During the Covid-19 emergency period, lessons will be held remotely asynchronously with synchronous videoconferencing events.In the non-emergency period the lessons will be frontal. During the lectures, the topics explained will be dealt with from a theoretical point of view and through empirical cases.
The SPSS software will also be shown.
Unità didattica
Course full name
Statistical Methods for the Territorial and Social Environment
Course ID number
2122-2-F7601M007-F7601M017M
Course Syllabus
Obiettivi formativi
L'obiettivo dell'insegnamento è di dare agli studenti conoscenze statistiche progredite necessarie per effettuare autonomamente l'analisi quantitativa e l'interpretazione dei risultati di elaborazioni riguardanti i fenomeni turistici.
Contenuti sintetici
Durante il corso di Statistica dell’ambiente fisico e sociale verranno presentati i metodi di analisi statistica multivariata con particolare attenzione a quelli maggiormente utilizzati per l’analisi dell’ambiente inteso sia come territorio sia come quello costituito dalle condizioni di vita e di lavoro, dal livello di reddito, dal grado d'istruzione e dalla comunità di cui un individuo fa parte. Nel corso si illustrerà l’utilizzo del software SPSS per la soluzione di problemi reali
Programma esteso
Agresti A., Finlay B. “Statistical Methods for the Social Sciences” Pearson International Edition (fourth Edition)
Ch1: Introduction (pag. 1-7)
- Introduction to Statistical Methodology
- Descriptive Statistics and Inferential Statistics
- The Role of Computers In statistics
Ch2: Sampling and Measurement (pag. 11-21)
- Variables and their measurement
- Randomization
- Sampling Variability and Potential Bias
Ch 3: Descriptive Statistics (pag. 31-59)
- Describing Data with Tables and Graphs
- Describing the Center of the Data
- Describing Variability of the Data
- Measures of Position
- Bivariate Descriptive Statistics
- Sample Statistics and Population Parameters
Ch8: Analyzing Association between Categorical Variables (pag. 221-239)
- Contingency tables
- Chi-Squared Test of Independence
- Residuals: Detecting the Pattern of Association
- Measuring Association In Contingency Tables
Ch9: Linear regression and correlation (pag.255-283)
- Linear Relationships
- Least Squares Prediction Equation
- The Linear Regression Model
- Measuring Linear Association: the Correlation
- Inference for the Slope and Correlation
Ch10: Introduction to multivariate relationship (pag. 301-313)
- Association and Causality
- Controlling for Other Variables
- Types of Multivariate Relationships
Ch11: Multiple Regression and Correlation (pag. 321-340;345-355)
- The Multiple Regression Model
- Example with Multiple Regression Computer Output
- Multiple Correlation and R2
- Inference for Multiple Regression Coefficients
- Comparing Regression Models
- Partial Correlation
- Standardized Regression Coefficients
Combining Regression and ANOVA: Quantitative and Categorical Predictors (pag. 416-419)
- Regression with Quantitative and Categorical PredictorsPrerequisiti
Conoscenza della statistica descrittiva univariata
Metodi didattici
Nel periodo di emergenza Covid-19 le lezioni si svolgeranno da remoto asincrono con eventi in videoconferenza sincrona.
In periodo di non emergenza le lezioni saranno frontali
Modalità di verifica dell'apprendimento
Nel periodo di emergenza Covid-19 gli esami saranno solo telematici. Verranno svolti utilizzando la piattaforma WebEx e nella pagina e-learning dell'insegnamento verrà riportato un link pubblico per l'accesso all'esame di possibili spettatori virtuali.
La verifica dell'apprendimento comprende una prova scritta e un lavoro di gruppo. La prova scritta valuterà le conoscenza teorica degli argomenti. Nel lavoro di gruppo gli studenti dovranno dimostrare la conoscenza del software SPSS.
Testi di riferimento
Agresti A., Finlay B. “Statistical Methods for the Social Sciences” Pearson International Edition (fourth Edition).
Periodo di erogazione dell’insegnamento
Secondo semestre
Lingua di insegnamento
Inglese
Learning objectives
The course will give to the students the advanced statistical knowledge necessary to independently perform quantitative analysis and interpretation of the results concerning the tourism phenomena.
Contents
During the course of the Territorial and social statistics will be presented the methods of multivariate statistical analysis with special focus on those most commonly used for the analysis , where for the environment is understood as a territory and as the one constituted by the conditions of life and work, from income level, educational level and the community to which an individual belongs. The course will illustrate the use of the SPSS software for the solution of real problems.
Detailed program
Agresti A., Finlay B. “Statistical Methods for the Social Sciences” Pearson International Edition (fourth Edition)
Ch1: Introduction (pag. 1-7)
- Introduction to Statistical Methodology
- Descriptive Statistics and Inferential Statistics
- The Role of Computers In statistics
Ch2: Sampling and Measurement (pag. 11-21)
- Variables and their measurement
- Randomization
- Sampling Variability and Potential Bias
Ch 3: Descriptive Statistics (pag. 31-59)
- Describing Data with Tables and Graphs
- Describing the Center of the Data
- Describing Variability of the Data
- Measures of Position
- Bivariate Descriptive Statistics
- Sample Statistics and Population Parameters
Ch8: Analyzing Association between Categorical Variables (pag. 221-239)
- Contingency tables
- Chi-Squared Test of Independence
- Residuals: Detecting the Pattern of Association
- Measuring Association In Contingency Tables
Ch9: Linear regression and correlation (pag.255-283)
- Linear Relationships
- Least Squares Prediction Equation
- The Linear Regression Model
- Measuring Linear Association: the Correlation
- Inference for the Slope and Correlation
Ch10: Introduction to multivariate relationship (pag. 301-313)
- Association and Causality
- Controlling for Other Variables
- Types of Multivariate Relationships
Ch11: Multiple Regression and Correlation (pag. 321-340;345-355)
- The Multiple Regression Model
- Example with Multiple Regression Computer Output
- Multiple Correlation and R2
- Inference for Multiple Regression Coefficients
- Comparing Regression Models
- Partial Correlation
- Standardized Regression Coefficients
Combining Regression and ANOVA: Quantitative and Categorical Predictors (pag. 416-419)
- Regression with Quantitative and Categorical PredictorsPrerequisites
Univariate descriptive statistics
Teaching methods
Assessment methods
In the Covid-19 emergency period, exams will only be online. They will be carried out using the WebEx platform and on the e-learning page of the course there will be a public link for access to the examination of possible virtual spectators.The assessment includes a written exam and a group work. The written exam will evaluate the theoretical knowledge of the topics. The group work will evaluate the knowledge of SPSS.
Textbooks and Reading Materials
Agresti A., Finlay B. “Statistical Methods for the Social Sciences” Pearson International Edition (fourth Edition).
Semester
Second semester
Teaching language
English