Industrial statistics

The course is in Italian. The original title is statistica industriale.

As the name suggests, this is a very practical course, atypical for the degree in mathematics, with few theorems and proofs. It aims at forming good statistics practitioners, in the belief that the application of statistics in industrial setting requires a practical more than theoretical approach, but still greatly benefits from a true mathematical mindset.

This is the only course with some statistics content of the degree in mathematics, so from that point of view it must be (and truly is) self-contained. Nevertheless, since some topics are quite advanced, a thorough understanding of probability theory is an expected prerequisite and students are recommended to do all the exercises and homeworks given in the first part without delay.

Syllabus

Course goals for Students

Gain the knowledge, understanding and practical ability to develop advanced statistical analysis, based on the treated methods and techniques. It is moreover required to become able to use Microsoft Excel in a thorough, flexible and very fast way.

Prerequisites

Analisi matematica 2, geometria 1, elementi di probabilità.

Lecture topics overview

  1. Maximum likelihood estimators, confidence intervals, hypothesis testing.
  2. Multiple regression, linear and polynomial, also heteroscedastic.
  3. Design of Experiments (DoE).
  4. Analysis of variance (ANOVA), one-way, two-way and with interactions.
  5. Pearson's chi-square test (goodness-of-fit test and contingency tables).
  6. Advanced hypothesis tests: Operating Characteristic (OC) Curves and power; test for p with exact binomial law. Fisher-Irwin test.
  7. Montecarlo simulation.

Recommended readings

  1. Sheldon M. Ross - Introduction to Probability and Statistics for Engineers and Scientists, Fourth Edition - Academic Press, 2009 - ISBN 978-0123704832
  2. Richard A. Johnson, Dean W. Wichern - Applied Multivariate Statistical Analysis - Pearson, 2007 - ISBN 9780131877153
  3. Michael R. Middleton - Data Analysis Using Microsoft Excel: Updated for Office XP - South-Western College Pub, 2003 - ISBN 978-0534402938
  4. Andrew Sleeper - Design for Six Sigma Statistics - McGraw-Hill, 2005 - ISBN 978-0071451628

Assessment methods and criteria

  1. Practical test: multivariate statistical analysis on Microsoft Excel.
  2. Interview.

Teaching methods

Class teaching (32 h) and computer lab on Microsoft Excel 2010 (20 h)

Materials and links

2014-15

The course was held in the second semester, from March, 3rd to June, 3rd 2015.

2016-17

The course will be held in the second semester, starting in March 2017.