2288 - Probability Theory and Statistics
Course information
- Title
- Probability Theory and Statistics
- Course number
- 2288.22
- Academic year
- 2024-2025
- ECTS
- 7.50
- Level
- Bachelor
- Faculties
- History and Social Sciences
- Educations
- BSc in Economics and Management
- Prerequisites
- Pass grade in Mathematics B at the upper secondary level. Skills and knowledge from or equivalent to those taught in the courses Mathematics 1 and Mathematics 2 is an advantage.
- Language of instruction
- Faroese
- Registration
- Students in a program are automatically enrolled. Students of a single subject, apply through the student affairs office lss@setur.fo
- Beginning date
- Tuesday, January 28, 2025
- End date
- Thursday, May 29, 2025
Academic content
- Purpose
- The aim of the course is to provide students with the basic ideas of probability and statistics required for the study of economics.
- Learning outcomes
- Having successfully completed the course, the student will be able to describe and implement the following: • Tools used in descriptive statistics • Law of Large Numbers and Central Limit Theorem • Statistical concepts - including: o Joint, marginal and conditional probability o Stochastic variables and transformations of stochastic variables o Distributions o Probability function o Density function o Independent variables o Mean and conditional mean o Variance and covariance • Selected probability distributions, including: o Bernoulli, Binomial, Poisson, Multinomial, geometric, uniform, normal, chi2, and exponential distributions. • Important statistical concepts, including: o Independent, identically distributed variables o Consistency and asymptotic normality o Confidence intervals and hypothesis tests
- Content
- The first part of the course is an introduction to probability theory. The topics include probability, stochastic variables, probability distributions and transformations of stochastic variables. The students learn how to describe stochastic variables by their distributions. The students see examples of various probability distributions (discrete and continuous), and how one can describe these distributions with measures such as mean and variance. The second part of the course is an introduction to statistical analysis of data and inference. This includes choice of model to fit the data, estimating parameters in the model, testing hypotheses and drawing conclusions about the model assumptions.
- Learning and teaching approaches
- New material is presented in lectures and classes. In classes, students solve and present exercises.
Assessment
- Assessment method
- 3 hour written exam. Students may use textbooks, notes and data programs during the exam. They may not use the internet. Students are required to pass a minimum of two assignments in order to attend the exam.
- Examination (internal/external)
- External
- Grading scale
- 7-scale
- Exam date/dates
- Week 23
- Deadline for withdrawal from exam
- Tuesday, January 28, 2025
Academic responsibility and teachers
- Academic responsibility
- Herit Vivi Bentsdóttir Albinus
- Teachers
- Sjúrður Zachariasson