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
- Statistica per le decisioni (III edizione), Il Mulino (2020)
Domenico Piccolo
Textbook for English students
- Statistics: Principles and Methods, Pearson (2020)
Giuseppe Cicchitelli - Pierpaolo D’Urso - Marco Minozzo
Teaching materials: Supplementary materials, articles, readings and homeworks will be provided through the LMS MS-Teams platform and the webpage associated to the class.
Statistical Computing with R [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
- R for Data Science, O’Reilly
Garrett Grolemund - Hadley Wickham - Intuitive Introductory Statistics, Springer (2017) [first two chapters]
Douglas A. Wolfe - Grant Schneider
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)
- Fondamenti di Psicometria (III edizione), McGraw-Hill (2020)
Carlo Chiorri - Fondamenti di Statistica, Pearson (2018)
Arthur Aaron - Elliot J. Coups - Elaine N. Aron - Psicometria. Fondamenti, metodi e applicazioni, Il Mulino (2008)
Stefania Mannarini
Textbook for English students
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]
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
- Analisi dei dati e data mining per le decisioni aziendali, Giuffrè, 2007
Sergio Zani - Andrea Cerioli - R for Data Science, O’Reilly
Garrett Grolemund - Hadley Wickham
Textbooks for English students
- R for Data Science, O’Reilly
Garrett Grolemund - Hadley Wickham - Exploratory Multivariate Analysis by Example using R
Francois Husson, Sebastien Le, Jérôme Pagès
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 |
|---|---|---|---|
| 2019-2022 | Production Process Control | English | Naples Federico II |
| 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” |