STATISTICA SOCIALE

The course aims to provide the necessary tools for the construction and management of a database. At the end of the course, moreover, the student will be able to perform analysis of the individual variables in a descriptive perspective and to identify any functional relationships between two variables. Finally, the course will present the fundamental principles of statistical inference and the procedures for estimating and checking hypotheses. The theoretical aspects are flanked, with greater importance, by the practical aspects through the use of exercises by means of Excel.

The knowledge of mathematical fundamental notions is required

Module 1: Principles and Foundations of Statistical Data Analysis. Numerical Description of Data

• Origin and development of statistics
• Statistics and its functions
• The nature of variables
• Levels of measurement
• Statistical surveys
• Tabular and graphical representations
• Measures of central tendency
• Measures of variability

Module 2: Statistical Tools for Bivariate Analysis. Probability and Statistical Inference

• Measures of relationships between variables
• Linear relationships
• Probability
• Probability distributions and discrete random variables
• Probability distributions and continuous random variables
• Sampling and sampling distributions

Module 3: Parameter Estimation and Hypothesis Testing

• Statistical inference
• Parameter estimation
• Estimation problems involving a single population
• Estimation problems: further topics
• Hypothesis testing for a single population
• Hypothesis testing: further topics

For attending students, three intermediate assessments are scheduled, one at the end of each module. Students must pass each assessment before taking the next one. The intermediate assessments will be held in the computer laboratory and will be conducted using Excel.

For non-attending students

The examination will be entirely written and will consist of five exercises covering the entire syllabus. Students will have 90 minutes to complete the exercises. The examination will be held in the computer laboratory and will be conducted using Excel.

Assessment Criteria

Grades will be awarded according to the following scale:

Fail (Non idoneo)

• Knowledge and understanding: The student has not understood the subject, even in general terms.
• Analysis and synthesis skills: Completely absent.
• Use of references: Entirely inappropriate.

18–20

• Knowledge and understanding: The student understands the subject only in general and vague terms, with substantial gaps and significant errors.
• Analysis and synthesis skills: Barely sufficient.
• Use of references: Absent or minimally appropriate.

21–23

• Knowledge and understanding: General knowledge of the subject, with some gaps but no significant inaccuracies.
• Analysis and synthesis skills: Sufficient.
• Use of references: Sufficient but not adequately in-depth.

24–26

• Knowledge and understanding: More specific knowledge, although with some inaccuracies.
• Analysis and synthesis skills: Good. The topics are presented coherently, with a limited but evident degree of critical thinking.
• Use of references: Goes slightly beyond standard references.

27–29

• Knowledge and understanding: Very good knowledge, without inaccuracies.
• Analysis and synthesis skills: Outstanding analytical and synthesis skills.
• Use of references: The student has explored the topics in depth and can provide examples that go beyond the material covered in the assessment.

30–30 with honors (30L)

• Knowledge and understanding: Excellent knowledge.
• Analysis and synthesis skills: Excellent analytical and synthesis skills, together with a notable capacity for critical thinking.
• Use of references: Significant in-depth study and further exploration.