First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Human and Social Sciences and Cultural Heritage
Course unit
SFO2042659, A.A. 2015/16

Information concerning the students who enrolled in A.Y. 2014/15

Information on the course unit
Degree course First cycle degree in
SF1333, Degree course structure A.Y. 2011/12, A.Y. 2015/16
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination SOCIAL STATISTICS WORKSHOP
Department of reference Department of Philosophy, Sociology, Education and Applied Psychology
Mandatory attendance No
Language of instruction Italian
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Teacher in charge RINA CAMPORESE 000000000000

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses SECS-S/05 Social Statistics 6.0

Course unit organization
Period Second semester
Year 2nd Year
Teaching method frontal

Type of hours Credits Teaching
Hours of
Individual study
Lecture 6.0 42 108.0 No turn

Start of activities 01/03/2016
End of activities 11/06/2016
Show course schedule 2019/20 Reg.2011 course timetable

Examination board
Board From To Members of the board
10 2019/20 01/10/2019 30/11/2020 MEGGIOLARO SILVIA (Presidente)
CASTIGLIONI MARIA (Membro Effettivo)
CLERICI RENATA (Membro Effettivo)
9 2018/19 25/02/2019 30/11/2019 CAMPORESE RINA (Presidente)
CLERICI RENATA (Membro Effettivo)
8 2018/19 01/10/2018 23/02/2019 CLERICI RENATA (Presidente)
BOCCUZZO GIOVANNA (Membro Effettivo)
7 2017/18 01/10/2017 30/11/2018 MEGGIOLARO SILVIA (Presidente)
CASTIGLIONI MARIA (Membro Effettivo)
CLERICI RENATA (Membro Effettivo)
6 2016/17 01/10/2016 30/11/2017 MEGGIOLARO SILVIA (Presidente)
CASTIGLIONI MARIA (Membro Effettivo)
CLERICI RENATA (Membro Effettivo)
5 2016/17 01/10/2016 30/11/2017 CAMPORESE RINA (Presidente)
CLERICI RENATA (Membro Effettivo)
4 2015/16 01/10/2015 30/11/2016 CAMPORESE RINA (Presidente)
CLERICI RENATA (Membro Effettivo)
3 2015/16 01/10/2015 30/11/2016 CLERICI RENATA (Presidente)
CASTIGLIONI MARIA (Membro Effettivo)

Prerequisites: Having attended the course "Social Statistics" is recommended, but not compulsory.
Target skills and knowledge: Obtaining technical abilities in the statistical analysis of data (through the use of Excel) in order to know how describing and valuating phenomena.
Abilities in data interpretation.
Abilities in the analysis of relationships between variables (not only from the descriptive viewpoint, but also from the inferential one).
Examination methods: Examination using computer; students will have to show their abilities in using statistical methods implemented by spreadsheet to organize and study real datasets.
Assessment criteria: Evaluation will be based on the abilities in applying methods of data analysis, in interpreting results, and in the understanding of used methods.
Course unit contents: After some introductory lessons on the use of Excel and on the presentation of some theoretical aspects of descriptive statistics (recalling some concepts already known to students who have attended the course "Social Statistics"). These notions are applied to analyse and describe phenomena, using an automatic analysis tool such as Excel which allows to consider real large size dataset. Then, the course will develop the abilities acquired from a descriptive viewpoint in inferential area (from the theoretical perspective, but, above all, from the practical one).
In the following, the detailed programme is presented:
- monovariate analysis: frequence tables, graphics, synthetic measures and variability;
- bivariate analysis: tables, profiles analysis, measure of association, correlation;
- inferential concepts: sampling schemes, probabilistic models (normal distribution, chi-square, Student’s t distribution, Snedecor’s F), sample distribution of the mean;
- Infernce: point and interval estimates (with particular reference to the mean). Developments will regard the comparisons between two or more populations (variance analysis) and independence hypothesis testing.
In addition, the linear regression models (and multiple linear regressions) will be examined.
All these aspects will be briefly presented by the theoretical viewpoint, and the practical aspects will be favoured.
Planned learning activities and teaching methods: Lessons supported by exercises using computer. Materials will be available to the students.
Textbooks (and optional supplementary readings)
  • Borazzo F.P. e Perchinunno P., Analisi statistiche con Excel. --: Pearson Education, 2007. Cerca nel catalogo
  • Giuliani D., Dickson M.M., Analisi statistica con Excel. --: Maggioli Editore, 2015.