Course 2014-2015 a.y.

Obiettivi formativi del corso

Dati e modelli quantitativi caratterizzano sempre di più il moderno processo decisionale. Sapere interpretare e leggere efficacenemente i dati a disposizione di un’impresa e creare modelli appropriati per l’individuazione delle strategie ottimali sono spesso la chiave per una maggiore competitività. Con Business analytics si intendono le competenze, tecnologie e i metodi che consentono di analizzare dati, sia attuali sia relativi alle performance aziendali del passato, al fine di orientare il processo decisionale e la pianificazione. Il corso fornisce un’ampia introduzione alla business analytics, consentendo agli studenti di acquisire familiarità con varie tipologie di problemi e con i metodi quantitativi che sono maggiormente utilizzati nella soluzione di problemi gestionali. Si adotta un approccio orientato alle applicazioni. Un'attenzione specifica è dedicata all'implementazione pratica delle metodologie proposte attraverso pacchetti software di comune utilizzo nella pratica aziendale (Excel).

Programma sintetico del corso

• Il processo di decisione moderno: La Decision Analysis.
• Problemi di Ottimizzazione e La Programmazione Lineare.
• Fonti di dati e revisione di alcuni concetti di base di statistica.
• Regressione lineare con applicazioni al Management.
• Introduzione alla regressione logistica e ai suoi principali impieghi nel Management.
   

Descrizione dettagliata delle modalità d'esame

La prova d’esame è scritta, con svolgimento in aula informatica mediante l’utilizzo del calcolatore. La durata della prova è di 1 ora e 30 minuti, con esercizi su tutto il programma per un totale di 16 domande da due punti ciascuna, per un massimo di 32 punti. Ad ogni domanda possono essere assegnati 0, 1 o 2 punti.

Testi d'esame

• P. KLIBANOFF, A. SANDRONI, B. MOSELLE et al., Statistica per manager, EGEA, 2010
• G.E. MONAHAN, Management Decision Making, Cambridge University Press, 2000
• Note a cura dei docenti

Prerequisiti

Sono richieste competenze di base di statistica e probabilità. Tali temi sono oggetto del precorso omogeneizzante aperto a tutti gli studenti e tenuto all’inizio di settembre.

Course Objectives

The revolution of big data and business analytics has marked the modern decision-making process. Knowing how to interpret and to effectively read the available data of a company and to create appropriate models for the identification of optimal strategies are increasingly deemed as one of the keys to competitiveness. With business analytics we mean the set of skills , technologies, and methods that allow us to analyze data and develop quantitative models to guide the managerial decision making and business planning. The course provides a broad introduction to business analytics , allowing students to become familiar with alternative problem categories and with the quantitative methods that are most commonly used in the solution of managerial problems. The teaching style is application oriented. Specific attention is devoted to the practical implementation of the proposed methodologies through software packages commonly used in business practice (Excel).

Course Content Summary

• Making Decisions: Introduction to Decision Analysis.
• Deciding under Trade-offs: Linear Programming.
• Data sources and review of basic statistics.
• Linear regression with managerial applications.
• Introduction to logistic regression and its main uses in Management.

Detailed Description of Assessment Methods

The exam is written, with students taking the exam using the calculator in computer rooms. The exam shall last 1 hour and 30 minutes. There are problems covering the entire course material for a total of 16 questions for a maximum of 32 points. Each question shall be graded 0, 1 or 2 points.

Textbooks

• P. Klibanoff, A. Sandroni, B. Moselle et al., Managerial Statistics: A Case-Based Approach, Cengage, 2015.
• G.E. Monahan, Management Decision Making, Cambridge University Press, 2000.
• Notes provided by the teachers.

Prerequisites

Knowledge of basic topics in statistics and probability is required.These topics are the content of the preparatory course, which is held at the very beginning of September.

Course Objectives

The revolution of big data and business analytics has marked the modern decision-making process. Knowing how to interpret and to effectively read the available data of a company and to create appropriate models for the identification of optimal strategies are increasingly deemed as one of the keys to competitiveness. With business analytics we mean the set of skills , technologies, and methods that allow us to analyze data and develop quantitative models to guide the managerial decision making and business planning. The course provides a broad introduction to business analytics , allowing students to become familiar with alternative problem categories and with the quantitative methods that are most commonly used in the solution of managerial problems. The teaching style is application oriented. Specific attention is devoted to the practical implementation of the proposed methodologies through software packages commonly used in business practice (Excel).

Course Content Summary

• Making Decisions: Introduction to Decision Analysis.
• Deciding under Trade-offs: Linear Programming.
• Data sources and review of basic statistics.
• Linear regression with managerial applications.
• Introduction to logistic regression and its main uses in Management.

Detailed Description of Assessment Methods

The exam is written, with students taking the exam using the calculator in computer rooms. The exam shall last 1 hour and 30 minutes. There are problems covering the entire course material for a total of 16 questions for a maximum of 32 points. Each question shall be graded 0, 1 or 2 points.

Textbooks

• P. Klibanoff, A. Sandroni, B. Moselle et al., Managerial Statistics: A Case-Based Approach, Cengage, 2015
• G.E. Monahan, Management Decision Making, Cambridge University Press, 2000
• Notes provided by the teachers.

Prerequisites

Knowledge of basic topics in statistics and probability is required.These topics are the content of the preparatory course, which is held at the very beginning of September.