) exercises in which students are asked to solve real case-studies using statistical methods presented during the course.
The exam score is on a 30-point scale.
Contacts/More Information E-mail: agnese.rapposelli@unich.it
Reception hours: Tuesday 11.00 -13.00.
All information concerning the course and other learning materials will be available on fad.unich.it (on the e-learning page named Corporate Statistics).
Erasmus students can take their exams in English or in French.