INTRODUCTION TO PROBABILITY FOR ECONOMICS

Academic year
2024/2025 Syllabus of previous years
Official course title
INTRODUCTION TO PROBABILITY FOR ECONOMICS
Course code
LT9029 (AF:513066 AR:289917)
Modality
On campus classes
ECTS credits
6
Degree level
Bachelor's Degree Programme
Educational sector code
SECS-S/01
Period
1st Term
Course year
1
Moodle
Go to Moodle page
This course focuses on data analysis, probability theory, and statistical inference using a concept-driven approach.
It aims to provide undergraduate students with practical concepts widely applied in economics and social sciences. These concepts are essential for professionals and researchers who need to collect and analyze data to make informed decisions or predictions.
The course keeps the technical use of mathematics at a basic level to introduce students to probabilistic reasoning and statistical methods.
The course intends to introduce students to the probabilistic and statistical tools used in analyzing and interpreting empirical evidence in economics and social sciences. The goal is to enable students to effectively interact with researchers and practitioners in these fields.
Students are expected to have a basic knowledge of mathematics at a middle school level.
1. Statistics: scopes and methods. Data description: graphical and numerical summaries. Data collection.
2. Probability, probability distributions, sampling distributions.
3. Statistical inference: point and interval estimation.
4. Statistical inference: testing statistical hypotheses.
Agresti A., Franklin C., and Klingenberg B. (2017): Statistics. The art and science of learning from data. Pearson. Chapters 1-9.
The final assessment consists of a written test followed by an oral interview, provided the written test has been successfully passed. The written test comprises multiple-choice questions. Examples of multiple-choice questions are available on the Ca' Foscari Moodle e-learning platform. Regarding the grading, the exam will be marked on a scale ranging from 0 to 30. The minimum passing grade is 18. Honors ("lode") will be granted only for exceptional capacity of judgment and excellent knowledge of the topics under evaluation.
The course will be presented in a lecture-style format.
English
Students are encouraged to register for the course on the Moodle platform (moodle.unive.it), where they can find supplementary materials.
written and oral
Definitive programme.
Last update of the programme: 04/08/2024