Quantitative Methods of Business Research

Quantitative Methods of Business Research 

 

Instructor:

Iya Y. Churakova, Cand.Sc., Senior Lecturer, Department of Operations Management, Graduate School of Management, St.Petersburg University
Margarita A. Gladkova, Cand.Sc., Assistant Professor, Department of Operations Management, Graduate School of Management, St.Petersburg University

Fattakhova M.V., Ca.of Applied Sciences, Associate Professor, St.Petersburg State University of Aerospace Instrumentation 

Workload:

5,0 ECTS

30 contact hours

Prerequisites:

Introduction to business: statistics

Goals and objectives:

The course is based on the basic statistical tools. It introduces students to the widely used modern research methods of statistical and econometric data in solving economic and managerial tasks.
The course includes topics such as random variables and a system of random variables, sampling distributions, confidence intervals and hypothesis testing, as well as key elements of the regression analysis, including simple and multiple linear regression, time series analysis and forecasting, instrumental variables, the analysis of panel data and regression with binary dependent variables. Exercises on computer using MS Excel, R, or STATA are an important part of the course, ensuring that
students receive practical skills of data analysis in solving economic and managerial tasks.
It is expected that at the end of the course students will be able to:
• to choose the data for quantitative research in accordance with the objectives of the study, as well as to choose for analysis statistical and econometric tools, corresponding to the study features;
• formulate statistical hypotheses on the basis of substantive research assumptions and test them using specific criteria;
• understand and be able to apply the method of simple and multiple linear regression models, to test various model specifications, evaluate and interpret a regression to make predictions for a given value of the independent variables;
• understand the specific time series analysis, guided in its basic concepts and models;

• navigate in the models based on panel data and discrete choice models, as well as an understanding of their use in quantitative analysis for business and management. 

Course Content:

Topic 1. Application of Statistics and Econometrics in business studies
Topic 2. Random variables, the system of random variables and special distribution
Topic 3. Sampling method and estimation the parameters of samples distribution.
Building confidence intervals
Topic 4. Hypothesis testing
Topic 5. Simple linear regression
Topic 6. Multiple linear regression
Topic 7. Time series analysis and forecasting
Topic 8. Transformation of variables, selection of functional dependencies
Topic 9. Categorical independent variables, interaction variables
Topic 10. Regression with a binary dependent variable (binary choice model)
Topic 11. endogenous regressors and the method of instrumental variables

Topic 12. Introduction to panel data analysis 

Teaching Methods:

Lectures are held in classrooms equipped with projectors and document-cameras.

Students receive guidance for out of class work. 

Course Reading:

1. Stock, James H. and Mark W. Watson (2007) Introduction to Econometrics. Second Edition. Pearson Education, Inc. ISBN: 0321442539.
2. Venables, William N. and David M. Smith (2009). An Introduction to R. Network Theory Ltd. ISBN:0954612086.
3. Levine, David M., David F. Stephan, Timothy C. Krehbiel, and Mark L. Berenson (2011) Statistics for Managers Using Microsoft Excel. Sixth Edition. Pearson Education, Inc. ISBN: 0136113494 (referred in the text below as LSKB). 
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