Bachelor
2024/2025
Statistical Methods for Market Research
Type:
Compulsory course (Data Science and Business Analytics)
Area of studies:
Applied Mathematics and Information Science
Delivered by:
Big Data and Information Retrieval School
Where:
Faculty of Computer Science
When:
4 year, 2, 3 module
Mode of studies:
offline
Open to:
students of one campus
Language:
English
ECTS credits:
4
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
- To learn how various advanced probabilistic, statistical, econometric and stochastic techniques can be applied to the real business problems
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
- A/B testing
- difference-in-difference approach
- bootstrap
- logistic regression (simple, ordered and multinomial)
- non-parametrics
- stochastics (Markov models and extreme value analysis)
Interim Assessment
- 2024/2025 3rd module0.2 * final exam + 0.15 * home assignment 1 + 0.15 * home assignment 2 + 0.25 * midterm 1 + 0.25 * midterm 2
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