Marketing Models: Principles and Applications Using R

Seminar

Instructor: Prof. Hernán Bruno, Ph.D.
Date, Time & Room: see KLIPS

Content

This course provides a general foundation for thinking about marketing in terms of empirical models of marketing data.
Models are representations of a system. In marketing, we develop sales models to explain and predict a customer response in terms of price, advertising and other marketing and environmental variables. Sometimes we model customer decisions or the evolution of a customer relationship. Other times, we need to summarise and make inferences from survey data.
Part of developing empirical models with is to understand and manipulating data. We will use the statistical programming environ R, which offers a wide range of tools for modelling and visualization. No previous knowledge of R is required. The set up and the foundational ideas will be imparted in the course, but the students are expected to make progress on their own like the rest of us: by trial and error and looking up information online.
Part of the course will be “hands on”. That means that students are recommended to bring their personal laptops to class and we go through code together. Occassionally there will be slides and derivations on the board.

Objectives

The students that successfully completes this course should be able:
•    To feel comfortable with the R language 
•    To use R to manipulate and process datasets conveniently and efficiently
•    To write reproducible code in social science research
•    To model marketing phenomena using statistical models
•    To translate questions to models that can be applied to real data to make marketing decisions.
•    To develop a rigorous way of thinking
•    To develop compelling visualizations of data and model outputs
•    To never use SPSS again and to help others never to SPSS again