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Regular version of the site
Bachelor 2023/2024

Statistical Methods for Market Research

Type: Compulsory course (Data Science and Business Analytics)
Area of studies: Applied Mathematics and Information Science
When: 4 year, 2, 3 module
Mode of studies: offline
Open to: students of one campus
Instructors: Ksenia Kasianova
Language: English
ECTS credits: 5
Contact hours: 68

Course Syllabus

Abstract

In this course, we understand market analysis as a set of various probabilistic, statistical, econometric and stochastic methods that help to solve real applied problems. Classical approaches of data analysis do not always work properly in reality. There is a need to explore other methods (often more complex and advanced). We introduce some of such tools which can be applied in practice and, in our humble opinion, are extremely important and useful.
Learning Objectives

Learning Objectives

  • To learn how various advanced probabilistic, statistical, econometric and stochastic techniques can be applied to the real business problems
Expected Learning Outcomes

Expected Learning Outcomes

  • Students will gain ample knowledge of Bootstrap, Welch test, Mann-Whitney test, CUPED, The difference in Difference estimator, Matching, Multiple comparison.
  • Students will gain ample knowledge of Discriminant analysis, LOGIT, PCA, Factor analysis, Cluster analysis, Dendrogramms, Conjoint Analysis and Multidimensional scaling.
  • Students will gain ample knowledge of Sampling, Sample size calculation, Contingency tables, Chi-squared tests, ANOVA, ANCOVA and Partial correlation.
  • a student can perform an A/B test
  • a student can apply a difference-indifference approach
  • a student can apply bootstrap techniques
  • a student can work with logistic regressions (simple, ordered and multinomial)
  • a student can apply non-parametric techniques
  • a student can apply stochastic methods
  • a student can conduct an A/B test
Course Contents

Course Contents

  • A/B testing
Assessment Elements

Assessment Elements

  • non-blocking Homework
  • non-blocking Exam 1
  • non-blocking Exam 2
  • non-blocking Bonus activities
Interim Assessment

Interim Assessment

  • 2023/2024 2nd module
    Fall Grade = 0.4*Homework + 0.6*Exam 1 + 0.1*Bonus activities
  • 2023/2024 3rd module
    Final Grade = 0.5*Fall Grade + 0.2*Homework + 0.3*Exam 2 + 0.1*Bonus activities
Bibliography

Bibliography

Recommended Core Bibliography

  • Malhotra, N. K. (2017). Marketing Research. [N.p.]: Pearson. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1531280

Recommended Additional Bibliography

  • Newbold, P., Carlson, W. L., & Thorne, B. (2013). Statistics for Business and Economics: Global Edition (Vol. Eight edition). Boston, Massachusetts: Pearson Education. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1417883

Authors

  • Абдулхакимов Мухиддин Мураджанович
  • Стоякина Елена Игоревна