QUANTITATIVE TOOLS FOR MARKETING

Academic year
2021/2022 Syllabus of previous years
Official course title
QUANTITATIVE TOOLS FOR MARKETING
Course code
EM7023 (AF:358047 AR:189504)
Modality
On campus classes
ECTS credits
6
Degree level
Master's Degree Programme (DM270)
Educational sector code
SECS-S/03
Period
1st Term
Course year
1
Where
VENEZIA
Moodle
Go to Moodle page
The course is one of those characterizing the Degree Innovation and Marketing.
The objective is to introduce students to some statistical techniques for marketing research, conceived as a tool to support the decision making process. The course will concentrate on regression, classification and positioning techniques giving attention to some practical examples and introducing the student to the use of R.
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 using R
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 Analyse data adopting the correct statistical procedure using R
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 implication
Students are assumed to be able to apply their knowledge and understanding about the concepts and methods concerning descriptive and inferential statistics.
The following topics will be covered both from a theretical perspective and using R:

1. Data collection
2. Multivariate regression analysis and classification techniques
3. Principal components analysis and Cluster Analysis
4. Applications

Excercises from the Datacamp learning platform will be proposed.
Slides and other provided during lectures. Textbook:

An Introduction to Statistical Learning: With Applications in R, di Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
The exam consists of a preparation and a presentation of a project on a a dataset.
The exam aims to verify that the student has acquired the concepts presented during the lessons, is familiar with the software and has learned how to integrate this knowledge and skills to solve business problems. The critical and personal ability to carry out the analysis will be evaluated.
Lectures, exercises and tutorials.
English
1. Students should register in the related course web page of the university e-learning platform moodle.unive.it

2. Accessibility, Disability and Inclusion
Accommodation and support services for students with disabilities and students with specific learning impairments
Ca’ Foscari abides by Italian Law (Law 17/1999; Law 170/2010) regarding support
services and accommodation available to students with disabilities. This includes students with
mobility, visual, hearing and other disabilities (Law 17/1999), and specific learning impairments (Law 170/2010). If you have a disability or impairment that requires accommodations (i.e., alternate testing, readers, note takers or interpreters) please contact the Disability and Accessibility Offices in Student Services: disabilita@unive.it.
written
Definitive programme.
Last update of the programme: 19/06/2021