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# Empirical Methods and Applications in Business

2019/2020
Учебный год
ENG
Обучение ведется на английском языке
3
Кредиты
Статус:
Курс по выбору
Когда читается:
2-й курс, 2 модуль

#### Преподаватели

Александрова Екатерина Александровна

### Course Syllabus

#### Abstract

This course introduces students to sources and analytical techniques of data commonly used in management and business studies. A conceptual part of the course is dedicated to the overview of appropriate data sources, indicators and statistical metrics, basic and advanced techniques for data analysis and econometrics Practical approach to learning is based on professional tools for data collection and processing and analysis – Stata and R.

#### Learning Objectives

• to have knowledge of commonly used data sources, their benefits and limitations
• to understand the meaning of various statistical indicators in principle fields of social science
• be able to identify suitable statistical sources for a defined research problem
• be able to run descriptive analysis using Stata and R

#### Expected Learning Outcomes

• to have knowledge of commonly used data sources, their benefits and limitations
• to understand the meaning of various statistical indicators in principle fields of social science
• be able to identify suitable statistical sources for a defined research problem
• be able to run descriptive analysis using Stata and R

#### Course Contents

• Introduction into principles of collecting and using business data
Research in business. Ethics in business research. Research questions and associated techniques. Screening data prior to analysis. Normality, linearity, and homoscedasticity. Data transformations.
• Probability and statistics in advanced data analysis
Exploratory data analysis. Data and sampling distributions. Statistical experiments and significance testing. Experimental and quasi-experimental techniques. Regression and prediction. Correlation vs causation. Endogeneity. Guide to entering, editing, saving, and retrieving large quantities of data using R and Stata.
• Data visualization and reporting
Presenting insights and findings. Written report: research report components, writings, presentation of statistics. Oral presentation: planning, organizing, supporting, visualizing, delivering.

#### Assessment Elements

• Exam
• Control work
• Problem-solving discussions
• Workshops

#### Interim Assessment

• Interim assessment (2 module)
0.1 * Control work + 0.5 * Exam + 0.1 * Problem-solving discussions + 0.15 * Teamwork task + 0.15 * Workshops

#### Recommended Core Bibliography

• Tong, H., Huang, Y. X., & Kumar, T. K. (2011). Developing Econometrics. Hoboken: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=473846