The course is an introduction to probability and statistics. The topics covered include descriptive statistics, probability and inferential statistics. The aim of the course is to introduce the notions, methods an the necassary theoretical background related to data analysis and probability with applications in engineering.
Probability and Statistics (GAINBAN-VALOSTAT-1)
Basic data
Name and type of the study programme
Computer Science Engineering, undergraduate program
Curriculum
2022
Classes / consultation hours
2 + 2 + 0 (L+S+Labs)
Credits
5 credits
Theory – Practice
Theory: 50%, Practice: 50%
Recommended semester
Semester 3
Study mode
full-time
Prerequisites
Calculus I
Evaluation type
Mid-term evaluation
Course category
Compulsory
Language
English
Instructors
Responsible instructor
Osztényiné dr. Krauczi Éva
Responsible department
Department of Basic Sciences
Instructor(s)
Kelecsényi Klára
Checked by
Kovács Márk
Course objectives
Course content
Lectures
1. Descriptive statistics: measures of location 2. Descriptive statistics: variability and shape 3. Mathematical model of random experiments, relative frequency, events and probability, Kolmogorov axioms 4. Classical probability model 5. Conditional probability, independence 6. Discrete random variables, expected value and variance 7. Binomial, Hypergeometric and Poisson distribution 8. Continuous random variables, expected value and variance 9. Uniform, Exponential and Normal Distribution, De Moivre-Laplace theorem, Central limit theorem 10. Sampling distributions, point and interval estimation 11. Hypothesis testing 12. Analysing bivariate data: Khi-square test for independence 13. Analysing bivariate data: correlation, regression
Seminars
1. Descriptive statistics: measures of location 2. Descriptive statistics: variability and shape 3. Mathematical model of random experiments, relative frequency, events and probability, Kolmogorov axioms 4. Classical probability model 5. Conditional probability, independence 6. Discrete random variables, expected value and variance 7. Binomial, Hypergeometric and Poisson distribution 8. Continuous random variables, expected value and variance 9. Uniform, Exponential and Normal Distribution, De Moivre-Laplace theorem, Central limit theorem 10. Sampling distributions, point and interval estimation 11. Hypothesis testing 12. Analysing bivariate data: Khi-square test for independence 13. Analysing bivariate data: correlation, regression
Acquired competences
Knowledge
Knowledge of the principles and methods of natural sciences (mathematics, physics, other natural sciences) relevant to the field of IT.
Skills
They develop the ability to analyze, interpret, and critically evaluate data in various contexts and use it for decision making. Have a sense of the meaning of variability in data and randomness.
Attitude
He/she makes an effort to work efficiently and to high standards.
Autonomy and responsibilities
Through group work, students learn to collaborate effectively, take initiative in problem-solving, and share responsibility in developing creative and practical solutions for probability problems.
Additional professional competences
Efficient use of digital technology, knowledge of digital solutions to fulfill educational objectives
Requirements, evaluation and grading
Mid-term study requirements
Four midterm tests (4*25 points).
Generative AI usage
Use of GAI tools is not permitted for solving assignments. This means GAI tools cannot be used to complete formative or summative assessments, and using GAI constitutes academic misconduct. The use of AI tools for spelling and grammar checking does not fall under this prohibition.
Study aids, laboratory background
Materials uploaded to TEAMS.
Readings
Compulsory readings
Authors: Barbara Illowsky, Susan Dean Publisher/website: OpenStax Book title: Introductory Statistics 2e Publication date: Dec 13, 2023 Location: Houston, Texas Book URL: https://openstax.org/books/introductory-statistics-2e
Recommended readings
Authors: Barbara Illowsky, Susan Dean Publisher/website: OpenStax Book title: Introductory Statistics 2e Publication date: Dec 13, 2023 Location: Houston, Texas Book URL: https://openstax.org/books/introductory-statistics-2e