STATISTICS - 2

The course is one of the characterizing activities of the degree course in Economics and Commerce that allows students to acquire knowledge and understanding
of the main statistical concepts and their use in economic disciplines.
The aim of the course is to provide knowledge of analysis and management of data in order to enable students to develop the skills that enable them to structure, process,
statistically analyse data to solve some inferential problems that arise in the economic and management field.

Frontal lectures, the study and analysis of the reference texts and the suggested materials, will allow students to:

1. Knowledge and understanding
1.1 know and use the main statistical tools necessary for the analysis of economic phenomena in their various manifestations

2. Ability to apply knowledge and understanding
2.1 know how to interpret the main relative economic phenomena to the functioning of markets and businesses through the application of statistical tools
2.2 provide a summary of data on economic phenomena

3. Making judgements
3.1 critically evaluate the different scenarios in the economic decision-making process and in the management of uncertainty

The exam of MATHEMATICS is mandatory. In particular, the student should master the concepts and methods related to the systems of equations and inequalities as well as to the integral calculus.
Good knowledge of set theory.

The list of mandatory priority exams is available on the webpage https://www.unive.it/web/fileadmin/user_upload/cdl/et4/doc/propedeuticitaET4_sett2023.pdf

The full 12 credit course program is as follows:

a) STATISTICS 1
1. Introduction to statistical methodology.
2. Descriptive statistics in order to be able to interpret the main economic phenomena related to the functioning of markets and businesses through the application of statistical tools: classification and data collection; in order to summarize the data related to economic phenomena: frequency distributions, statistical indices.
3. Probability theory and random variables as an introduction to statistical inference: basic concepts, conditional probability and stochastic independence, Bayes theorem, common probability distributions.

b) STATISTICS 2
4. Statistical inference to critically evaluate the different scenarios in the economic decision-making context and in the management of uncertainty: point and interval estimation; hypothesis testing.
5. Relationship among variables: association and test of independence

Cicchitelli G, D'Urso P, Minozzo M (2021)
Statistics. Principles and Methods.
Pearson
(chapters 1-2-3-4-5-7-12-13-14-15-16-17-18-19-20-21-22)

The final exam consists of two written tests, each lasting one hour and structured in the same way.
Each test involves solving exercises covering the topics explained in the syllabus and is divided into two parts, as follows:

- A first section with 6 multiple-choice questions on specific topics from the syllabus,
both theoretical and practical, to verify that the student has acquired the concepts presented during classes
and included in the syllabus (for a maximum of 15 total points).
- A second section with two exercises structured in multiple questions both theoretical and practical (for a maximum of 10 points per exercise).
The student must be able to justify the methods used to solve the exercises.

In the first written test (graded out of thirty), the exercises aim to verify the ability
to understand and/or use descriptive statistics tools as well as probability calculus problems presented during the course.

In the second written test (graded out of thirty), the exercises aim to verify the ability
to solve data analysis problems using the inferential statistics tools presented during the course.

Exercises similar to those proposed in the final exam are available on the e-learning platform.

The two written tests are taken on the same day in succession, except for the first session,
which can be divided into two partial tests (the first at the end of the first period's classes,
the second during the first call).

The final grade is calculated as the arithmetic mean of the two grades.

- To pass the exam, the student must demonstrate the ability to correctly answer more
than half of the multiple-choice questions and be capable of solving the exercises for at least half of their respective points.
- To achieve the maximum grade, the student must demonstrate the ability to accurately solve all the exercises and
correctly answer all the multiple-choice questions.
- An intermediate grade is attributed in proportion to the number of correct answers and without serious mistakes.

written

A. grades between 18 and 20 are assigned if the student is able to correctly answer at least half of the multiple-choice questions and to solve the exercises for at least half of their respective points, showing sufficient knowledge, but with lacks, of the topics covered in the lessons and textbooks, with limited ability to apply statistical techniques.

B. grades between 21 and 26 are assigned if the student is able to correctly answer more than half of the multiple-choice questions and to solve the exercises for more than half of their respective points, the grade is assigned proportionally to the number of correct answers (between 60% and 75%) and without serious errors, showing not always deep knowledge of the topics covered in the lessons and textbooks, with not always correct ability to apply statistical techniques.

C. grades between 27 and 30 are assigned if the student is able to correctly answer almost all multiple-choice questions and to solve the almost all exercises, showing good knowledge of the topics covered in the lessons and textbooks, with appropriate ability to apply statistical techniques.

D. lode is assigned if the student demonstrates the ability to accurately solve all the exercises and correctly answer all the multiple-choice questions, showing perfect knowledge and comprehension of the topics covered in the lessons and textbooks.

The course consists of frontal lessons. Teaching modules are available on the moodle.unive.it e-learning platform.
Practice.

Students are required to register on the e-learning platform (moodle.unive.it). Access information will be provided at the beginning of the course.

Accessibility, Disability and Inclusion
Accommodation and support services for students with disabilities and students with specific learning impairments

Ca' Foscari abides by Italian Law (Law 17/1999; Law 170/2010) regarding support services and accommodation available to students with disabilities. This includes students with mobility, visual, hearing and other disabilities (Law 17/1999), and specific learning impairments (Law 170/2010). If you have a disability or impairment that requires accommodations (i.e., alternate testing, readers, note takers or interpreters) please contact the Disability and Accessibility Offices in Student Services: disabilita@unive.it.