75976 - BUSINESS DATA ANALYSIS

Anno Accademico 2020/2021

  • Docente: Silvia Emili
  • Crediti formativi: 6
  • SSD: SECS-S/03
  • Lingua di insegnamento: Inglese
  • Modalità didattica: Convenzionale - Lezioni in presenza
  • Campus: Rimini
  • Corso: Laurea Magistrale in Amministrazione e gestione d'impresa (cod. 8842)

Conoscenze e abilità da conseguire

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.

Contenuti

  • 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;

    Testi/Bibliografia

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

    Metodi didattici

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

    Modalità di verifica e valutazione dell'apprendimento

    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.

    Strumenti a supporto della didattica

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

    Orario di ricevimento

    Consulta il sito web di Silvia Emili