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Fundamentals of mathematical statistics and probability theory

ОК 02

Обов’язкова дисципліна для ОП

First

2021/2022

1 Semester

4

P05. Collect, process and analyze information in the field of geographical sciences for cross-border needs, national, regional and local complex ecological projects P06. Use informative technologies, cartographic and geoinformation models in the study landscape structure of the territory, execution of complex ecological projects P08. Apply models, methods physics, geochemistry, geology, ecology, mathematics, information technologies etc. when studying natural and social processes of formation and development of landscapes and their components. P11. To adhere to moral and ethical aspects of research, honesty, professional code of conduct.

Full-time form

There are no prerequisites for mastering or choosing an academic discipline.

Educational discipline "Fundamentals of mathematical statistics and probability theory" belongs to the mandatory components of the educational program of training specialists in education at the "bachelor" level of the field of knowledge 10 - Natural sciences with a specialty 106 - Geography educational program "Cross-border ecological cooperation". The discipline "Fundamentals of mathematical statistics and the theory of probabilities" studies theoretical and probabilistic and statistical methods of collecting, systematizing and processing the results of observations with a goal detection of statistical regularities of a feature or features of a certain set of elements and covers the following range of questions: fundamentals of combinatorics, random events and random values, sampling and its characteristics, as well as paired linear regression. It is taught in the 1st semester of the 1st course in the amount of 120 hours. (4 ECTS credits) in particular: lectures – 28 hours, practical - 28 hours, independent work - 64 hours. The course includes 2 contents modules and 2 modular test papers. The discipline ends with a test.

1. O. Chernova, F. Lavancier and P. Rochet. Averaging of density kernel estimators, Statistics and Probability Letters, 2020, Vol. 158. DOI: https://doi.org/10.1016/j.spl.2019.108645 2. O. Chernova and A. Kukush. Testing linear and nonlinear hypotheses in a Cox proportional hazards model with errors in covariates. Lithuanian Journal of Statistics, 2019, 58, N1, 39-47. DOI: https://doi.org/10.15388/LJS.2019.16669 3. Жерновий Ю.В. Збірник задач з теорії ймовірностей та математичної статистики для студентів нематематичних спеціальностей. Львів, 2009. – 18 с. 4. Жерновий Ю.В. Теорія ймовірностей та математична статистика: тексти лекцій для студентів нематематичних спеціальностей. Львів, 2008. – 101 с. 5. Турчин В.М. Теорія ймовірностей і математична статистика. Основні поняття, приклади, задачі. – Дніпропетровськ, Видавництво ДНУ, 2006. – 475 с. 6. Практикум з теорії ймовірностей та математичної статистики: навчальний посібник / за ред. Р. К. Чорнея. Київ: МАУП, 2003. – 328 с.

lecture, practical session, independent work

active work at lectures, modular control work, assessment, solving problems on practical classes, performance of tasks independent work, modular control work,

Ukrainian