Statistics
A.A. 2019/2020
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 implement the knowledge learned in the particular context of the political and social sciences, using inferential statistics.
Risultati apprendimento attesi
At the end of the course, the student shall know the main statistical approaces to describe a statistical variable and to measure the bivariate relationships between variables. Moreover 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.
Periodo: Primo trimestre
Modalità di valutazione: Esame
Giudizio di valutazione: voto verbalizzato in trentesimi
Corso singolo
Questo insegnamento non può essere seguito come corso singolo. Puoi trovare gli insegnamenti disponibili consultando il catalogo corsi singoli.
Programma e organizzazione didattica
Edizione unica
Responsabile
Periodo
Primo trimestre
Programma
Chapter 1, Agresti and Finlay, Statistical Methods for the Social Sciences
Introduction to statistical methodology
Descriptive statistics and inferential statistics
The role of computers in statistics
Chapter 2, Agresti and Finlay, Statistical Methods for the Social Science
Sampling and Measurement
Variables and their measurement
Randomization
Sampling variability and potential bias
other probability sampling methods *
Chapter 3 Agresti and Finlay, Statistical Methods for the Social Sciences
Descriptive statistics
Describing data with tables and graphs
Describing the center of the data
Describing variability of the data
Measure of position
Bivariate descriptive statistics
Sample statistics and population parameters
Chapter 4 Agresti and Finlay, Statistical Methods for the Social Sciences
Probability Distributions
Introduction to probability
Probablitity distributions for discrete and continuous variables
The normal probability distribution
Sampling distributions describe how statistics vary
Sampling distributions of sample means
Review: Probability, sample data, and sampling distributions
Chapter 5 Agresti and Finlay, Statistical Methods for the Social Science
Statistical inference: estimation
Point and interval estimation
Confidence interval for a proportion
Confidence interval for a mean
Choice of sample size
Chapter 6 Agresti and Finlay, Statistical Methods for the Social Sciences
Statistical Inference: Significance Tests
Steps of a significance test
Significance test for a eman
Significance test for a proportion
Decisions and types of errors in tests
Limitations of significance tests
Chapter 7 Agresti and Finlay, Statistical Methods for the Social Science
Comparison of Two Groups
Preliminaries for comparing groups
Categorical data: comparing two proportions
Quantitative data: comparing two means
Comparing means with dependent samples
Chapter 8 Agresti and Finlay, Statistical Methods for the Social Science
Analyzing Association between Categorical Variables
Contingency Tables
Chi-squared test of independence
Residuals: Detecting the pattern of association
Measuring association in contingency tables
Chapter 9 Agresti and Finlay, Statistical Methods for the Social Science
Linear Regression and Correlation
Linear relationships
Least squares prediction equation
The linear regression model
Measuring linear association - the correlation
Inference for the slope and correlation
Model assumptions and violations
Introduction to statistical methodology
Descriptive statistics and inferential statistics
The role of computers in statistics
Chapter 2, Agresti and Finlay, Statistical Methods for the Social Science
Sampling and Measurement
Variables and their measurement
Randomization
Sampling variability and potential bias
other probability sampling methods *
Chapter 3 Agresti and Finlay, Statistical Methods for the Social Sciences
Descriptive statistics
Describing data with tables and graphs
Describing the center of the data
Describing variability of the data
Measure of position
Bivariate descriptive statistics
Sample statistics and population parameters
Chapter 4 Agresti and Finlay, Statistical Methods for the Social Sciences
Probability Distributions
Introduction to probability
Probablitity distributions for discrete and continuous variables
The normal probability distribution
Sampling distributions describe how statistics vary
Sampling distributions of sample means
Review: Probability, sample data, and sampling distributions
Chapter 5 Agresti and Finlay, Statistical Methods for the Social Science
Statistical inference: estimation
Point and interval estimation
Confidence interval for a proportion
Confidence interval for a mean
Choice of sample size
Chapter 6 Agresti and Finlay, Statistical Methods for the Social Sciences
Statistical Inference: Significance Tests
Steps of a significance test
Significance test for a eman
Significance test for a proportion
Decisions and types of errors in tests
Limitations of significance tests
Chapter 7 Agresti and Finlay, Statistical Methods for the Social Science
Comparison of Two Groups
Preliminaries for comparing groups
Categorical data: comparing two proportions
Quantitative data: comparing two means
Comparing means with dependent samples
Chapter 8 Agresti and Finlay, Statistical Methods for the Social Science
Analyzing Association between Categorical Variables
Contingency Tables
Chi-squared test of independence
Residuals: Detecting the pattern of association
Measuring association in contingency tables
Chapter 9 Agresti and Finlay, Statistical Methods for the Social Science
Linear Regression and Correlation
Linear relationships
Least squares prediction equation
The linear regression model
Measuring linear association - the correlation
Inference for the slope and correlation
Model assumptions and violations
Prerequisiti
Mathematics. The course requires no prior knowledge of statistics, but it is advisable to have knowledge of basic mathematics.
Metodi didattici
Each topic will be presented during the lectures and some apllication to real dataset using the statistical packake SPSS will be showed to the students. Some lectures will be devote to solve pratical exercice.
Materiale di riferimento
Alan Agresti and Barbara Finlay, Statistical Methods for the Social Sciences, 4/E, Pearson
Additional materials in the ARIEL website
Additional materials in the ARIEL website
Modalità di verifica dell’apprendimento e criteri di valutazione
The exam consists of a written test in which the student must solve 2 pratical exercises and comment 2 statistical outputs produced using the package SPSS. Each exercise is 8 points. In order to verify the ability to apply the knowledge learned is required students to be able to interpret a statical output in which techniques of univariate and bivariate statistical analysis are applied to a real dataset (Istat, Eurostat , OECD, ESS, etc.). There is no oral examination.
SECS-S/01 - STATISTICA - CFU: 9
Lezioni: 60 ore
Docente:
Salini Silvia
Turni:
-
Docente:
Salini SilviaDocente/i
Ricevimento:
Il ricevimento studenti è il martedì dalle 10.00 alle 13.00 o in presenza o via Teams (meglio fissare un appuntamento) - Il ricevimento di martedì prossimo, per altri impegni accademici, non sarà svolto. Contattare il docente per un altro appuntamento.
DEMM, stanza 30, 3° p oppure su Teams