STATISTICS - 2
- Academic year
- 2024/2025 Syllabus of previous years
- Official course title
- STATISTICS - 2
- Course code
- ET2022 (AF:450067 AR:256028)
- Modality
- On campus classes
- ECTS credits
- 6 out of 12 of STATISTICS
- Degree level
- Bachelor's Degree Programme
- Educational sector code
- SECS-S/01
- Period
- 2nd Term
- Course year
- 2
- Where
- VENEZIA
- Moodle
- Go to Moodle page
Contribution of the course to the overall degree programme goals
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.
Expected learning outcomes
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
Pre-requirements
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
Contents
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
Referral texts
Statistics. Principles and Methods.
Pearson
(chapters 1-2-3-4-5-7-12-13-14-15-16-17-18-19-20-21-22)
Assessment methods
Each test involves solving exercises covering the topics explained in the syllabus and is divided into two parts, as follows:
- A first section with 5 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 12 total points).
- A second section with two exercises structured in multiple questions (for a maximum of 11 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.
Teaching methods
Practice.
Teaching language
Further information
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.