75976 - Business Data Analysis

Learning outcomes

This course aims at providing students with the ability to analyze multivariate data most often stemming from questionnaires .The course educates students in the skills needed for a good performance of multivariate analysis and thereby enhance their overall analytical competence. The course focuses on the understanding of each multivariate tools as well as interpretation and use of the results on management, marketing, strategy and innovation decisions.

Course contents

• Part 1: Introduction to descriptive and inferential statistics

  Central tendency and dispersion; frequency tables; sample and population; hypothesis testing and confidence intervals. LAB: R tutorial on data visualization, hypothesis testing and confidence intervals.

• Part 2: Regression

  Simple linear regression; multiple linear regression; least squares estimation; inference for the model coefficient; model checking; extension of linear regression. LAB: R tutorial on linear regression with two real case studies.

1. hedonic regression;
2. production functions;

• Part 3: Clustering

  Distance metrics; clustering algorithms. LAB: R tutorial on classification techniques applied to two real case studies:

1. industrial clusters;
2. tourism questionnaires;

 

Readings/Bibliography

An Introduction to Statistical Learning, with Applications in R. James, Witten, Hastie and Tibshirani (2013)

Teaching methods

Frontal lectures using slides, notes at the board/ipad. Laptop when using R for the applied tutorials.

Assessment methods

Exam is a quiz on EOL/Zoom, including multiple choice, R output to be analysed and questions on all the topics included in the syllabus.

Teaching tools

Softwares: Excel, R (http://www.r-project.org/), RStudio (https://rstudio.com/)

Office hours

See the website of Silvia Emili