Master
2021/2022
Basics of econometrics
Type:
Bridging course (Strategic Management in Logistics)
Area of studies:
Management
Delivered by:
Department of Management
When:
1 year, 1 module
Mode of studies:
offline
Open to:
students of all HSE University campuses
Master’s programme:
Strategic Management in Logistics
Language:
English
ECTS credits:
3
Contact hours:
24
Course Syllabus
Abstract
The course introduces students to basic statistical methods for exploratory analysis and the analysis of relationships. Students will get ready for data management and for basic comparative, correlation and regression analysis of survey, sales and other types of data commonly used in marketing and management. Students will get intermediate R statistical computing skills necessary for more advanced courses. 50% of the course is dedicated to hands-on R coding, which is why the course will be useful even for students who studied Econometrics using another package but want to master the popular and powerful R package. In addition, being tailored to management students, this course does not duplicate traditional Econometrics courses for economists in terms of empirical examples used in it.
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
- Explore new data to extract actionable insights
- Model relationships between outcomes and their drivers
- Produce dynamic reproducible research reports with publication-quality tables and graphics
Expected Learning Outcomes
- Solve economic and managerial problems using best practices of data analysis using modern computational tools
- Choose methods adequately corresponding to the objectives of a research project
- Collect, store, process and analyze data according to high standards
- Ability to import and preprocess data to statistical software
- Conduct descriptive analysis of data
- Explore and test relationships between various features
- Explore differences among subgroups of data
- Identify drivers of outcomes
- Test differences among groups of data
Course Contents
- Introduction. Review of basic probability and statistics concepts.
- Introduction to the R Language
- Describing Data
- Relationships between Continuous Variables
- Comparing Groups: Tables and Visualizations
- Comparing Groups: Statistical Tests
- Identifying Drivers of Outcomes: Linear Models. Regression diagnostics.
Interim Assessment
- 2021/2022 1st moduleThe final grade is the simple average of 4 components. As each component is evaluated on the 100-point scale (without rounding to the nearest integer), the final grade is first obtained as a continuous number on a 100-point scale (not rounded to integers) and then converted to the 10-point according to the rules for converting the 100-point scale final grade to the 10-point scale: [95,100)=10 [90,95)=9, [80,90)=8, [70,80)=7, [60,70)=6, [50,60)=5, [40,50)=4, [30,40)=3, [20,30)=2, [10,20)=1, [0,10)=0
Bibliography
Recommended Core Bibliography
- Chapman, C., & Feit, E. M. (2019). R For Marketing Research and Analytics (Vol. Second edition). Cham: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2093001
- Hamid Seddighi. (2012). Introductory Econometrics : A Practical Approach. Routledge.
Recommended Additional Bibliography
- Greenberg, E. (2013). Introduction to Bayesian Econometrics: Vol. 2nd ed. Cambridge eText.