STATISTICS
STATISTICA
A.Y. | Credits |
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2024/2025 | 6 |
Lecturer | Office hours for students | |
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Nicola Maria Rinaldo Loperfido | Half an hour after each class, 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
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
Notes written by the lectures. They include solutions to exercises, worked exercises, summary schemes, examination rules, fake exams.
Teaching, Attendance, Course Books and Assessment
- Teaching
In the classes there will be 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
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
The exam objectively assesses the Learning Achievements. It includes thirty exercises to be solved. Each correctly solved exercise corresponds to a point and the sum of all points constitutes the final mark. The student who has scored thirty points and hands in the assignment within 45 minutes from the beginning of the exam will get the mention of excellence.
The exam includes exercises to be solved. Each exercise recalls a concept, which must be known to obtain the correct solution (knowledge and understanding). Solutions also require the knowledge of the appropriate operational rules (applying knowledge and understanding). The choice between different solving methods depends on the information available to the student, who must use them critically (making judgments). Effective communication of the solutions requires the communication skill taught in the course (communication skills). The efficiency in solving the exercises will be increased if the student will adapt to her/his own personal features the solution method taught in the course (learning skills).
- 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
The exam objectively assesses the Learning Achievements. It includes thirty exercises to be solved. Each correctly solved exercise corresponds to a point and the sum of all points constitutes the final mark. The student who has scored thirty points and hands in the assignment within 45 minutes from the beginning of the exam will get the mention of excellence.
The exam includes exercises to be solved. Each exercise recalls a concept, which must be known to obtain the correct solution (knowledge and understanding). Solutions also require the knowledge of the appropriate operational rules (applying knowledge and understanding). The choice between different solving methods depends on the information available to the student, who must use them critically (making judgments). Effective communication of the solutions requires the communication skill taught in the course (communication skills). The efficiency in solving the exercises will be increased if the student will adapt to her/his own personal features the solution method taught in the course (learning skills).
- 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.
Notes
The student can ask to take the exam in English and to have textboks in English.
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