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).

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

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

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.

Innovative teaching methods

Flipped classroom

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 chosen from the teacheing material. Each exercise with a correcct solution corresponds to a point. The sum of points constitutes the final mark. The student has one hour at her/his disposal for the exam.

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.

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

Written exam based on questions and exercises from the teaching material.

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.