Statistical Inference [Italian]
University of Naples Federico II

Prerequisites: A first class in basic Statistics. A first class in Mathematics is not mandatory but it is useful for easier understanding technical aspects.

Aim: Aim of the course is to provide students with a broad overview of basic statistical inference. Emphasis on the applications of the techniques and on the interpretation of results will help students to appreciate the relevance of the statistical tools in real life.

Content: Sampling and sampling distribution, Sampling distributions for one population problems, Sampling distributions for two population problems, Likelihood function, Sufficienty and minimal sufficiency of a statistics, Estimation, Hypothesis testing, Confidence intervals, Analysis of variance.

Textbook for Italian students

Textbook for English students

Teaching materials: Supplementary materials, articles, readings and homeworks will be provided through the LMS platform associated to the class.


Statistics for Psychology [Italian]
University of Naples Federico II

Prerequisites: No formal prerequisites requested.

Aim: Aim of the course is to provide students with a broad overview of quantitative methods for psychological and cognitive sciences. The logic of the inferential process is proposed from an application rather than a theoretical point of view.

Content: Tabular representation of a distribution. Graphic representation of a distribution. Descriptive statistics. Probability. Theoretical models. Statistical inference. Study of the relations between characters. Application contexts and methods. Analysis of variance.

Textbook for Italian students (alternative)

Textbook for English students

Teaching materials: Supplementary materials, articles, readings and homeworks will be provided through the LMS platform associated to the class.


Production Process Control [English]
University of Naples Federico II

Prerequisites: No formal prerequisites requested.

Aim: Aim of the course is to provide students with a broad overview of basic statistical methods. Room is devoted to applications and case studies. Students will learn statistics by doing, exploiting R, a popular open-source software for data analysis. Emphasis on the applications of the techniques and on the interpretation of results will help students to appreciate the relevance of the statistical tools in their study context.

Content: Data trasformation. Tidy data. Relational data. Tabular representation of a distribution. Graphical representation of a distribution. Univariate and bivariate statistical summaries. Statistical reporting. Dashboard. Reproducibility.

Textbooks

Teaching materials: Supplementary materials, articles, readings and homeworks will be provided through the LMS platform associated to the class.


Data and Statistical Models for Business [Italian] - Module 1: Exploratory data analysis
University “Suor Orsola Benincasa”

Prerequisites: No formal prerequisites. Notwithstanding, a review of the topics of the first statistics course is recommended

Aim: The aim of this course is to provide students with some logical and technical statistical tools which may be exploited to tackle economics and business issues starting from data. The exploratory data analysis and model building perspective is adopted. Room is devoted to applications and case studies.

Content: Recall of basic univariate and bivariate methods. The phases of data analysis: import, tidy, transform, visualize, model, communicate. Exploratory data analysis for business applications. Principal component analysis. Simple correspondence analysis. Multiple correspondence analysis. Cluster analysis. Supplumentary topics (for group projects): sentiment analysis, archetypal analysis, classification and regression trees, conjoint analysis, multidimensional scaling.

Textbooks for Italian students

Textbooks for English students

Teaching materials: Supplementary materials, articles, readings and homeworks will be provided through the Unisob Google Classroom associated to the class.


Previous academic years

a.y. Class Language University
2018 - 2019 Business Statistics English Cassino
2003 - 2018 Statistics Italian Cassino
2003 - 2019 Statistics (single class) Italian Cassino
2017 - 2018 Data Analysis with R English Marthin Luther Universitat
2016 - 2017 Advanced Linear Models English Marthin Luther Universitat
2013 - 2017 Statistics for Economics and Business English Cassino
2008 - 2013 Elements of Statistical Inference Italian Cassino
2008 - 2018 Models for Economic and Financial Data Italian Cassino
2014 - 2015 Statistics and Operation Research Italian Cassino
2002 - 2005 Computer Programming for Statistician Italian Naples Federico II
1999 - 2001 Basic Computer Science Italian Campania “Luigi Vanvitelli”