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: Statistical inference

  Sample and population; sampling distribution of the mean; 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; anova; extension of linear regression. LAB: R tutorial on linear regression with real case studies.

• Part 3: Classification

  Logistic regression, linear discriminant analysis, some notions on generalized linear models. LAB: R tutorial on classification techniques applied to real case studies.

Readings/Bibliography

• Statistical Methods for the Social Sciences, Global Edition, 5/E. Agresti (2017).
• 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

The exam aims at evaluating students' understanding of the all topics included in the syllabus; it will be evaluated the ability to:

- produce statistical analysis (e.g. descriptive statistics, tests and model fitting);

- interpret the output of the analysis (including the output produced by the software R).

Exam is a quiz on EOL/Zoom. There will be questions on all the topics included in the syllabus; some questions are multiple choice while others require to enter a number (the use of software R is required to answer the questions requiring a number).

Teaching tools

Software: R (http://www.r-project.org/) e RStudio (https://rstudio.com/).

Office hours

See the website of Massimo Ventrucci