The course introduces the main descriptive statistics, which are more and more used both in business and economics studies. These concepts constitute the basis of more advanced and applied statistical methods, as for example data mining, big data and web scraping. Theory will be illustrated by means of real data ets which will be discussed during the lectures. The statistical concepts are introduced with simple examples, informally described and then formally defined by means of definitions. Their theoretical properties will be stated. The practical applications will be critically examined.

1.  Univariate descriptive statistics. Introductory concepts (population, sample, case, variable), distributions (simple, frequencies, densities), measures of location (mean, mode, median), measures of scatter (variance, entropy, concentration), measures of shape (skewness, kurtosis), graphical displays (hystogram, Pareto chart, box-plot).

2.  Bivariate descriptive statistics. Bivariate distributions (contingency tables, scatter plot, stereogram), association (expected frequencies, contingencies, chi-square, joint entropy), concordance (Kendall's tau, Spearman's rho), regression (group means, conditional entropy, Goodman and Kruskal lambda), simple linear regression (definition, residuals, variants).

General Mathematics

1.  Knowledge and under standing. The student will know the basic statistical methods and their use in marketing strategies.

2.  Applying knowledge and understanding. The student will be able to explore data sets and detect their latent structures.

3.  Making judgements. The student will be able to choose the most appropriate methods for data exploration and to evaluate the quality of the obtained results.

4.  Communication skills. The student will learn to communicate the results of the exploratory analyses by means of graphs, tables, slides and reports.

5.  Learning skills. The student will be able to connect the contents of the course with the methods learnt in other courses or by self-teaching. 

The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it

Fake exams, possibly seminars.

Teaching

1.  Classes. Presentation of the theory, discussion of real data sets, informal checking of learning progresses. Teching is interactive, in order to motivate student participation.

2.  Office hours. While classes are given, there are weekly office hours, whose time is fixed before the classes themselves. When there are no classes office hours are decided together with the student by e-mail.

3.       Innovative teaching based on flipped classrooms and peer-to-peer learning

Innovative teaching methods

1- Flipped classroom

2-Peer learning

Attendance

Class attendance is not mandatory but it is recommended.

Course books

Notes written by the lectures. They include solutions to exercises, worked exercises, summary schemes, examination rules, fake exams.

Assessment

Thirty exercises and thirty questions chosen from the teaching material. Each exercise with a correct solution and every correct answer corresponds to half a point. The sum of points constitutes the final mark, raised to the next higher integer when not an integer itself. The student has 90 minutes to complete the exam. The student who achieves thirty points and who hands in the exam within one hour will have the mention of excellence.

Disabilità e DSA

Le studentesse e gli studenti che hanno registrato la certificazione di disabilità o la certificazione di DSA presso l'Ufficio Inclusione e diritto allo studio, possono chiedere di utilizzare le mappe concettuali (per parole chiave) durante la prova di esame.

A tal fine, è necessario inviare le mappe, due settimane prima dell’appello di esame, alla o al docente del corso, che ne verificherà la coerenza con le indicazioni delle linee guida di ateneo e potrà chiederne la modifica.

Teaching

 Individual study and Office hours. While classes are given, there are weekly office hours, whose time is fixed before the classes themselves. When there are no classes office hours are decided together with the student by e-mail. 

Attendance

Class attendance is not mandatory but it is recommended.

Course books

Notes written by the lectures. They include solutions to exercises, worked exercises, summary schemes, examination rules, fake exams. 

Assessment

Thirty exercises and thirty questions chosen from the teaching material. Each exercise with a correct solution and every correct answer corresponds to half a point. The sum of points constitutes the final mark, raised to the next higher integer when not an integer itself. The student has 90 minutes to complete the exam. The student who achieves thirty points and who hands in the exam within one hour will have the mention of excellence.

Disabilità e DSA

Le studentesse e gli studenti che hanno registrato la certificazione di disabilità o la certificazione di DSA presso l'Ufficio Inclusione e diritto allo studio, possono chiedere di utilizzare le mappe concettuali (per parole chiave) durante la prova di esame.

A tal fine, è necessario inviare le mappe, due settimane prima dell’appello di esame, alla o al docente del corso, che ne verificherà la coerenza con le indicazioni delle linee guida di ateneo e potrà chiederne la modifica.

Innovative teaching based on flipped classrooms and peer-to-peer learning