STATISTICS
cod. 00914

Academic year 2013/14
1° year of course - Second semester
Professor
Luca SABATINI
Academic discipline
Statistica (SECS-S/01)
Field
Formazione interdisciplinare
Type of training activity
Basic
54 hours
of face-to-face activities
9 credits
hub: PARMA
course unit
in - - -

Learning objectives

Knowledge and understanding
The course will provide students with the tools for statistical data analysis in the social and political sciences. At the end of the course, the student will be able to employ statistical analysis techniques most frequently used and the methods of collecting information more widespread. Moreover, know how to interpret and evaluate the results of political or social opinion polls.

Applying knowledge and understanding
Through appropriate arguments, the student will be able to understand, analyze and interpret the themes covered in the course, with particular reference to social and political research.

Making judgments
At the end of the course, the student must have acquired the ability to critically interpret the results of the survey at the center of national or local political debate.

Communication skills
The student will be able to communicate to various stakeholders, effectively and with appropriate language, their own reflections on the interpretation and evaluation of issues and problems related to the course content.

Ability to learn
Given the progressive nature of the course, the student should have acquired the ability to approach so as independent as possible in more complex and in-depth studies.

Prerequisites

No.

Course unit content

General Section
Univariate analysis
• Concepts, indicators and variables
• The transformation of the data
• Tables and graphs
• Means and percentiles
• Measures of dispersion

Bivariate analysis
• Correlation and regression
• Contingency tables and chi-square test

Introduction to statistical inference
• Normal distribution
• Sampling
• Confidence intervals (means and proportions)
• Z-test and t-test

Special section
The special part of the course examines themes related to the use of statistics in the study of voting behavior

Full programme

- - -

Bibliography

General part:
Diamond I., Jefferies J (2006), Introduzione alla statistica per le scienze sociali, McGraw Hill, Milano
Special section:
A booklet will be available at the beginning of the course

Teaching methods

Lectures, exercises.

Assessment methods and criteria

Written exam (theoretical questions, resolution of exercises and interpretation of a research).

The knowledge and understanding will be assessed through four exercises relating to certain topics covered in class.

The ability to communicate and the ability to apply the knowledge gained through appropriate arguments and reflections will be assessed with a request to develop and argue an issue addressed in class.

Judgement will be evaluated by requiring the student to interpret and comment on the results of a socio-political research, through the articulation of coherent and logical different notions acquired during the teaching.

Learning skills will be assessed across the various answers to several questions of verification.

Other information

During the course will be invited researchers of the major Italian opinion poll institutes.

2030 agenda goals for sustainable development

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Contacts

Toll-free number

800 904 084

Student registry office

E. segreteria.giurisprudenza@unipr.it

 

Quality assurance office

Education manager:
Dott. Pietro Simoni
T. +39 0521 903905
Office E. giurisp.didattica@unipr
Manager E. pietro.simoni@unipr.it

President of the degree course

Prof. Emanuele Castelli
E. emanuele.castelli@unipr.it

Faculty advisor

Prof. Fabio Corigliano
E. fabio.corigliano@unipr.it

Carrer guidance delegate

Prof. Francesco Mazzacuva
E. francesco.mazzacuva@unipr.it

Tutor Professor

Prof. Giacomo Degli Antoni
E. giacomo.degliantoni@unipr.it

Erasmus delegates

Prof.ssa Veronica Valenti
E. veronica.valenti@unipr.it
 

Quality assurance manager

Prof.ssa Laura Pineschi
E. raq.scienzepolitiche@unipr.it

Tutor student

link: studenti tutor