Bachelor
2020/2021
Statistics with R Specialization
Type:
Elective course (Fundamental and Computational Linguistics)
Area of studies:
Fundamental and Applied Linguistics
Delivered by:
School of Linguistics
Where:
Faculty of Humanities
When:
4 year, 3 module
Mode of studies:
distance learning
Instructors:
Yury Lander
Language:
English
ECTS credits:
3
Contact hours:
2
Course Syllabus
Abstract
In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis. You will produce a portfolio of data analysis projects from the Specialization that demonstrates mastery of statistical data analysis from exploratory analysis to inference to modeling, suitable for applying for statistical analysis or data scientist positions.
Learning Objectives
- learn to analyze and visualize data in R
- learn to perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions
Course Contents
- Statistics with RIn this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis. You will produce a portfolio of data analysis projects from the Specialization that demonstrates mastery of statistical data analysis from exploratory analysis to inference to modeling, suitable for applying for statistical analysis or data scientist positions.
Assessment Elements
- Online course
- Discussion with a HSE instructor
- Online course
- Discussion with a HSE instructor
Interim Assessment
- Interim assessment (3 module)Рассчет оценки в соответствии с баллами, набранными на онлайн-платформе: 95-100 %: 10; 85-94 %: 9; 75-84 %: 8; 65-74 %: 7; 55-64 %: 6; 45-54 %: 5; 35-44 %: 4; 25-34 %: 3; 15-24 %: 2; 5-14 %: 1; < 4 %: 0;
Bibliography
Recommended Core Bibliography
- Мастицкий С.Э., Шитиков В.К. - Статистический анализ и визуализация данных с помощью R - Издательство "ДМК Пресс" - 2015 - 496с. - ISBN: 978-5-97060-301-7 - Текст электронный // ЭБС ЛАНЬ - URL: https://e.lanbook.com/book/73072
Recommended Additional Bibliography
- Джеймс Г., Уиттон Д., Хасти Т. - Введение в статистическое обучение с примерами на языке R - Издательство "ДМК Пресс" - 2017 - 456с. - ISBN: 978-5-97060-495-3 - Текст электронный // ЭБС ЛАНЬ - URL: https://e.lanbook.com/book/93580