STATISTICS FOR MARKETING

1. Knowledge and understanding: The course provides advanced concepts in statistics for marketing These tools will be then applied for analysing case studies based on real data in marketing.
2. Applying knowledge and understanding: The student has to be able to perform statistical analyses of multivarite data, using different statistical tools through the R language.
3. Making judgements: The student has to be able to manage statistical tools for marketing data analysis and draw suitable conclusions.
4. Communication skills: The student is expected to learn the technical language needed to understand/write properly a statistical report in the marketing area.
5. Learning skills: Ability to understand the logic of the statistical reasoning

Preliminaries. Statistical surveys. Questionnaire design. Data matrices. Summary statistics for multivariate data. The R Statistical software

Statistical surveys. Sampling techniques from finite populations. Survey sample methods (probability and non probability methods). Required sample size.

Analysis of multidimensional data. Distances, similarities and dissimilarities. Cluster analysis: hierarchical and non-hierarchical methods. Market and consumer segmentation. Factor Analysis.

Linear Regression Models. Simple and multiple regression models. Least squared estimation. Criteria of model fitting. Residual analysis. Inference on the parameters of regression models.

1. Hair J.F., Black W.C., Babin B.J., Anderson R.E., Multivariate Data Analysis, Pearson, Upper Saddle River, 2010
2. Fowler F.J., Survey Research Methods, Thousand Oaks, Sage, 2009
3. Falissard B., Analysis of Questionnaire Data with R, CRC Press, Boca Raton, 2012