STATISTICS
STATISTICA
A.Y. | Credits |
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2023/2024 | 8 |
Lecturer | Office hours for students | |
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Nicola Maria Rinaldo Loperfido | One hour during class times, During other times of the academic year the student time is agreed with the lectures using e-mail messages. |
Teaching in foreign languages |
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Course with optional materials in a foreign language
English
This course is entirely taught in Italian. Study materials can be provided in the foreign language and the final exam can be taken in the foreign language. |
Assigned to the Degree Course
Date | Time | Classroom / Location |
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Date | Time | Classroom / Location |
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Learning Objectives
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.
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).
Bridging Courses
General 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
Supporting Activities
Fake exams.
Teaching, Attendance, Course Books and Assessment
- Teaching
The classes include the following activities. Presentation of the theory, discussion of real data sets, informal checking of learning progresses. Teching is interactive, in order to motivate student participation.
- 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 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, possibly raised to the first highest integer. The student has 90 minutes at her/his disposal for the exam.
The student who has scored thirty points may ask for the mention of excellence. In such a case, the teacher asks the student three questions related to the topics described in the Notes. The student who answers to the three questions is awarded the note of excellence. The student's mark is lowered by a point for each question incorrectly answered.
- 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.
Additional Information for Non-Attending Students
- Teaching
Individual study.
- 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 teacheing material. Each exercise with a correct solution and every correct answer corresponds to half a point. The sum of points constitutes the final mark, possibly raised to the first highest integer. The student has 90 minutes at her/his disposal for the exam.
The student who has scored thirty points may ask for the mention of excellence. In such a case, the teacher asks the student three questions related to the topics described in the Notes. The student who answers to the three questions is awarded the note of excellence. The student's mark is lowered by a point for each question incorrectly answered.
- 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.
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