Master
2024/2025
Introduction to Business Statistics Using R
Type:
Elective course (Data Analytics for Business and Economics)
Area of studies:
Economics
Delivered by:
Department of Economics
When:
1 year, 1 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Dmitry Kislitsyn
Master’s programme:
Data Analytics for Business and Economics
Language:
English
ECTS credits:
3
Course Syllabus
Abstract
Statistical processing of data and visualisation of the results of analysis is an inevitable stage of working with data obtained in various fields of natural sciences, sociology, psychology or economics. In this course we will go through the basics of statistics and learn the basics of the statistical programming language R. We will teach you how to use visualisation tools (charts, graphs, etc.) flexibly to make the results of analysis as accessible and understandable as possible. You will learn how to calculate basic descriptive statistics: median and quantiles, mean and standard deviation. You will be introduced to the principles of using theoretical distributions of statistics to construct confidence intervals and test hypotheses (using the t-criterion as an example). Finally, we will discuss the difficulties encountered in multiple hypothesis testing and teach you how to overcome them.
Expected Learning Outcomes
- understand and apply basic statistical concepts relevant to business
- utilize R for data manipulation, analysis, and visualization
- interpret statistical outputs and communicate findings effectively
- conduct hypothesis testing and regression analysis
- make data-driven decisions based on statistical evidence
Course Contents
- 1. Origins of Data
- 2. Preparing Data for Analysis
- 3. Exploratory Data Analysis
- 4. Comparison and Correlation
- 5. Generalizing from Data
- 6. Testing Hypotheses
- 7. Simple Regression
- 8. Complicated Patterns and Messy Data
- 9. Generalizing Results of a Regression
- 10. Multiple Linear Regression
- 11. Modeling Probabilities
- 12. Regression with Time Series Data
Bibliography
Recommended Core Bibliography
- Fraser C. Business statistics for competitive advantage with Excel 2016: basics, model building, simulation and cases. New York, NY: Springer Science+Business Media, 2016. 475 с.
Recommended Additional Bibliography
- Groebner, David, et al. Business Statistics, EBook, Global Edition, Pearson Education, Limited, 2018. ProQuest Ebook Central, https://ebookcentral.proquest.com/lib/hselibrary-ebooks/detail.action?docID=5186156.