Master
2021/2022
Statistical Methods of Analysis
Type:
Compulsory course (Management and Analytics for Business)
Area of studies:
Management
Delivered by:
Department of Management
When:
1 year, 2, 3 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Evgeny A. Antipov,
Elena B. Pokryshevskaya
Master’s programme:
Management and Analytics for Business
Language:
English
ECTS credits:
6
Contact hours:
48
Course Syllabus
Abstract
The course covers a wide range of statistical methods and some important machine learning techniques used in today’s business analytics for exploratory and segmentation analysis, as well as for the estimation of relationships and predictive modeling. Students will get ready for data management and the analysis of survey, sales and other types of data commonly used in marketing and management. Students will learn how to use the R language – the most popular language for statistical computing, modeling and data management thanks to the fact that 50% of the course is dedicated to hands-on R coding.
Learning Objectives
- Choose methods adequately corresponding to the objectives of a research project
- Collect, store, process and analyze data according to high standards
- Conduct empirical research in management and marketing using modern analytic software tools
- Develop and apply new research methods
- Solve economic and managerial problems using best practices of data analysis using modern computational tools
Expected Learning Outcomes
- Solve economic and managerial problems using best practices of data analysis using modern computational tools
- Develop and apply new research methods
Course Contents
- Identifying Drivers of Outcomes: Linear Models
- Additional Linear Model Topics (Collinearity, Logistic, Hierarchical Linear Models (HLM))
- Confirmatory Factor Analysis and Structural Equation Modeling (SEM)
- Segmentation: Clustering and Classification
- Choice Modeling (Choice-based conjoint analysis)
- Association Rules for Market Basket Analysis
- Reducing Data Complexity (Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA))
Assessment Elements
- In-class Activity
- Midterm Exam
- ExamThe exam is conducted in written form. There will be not less than 60 minutes and not more than 90 minutes. to answer the questions. The exam is conducted on the platform (insert the platform name and link). You need to connect to the exam at the time mentioned in the schedule The student's computer must meet the requirements: R and R studio installed, access to LMS lms.hse.ru A short-term communication failure during the exam is considered less than 5 minutes. In case of any failure, the student should contact the lecturer vie email eantipov@hse.ru or using MS Teams chat with a screenshot of the problem. In case of such a problem the test can be retaken only of the student has contacted the lecturer in no more than 90 minutes from the start of the exam.
- Kahoot tests
Interim Assessment
- 2021/2022 3rd module0.25 * Exam + 0.25 * In-class Activity + 0.25 * Midterm Exam + 0.25 * Kahoot tests
Bibliography
Recommended Core Bibliography
- Chapman, C., & Feit, E. M. (2015). R for Marketing Research and Analytics. Cham: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=964737
Recommended Additional Bibliography
- Bolstad, W. M. (2017). Introduction to Bayesian Statistics (Vol. Third edition). Hoboken, N.J.: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1342637