Статистический анализ нечисловой информации

Бакалавриат 2025/2026

ID 958156

Статус: Курс обязательный (Экономика и статистика)

Кто читает: Департамент статистики и анализа данных

Где читается: Факультет экономических наук

Когда читается: 2-й курс, 3 модуль

Охват аудитории: для своего кампуса

Преподаватели: Астафьева Екатерина Викторовна

Язык: русский

Кредиты: 4

Контактные часы: 40

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Аннотация

Categorial Data Analysis is a course for the second year bachelor’s programme students who selected specialization Economics and Statistics. The course covers methods for analyzing qualitative variables, that often receive little attention in the traditional statistics curriculum, but play an important role in statistical practice due to the ubiquity of categorical data, especially in the social sciences. The course consists of two parts, including traditional (non modes) methods for analyzing the relationship between categorical variables and loglinear models. The first section provides basic terminology and notation; describes methods for testing the hypothesis of the independence of two categorical variables, including follow-up components extracting that improve the description of the relationship; covers different measures of association and their probabilistic interpretation. The second section considers loglinear models that allow to characterize the nature of the relationship between variables, determine how the expected cell frequencies of the contingency table depend on the levels of categorical variables and on the interactions between them. The course materials assume that students are familiar with the basic concepts and methods of Calculus, Probability Theory and Mathematical Statistics courses from the 1st and 2nd years of the bachelor’s programme

Цель освоения дисциплины

To provide students with a scientific understanding of statistical methods for studying random phenomena in economics
To introduce methods for the quantitative analysis of categorical and other non-numerical statistical data
To develop students' ability to formulate statistical hypotheses and to interpret the results of statistical analyses in a meaningful way
To foster probabilistic and statistical thinking that is essential for successful research and analytical work in modern socio-economic and management-related fields

Планируемые результаты обучения

Знать основные принципы работы с нечисловой информацией
Уметь проверять независимость, знать основные меры связи и строить логарифмически-линейные модели для нечисловой информации (категориальных признаков)