## STATISTICS STATISTICA

A.Y. Credits
2016/2017 8
Lecturer Email Office hours for students
Nicola Maria Rinaldo Loperfido

### Assigned to the Degree Course

Economics and management (L-18)
Curriculum: ECONOMIA E MANAGEMENT
Date Time Classroom / Location

### Learning Objectives

The course introduces the main descriptive statistics, which are more and more used both in business and economics studies. Theory will be illustrated by means of real data ets which will be discussed during the lectures.

### Program

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

### Learning Achievements (Dublin Descriptors)

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.

### Teaching Material

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

### Didactics, Attendance, Course Books and Assessment

Didactics

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.

Course books

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

Assessment

True/False questions extract from the teaching material, which also consider the agreements between the lecturer and the students sitting in the classes.

### Additional Information for Non-Attending Students

Didactics

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.

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.

### Notes

The student can request to sit the final exam in English with an alternative bibliography.

 « back Last update: 26/07/2016

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