# APPLIED MATHEMATICS

A.A. di erogazione 2015/2016
Insegnamento obbligatorio

(A.A. 2015/2016)

Docenti

GUERRAGGIO ANGELO
Anno di corso:
1
Tipologia di insegnamento:
Caratterizzante
Settore disciplinare:
METODI MATEMATICI DELL'ECONOMIA E DELLE SCIENZE ATTUARIALI E FINANZIARIE (SECS-S/06)
Crediti:
6
Ciclo:
Secondo Semestre
Ore di attivita' frontale:
40
Dettaglio ore:
Lezione (40 ore)

The main purpose of the Applied Statistics module is to supply a general overview of the use of statistic methods as a worthwhile support for decisional processes in management, marketing and finance.

During the course, both theoretical and practical sessions will be provided, focusing on applied data analysis:

• Applied statistical methodology
• Interpretation of the results

The practical sessions are based on real business data analyzed using MYSTAT software.

Basic statistics knowledge (both descriptive and inferential) is highly recommended.

FIRST PART:

• Course introduction. Examination Rules. Presentation of the course. Elements of univariate statistics.
• Presentation of MySTAT software; exercises about univariate statistics.
• Elements of bivariate statistics: cross tabulation, chi-squared test, linear correlation e analysis of variance. T-test and F-test.
• Practical session about bivariate statistics
• The simple linear regression model: theoretical elements and inference on the coefficients; the use of categorical variables (dummy)
• Practical session about simple linear regression model
• The multiple linear regression: theoretical elements and inference on the parameters; multicollinearity F test, residuals analysis.
• Practical session about the multiple linear regression

SECOND PART:

• Factor analysis: methodological aspects and practical examples.
• Practical session about Factor analysis
• Non-hierarchical cluster analysis (K-Means): methodological aspects and practical examples.
• Exercises about Non-hierarchical cluster analysis (K-Means).
• Hierarchical cluster analysis: methodological aspects and practical examples.
• Practical session about Hierarchical cluster analysis.
• Logistic regression: definitions, estimation and interpretation of the coefficients, evaluation of the model effectiveness.
• Practical session about logistic regression.

EXAMINATION RULES:

The exam consists of a written exam, composed by exercises, theory questions and interpretation of MYSTAT outputs. The exam program is constituted by the subjects described in the course syllabus. All the subjects are covered in the material available on the weblearning page of the course.

The exam will be written. At their choice the students can select to take the exam through the two midterms or through a unique final exam.

Partial Exam

The first midterm shall concern all the material in the syllabus covering the first part of the course.
The second midterm shall concern the material in the syllabus covering the second part of the course.
Each partial exam will last 1 hour.
Each midterm can have a maximum grade of 16 and the final grade will be the sum of the grades in the two midterms. For instance, if the grade in the first midterm is 4 and in the second midterm is 16, one obtains the grade of 20.
The minimum grade to pass the exam is 18. Thus, to access the second midterm a score greater than or equal to 2 in the first midterm is necessary. A total grade higher than 30 (i.e., 31 or 32) is rewarded by “cum laude.”

General Exam

The exam shall last 1 hour and 30 minutes. There will be exercises covering the entire course material.
A total grade higher than 30 (i.e., 31 or 32) is rewarded by “cum laude.”

- Slides and other digital materials provided by the teachers