DATA ANALYSIS AND DATA VISUALIZATION

The objective is to introduce students to some statistical techniques for marketing research, conceived as a tool to support the decision making process.
In particular, the course will concentrate on market segmentation and positioning techniques also giving attention to some practical examples.

1. KNOWLEDGE AND UNDERSTANDING
1.1 Understand and distinguish the main quantitative approaches to marketing research)
1.2 Know and understand the main procedures to obtain valuable data (in particular surveys)
1.3 Know and understand the main statistical techniques to analyse the data at hand
2. APPLYING KNOWLEDGE AND UNDERSTANDING
2.1 Recognize the type of problem at hand and the data set on which the quantitative analysis is based
2.2 Elaborate questionnaire to obtain data compatible with the type of analysis
2.3 Analyse data adopting the correct statistical procedure
3. MAKING JUDGMENTS
3.1 Given the problem at hand, being able to recognize the most adequate statistical procedure
3.2 Being able to distinguish data sources and quality
3.3 Being able to interpret the statistical results and their implications

Statistics (basics of descriptive statistics and inference).

What is Data Mining?
Data Visualization
Evaluating Classification and Predictive Performance
Near Neighbor and Naive Bayes Methods
Classification and Regression Trees
Regression Review and Selection of Variables
Logistic Regression
Discriminant Analysis
Neural Networks
Cluster Analysis
Bagging and Boosting
Dimension Reduction and Penalty Methods

Shmueli, Bruce, Yahiv, Patel, and Lichtendahl, Data Mining for Business Analytics: Concepts, Techniques, and Applications with R, 1st Edition (2017)
Ch. Balakrishna, B. Santhosh Kumar, S. Sathishkumar, Gopika G S, "Beginning Data Science in R Data Analysis, Visualization, and Modelling: Hands-On Tutorials".

Assessment methods: The final test consists of a written theoretical and practical exam, with open and close (crosses) answers, on the contents developed during the course.

Theoretical lectures alternating with practical examples.

English

English

written