Course: Marketing Research and Data Analysis

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Course title Marketing Research and Data Analysis
Course code KMG/MVA
Organizational form of instruction Lecture + Seminary
Level of course Master
Year of study not specified
Semester Summer
Number of ECTS credits 5
Language of instruction Czech
Status of course Compulsory, Compulsory-optional
Form of instruction Face-to-face
Work placements Course does not contain work placement
Recommended optional programme components None
Lecturer(s)
  • Dědková Jaroslava, doc. PhDr. Ing. Ph.D.
  • Červová Lenka, Ing. Ph.D.
  • Burešová Jitka, Ing. Ph.D.
  • Öhm Jan, Ing. Ph.D.
  • Rozkovec Jiří, Mgr.
  • Hovorková Valentová Vladimíra, Ing. Ph.D.
Course content
1. 1. Marketing research, its role, use and importance in marketing management 2. Marketing information system 3. Types of marketing research (primary, secondary, exploratory, descriptive, explanatory and prognostic reseach, longitudinal and ad hoc research, panel research, quantitative and qualitative research. Data sources: primary and secondary, internal and external. 4. Marketing research design, positivistic and phenomenological approach 5. Marketing research process and methodology (problem definition, objectives) 6. Methods of data collection 7. Questionnaire design 8. Types of questions, scales 9. Sampling methods, probability and nonprobability sampling, representatitve sampling, size of sample 10. Research report 11. Basic terms of statistical data analysis, processing of various types of scales with the help of tables, graphs and descriptive statistics. 12. Multivariate answers principles. Missing values and factors influencing work with them. 13. Statistical inference Estimation theory. Sample size determination. 14. Statistical inference Hypotheses testing (parametric tests for independent and paired samples). 15. Statistical inference - Hypotheses testing (non-parametric tests). 16. Exploratory data analysis data samples preparation. 17. Relationship among variables Analysis of variance (One-Way ANOVA, MANOVA), the Chi-Square test for independence, measurement of association, 2x2 tables. 18. Relationship among variables Regression and correlation analysis. The conditions of the classic linear model use. 19. Exploratory factor analysis (latent variables and their identification, factors influencing the correlation matrix, rotation, analysis and interpretation of the factors), confirmatory factor analysis. 20. Cluster analysis (hierarchical clustering, decomposition methods). 21. Other multivariate statistical methods (Discriminant analysis, correspondence analysis, conjoint analysis, multidimensional scaling). 1. Introduction, terms of credits and examination, semestral project assignment 2. Marketing research agencies, research conducted by a marketing research agency 3. Problem definition and objectives of marketing research 4. Secondary data sources, working with primary and secondary data, case study 5. Case study presentation 6. Methods of data collection, working in teams 7. Qualitative research, focus group 8. Sampling 9. Questionnaire design 10. Semestral project presentation . Basics of the program STATGRAPHICS Centurion XVII. Scales categorization examples. 12. Examples of various types of scales treating tables, graphs and descriptive statistics. 13. Multivariate answers analysis. Work with missing values. 14. Statistical estimations. Sample size determination. 15. Hypotheses testing one or two parameters tests. 16. Hypotheses testing non-parametric tests. 17. Data preparation outliers identification, normality tests, shape of data sets, independence of data set units, testing of homoscedasticity). 18. One-way ANOVA and MANOVA. Contingency tables, chi-square test for independence. 19. The 2 by 2 table and testing of the categorical variables independence. Testing of basic assumptions of the classic linear model, linear regression. 20. Non-linear regression. Correlation of answers. 21. Examples of factor and cluster analysis use.

Learning activities and teaching methods
Lecture
Learning outcomes
Prerequisites
unspecified

Assessment methods and criteria
Written exam

Credit: Elaboration of assigned tasks, semester work and its presentation. The elaboration of the semester work includes both parts - marketing research and data analysis. The minimum number of points for credit for the data analysis part is 60 % of points. Exam: written form containing questions from both parts. Maximum number of points: Marketing research 50 points and Data analysis 50 points. To successfully complete the course, students must obtain from both parts min. 30 points. In case of obtaining a lower number of points from one or both parts, the student takes a corrective exam from the part from which he or she failed.
Recommended literature
  • BABIN, B. and W. ZIKMUND. Essentials of Marketing Research. Boston: Cengage Learning, 2015. ISBN 978-1-305-26349-9.
  • HEBÁK, P. et al. Vícerozměrné statistické metody. Praha: Informatorium, 2005. ISBN 978-80-7333-039-3.
  • KOZEL, R., L. MYNÁŘOVÁ a H. SVOBODOVÁ. Moderní metody a techniky marketingového výzkumu.. Praha: Grada Publishing, 2011. ISBN 978-80-247-3527-6.
  • LOHR, S., L. Sampling: Design and Analysis. 2nd ed.. Boston: Brooks/Cole, 2010. ISBN 978-0-495-11084-2.
  • McDANIEL, C. Jr. and R. GATES. Marketing Research Essentials. Hoboken: Wiley, 2016. ISBN 978-1-119-23945-1.
  • PECÁKOVÁ, I. Statistika v terénních průzkumech. 1. vyd.. Professional Publishing. Praha, 2008. ISBN 978-80-86946-74-0.
  • ŘEZANKOVÁ, H. Analýza dat z dotazníkových šetření. 2. vyd. Professional Publishing. Praha, 2010. ISBN 978-80-7431-019-5.
  • STANKOVIČOVÁ, I., VOJTKOVÁ, M. Viacrozmerné štatistické metódy s aplikáciami. Iura Edition. Bratislava, 2007. ISBN 978-80-8078-152-1.
  • TAHAL, R. Základní metody sběru primárních dat marketingového výzkumu. Praha: C. H. Beck, 2015. ISBN 978-80-7400-585-5.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester