A.A. 2021/2022
Crediti massimi
Ore totali
Obiettivi formativi
The objectives of the course are on the one hand knowledge and understanding of the basic techniques of univariate and bivariate statistical analysis and secondly the ability to actually apply the knowledge learned in the particular context of the political and socio-econonomics sciences, using inferential statistics.
Risultati apprendimento attesi
At the end of the course, the student shall know the main statistical approaches to describe a statistical variable and to measure the bivariate relationships between variables. Moreover, the student will know how to test the significance of the relationships using statistical inferential tools. The student shall also acquire the ability to read and understand simple statistical package outputs, the will be able to interpret and comment with critical approach statistical outputs results
Programma e organizzazione didattica

Edizione unica

Primo trimestre
The lessons will be held in presence but also on the Microsoft Teams platform synchronously.

The program and the reference material for student not in attendance will not change.

The exam will take place in written form, possibly in presence.
If, based on the health situation in December, it will not be possible to take the exam in person, and in any case for students who cannot be present (temporary visa restrictions, limited international mobility, health conditions or legal impediments) the exam remotely using + SEB with video-surveillance through Teams or Zoom.

The exam, in particular, will be aimed at ascertain the ability to apply the statistical techniques learned to real data and to interpret the results.
Introduction to statistical methodology
Descriptive statistics and inferential statistics
Sampling and Measurement
Variables and their measurement
Descriptive statistics
Describing data with tables and graph
Describing the center of the data
Describing variability of the data
Introduction to probability
Probability distributions for discrete and continuous variables
The normal probability distribution
The binomial probability distribution
Sampling distributions
Statistical inference
Point estimators
Confidence interval for a proportion
Confidence interval for a mean
Hypothesis Tests
Test for a mean
Test for a proportion
Bivariate analysis
Association between Categorical Variables
Contingency Tables
Chi-squared test of independence
Comparison of groups
Categorical data: comparing two proportions
Quantitative data: comparing two means
Comparing means with dependent samples
Comparing more than two groups
Linear Regression and Correlation
Least squares prediction equation
The linear regression model
Inference for the slope
Model assumptions and violations
Mathematics. The course requires no prior knowledge of statistics, but it is advisable to have knowledge of basic mathematics.
Metodi didattici
Each topic of the program will be presented theorectically during the lectures. For each topic practical lectures will be devoted to solve practical exercises. Moreover, applications to real dataset using the statistical package STATA will be showed to the students during the course. Particular attention will be devoted to the reading and interpretation of the results
Materiale di riferimento
Alan Agresti , Statistical Methods for the Social Sciences, Pearson (Chapters 1,2,3,4,5,6,7,8)
Stock J., Watson M. (2010) Introduction to Econometrics, Pearson (Chapters 1,2,3,4,5)
Additional materials (slides, exercises, exam simulations) in the ARIEL website
Modalità di verifica dell’apprendimento e criteri di valutazione
The exam consists of a written test (1.5 hours) in which the student must solve practical exercises (16 points) and comment a statistical outputs produced using the package STATA (16 points) to real datasets. Students are not required to know how to use the STATA package which is not part of the program, but they must be able to interpret the outputs that the statistical packages produce for the techniques of univariate and bivariate statistical part of the program.
Lezioni: 40 ore
Docente: Salini Silvia
Siti didattici
A partire dal 20 settembre 2021 il ricevimento sarà in presenza il martedì dalle 10.30 alle 12 e il venerdì dalle 10.30 alle 12.00. In caso i necessità è possibile prendere appuntamento, nei medesimi orari, per il ricevimento via Teams.
DEMM, stanza 30, 3° p