Bachelor
2021/2022
Statistical Methods for Market Research
Type:
Elective course
Area of studies:
Applied Mathematics and Information Science
Delivered by:
Big Data and Information Retrieval School
Where:
Faculty of Computer Science
When:
4 year, 1-3 module
Mode of studies:
offline
Open to:
students of one campus
Language:
English
ECTS credits:
7
Contact hours:
104
Course Syllabus
Abstract
This course concentrates on transforming students into competent and confident users of statistical software to enable them to conduct independent data analysis by taking a more applied approach to conventional statistics. The first half of the course focuses on aspects of market research, and in the second half the emphasis is on the practical application of a variety of multivariate statistical techniques to supplied datasets.
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.
Interim Assessment
- 2021/2022 3rd module0.5 * Final exam + 0.3 * Midterm exam + 0.2 * Home Assignments
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