Course Details for A.Y. 2013/2014

The information on this page refer to the academic year 2013/2014. Therefore, several links are not available and data may be incomplete. To read the current information on the course, if it is still available, go to the university course catalogue . To read information relating other academic years, use the list at the bottom of this page.

A. Year:

2013/2014

Name:

Statistica Matematica / Mathematical Statistics

Type:

Course

Basic information

Code:

DT0030

Sector:

MAT/06

Credits:

: Laurea in Matematica 6 CFU (a) 6 CFU (b)

Term:

2° semestre

Degree(s):

Laurea in Matematica 3° anno curriculum Generale Opzionale

Language:

Italian

Teacher(s):

Maurizio Maravalle

Propaedeutics:

Mathematical Analysis

Course Objectives

The course discusses techniques for collecting and analyzing data. The main concepts of statistical thinking, both descriptive and inferential, are covered. In order to better understand the inferential techniques, the basis of probability theory and random variables are given. The focus is on analyzing real data, and particular attention is devoted to the illustration of the methods with the use of R, an open source software.

Course Content

Data collection and description through frequency distributions, graphical representation methods, and measures of location and spread. Application with statistical software R.
The study of the relationship existing between two variables using two-way frequency tables, scatterplots, and measures of dependence (covariance, linear correlation coefficient). Inferential statistics, sampling, statistics, sampling variability. Point and interval estimation. Application with statistical software R.
Parametric hypothesis testing for the population mean and the proportion of successes. Test of independence in two-way tables. Application with statistical software R.
Simple linear regression model: explanatory power of the model, parameter estimation, forecasting. Application with statistical software R.

Learning Outcomes (Dublin Descriptors)

On successful completion of this course, the student should

have a deep understanding of the nature of the data to be processed and the methods that will provide a brief description from numerical and graphic point of view with modern tools
be able to evaluate, through indicators such as indices of connection and correlation, the potential existence of links cause-effect from different variables
. be able to define the mathematical-statistical models and evaluate the significance from the probabilistic point of view also through tests of hypotheses
provide information, in numerical terms, about problems associated with modeling and their solution
be able to delve into topics of particular interest in view of the development of computer techniques and update in autonomy (self-directed)

Prerequisites and Learning Activities

Mathematical analysis

Assessment Methods and Criteria

The exam has, first a written general part and after a test on the computer using R, open source program.

Textbooks

G. Espa e R. Micciolo, Analisi esplorativa dei dati con R , APOGEO. 2012.
Domenico PICCOLO, Statistica per le decisioni-R, II Ed. , Il Mulino. 2010.
W. N. Venables, D. M. Smith and the R Development Core Team, An Introduction to R Scaricabile gratuitamente dal sito di R www.R-Project.org
David S. MOORE, Statistica di Base II Ed. , APOGEO. 2013.
P. NEWBOLD, W.L. CARLSON, B. THORNE, Statistics for Business and Economics , Pearson/Prentice Hall. 2007.

Course page updates

This course page is available (with possible updates) also for the following academic years:

To read the current information on this course, if it is still available, go to the university course catalogue .

Course information last updated on: 25 febbraio 2014, 17:04