Quantitative Methods of Business Research

 

Instructor:

  • Iya Churakova, Associate Professor, Department of Operations Management, Graduate School of Management, St.Petersburg University

E-mail: churakova@gsom.pu.ru

  • Margarita Gladkova, Assistant Professor, Department of Operations Management, Graduate School of Management, St.Petersburg University

E-mail: gladkova@gsom.pu.ru

Workload:

5 ECTS
30 contact hours

Prerequisites:

Introduction to Business Management: Statistics

Course Description:

Quantitative Methods of Business Research uses basic statistical methods and introduces the students to methods of quantitative analysis useful in their professional business and management activities.
The course topics include hypothesis testing, key elements of regression analysis, time-series analysis and forecasting, instrumental variables, factor analysis, cluster analysis, panel data analysis and regressions with binary dependent variables. Practical sessions using SPSS environment represent an integral part of the course ensuring that the students acquire skills and gain experience of data analysis in solving business and management problems.
After the course, the students should be able to apply the most typical quantitative methods to analyze data, critically assess the validity of statistical data and made conclusions before making business decisions, perform basic statistical and econometric analysis as well as interpret and discuss its results.

Course Content (Topics and subtopics):

Topic 1. Data gathering and analysis.

  • Research process
  • Sampling methods
  • Describing data: metrics, tables, graphs

Topic 2. Hypothesis testing.

  • General procedure
  • One-sample and two-sample tests
  • ANOVA
  • Non-parametric tests

Topic 3. Correlation and regression analysis.

  • Correlation, partial correlation, multiple correlation 
  • Simple linear and multiple regression
  • Mediation and moderation
  • Categorical predictors in regression
  • Logistic regression 

Topic 4. Cluster and factor analysis.

  • Terminology, procedure and applications

Topic 5. Time-series analysis and panel data

  • Time-series components
  • Forecasting
  • Panel data: fixed and random effects models

Course Organization:

1) Lectures and seminars, in-class discussions, group seminar tasks.
2) Seminars will be run in computer class with the use of SPSS software.

Course Reading (the full list):

Core reading:
• Field, Andy (2013). Discovering Statistics using IBM SPSS Statistics 4th edition. SAGE Publications Ltd., ISBN 9781446249179.
• Stock, James H. and Mark W. Watson (2007) Introduction to Econometrics. Second Edition. Pearson Education, Inc. ISBN: 0321442539.

Supplementary reading:
• Klibanoff, Peter, Alvaro Sandroni, Boaz Moselle, and Brett Saraniti (2006) Managerial Statistics: A Case-Based Approach. Mason, OH: Thomson/South-Western. ISBN: 0324314523
• Wooldridge, Jeffrey M. (2009) Introductory Econometrics: A Modern Approach. Fourth Edition. South-Western. ISBN: 0324660405

Exam format:

In-class
Duration: 90 minutes

Grading Policy (% or points):

Course progress – 50 %, exam – 50 %.
Course progress will be evaluated through seminar tasks that students will perform in small groups.

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