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Semester (Sem)
1First Semester
2Second Semester
AAnnual course
Course completely offered in italian
Course completely offered in english
--Not available
Innovative teaching
The credits shown next to this symbol indicate the part of the course CFUs provided with Innovative teaching.
These CFUs include:
  • Subject taught jointly with companies or organizations
  • Blended Learning & Flipped Classroom
  • Massive Open Online Courses (MOOC)
  • Soft Skills
Course Details
Academic Year 2019/2020
School School of Industrial and Information Engineering
Name (Master of Science degree)(ord. 270) - BV (479) Management Engineering
Track AM - INDUSTRY 4.0
Programme Year 2

Course Details
ID Code 052911
Course Type Mono-Disciplinary Course
Credits (CFU / ECTS) 5.0
Semester First Semester
Course Description The course aims to introduce students to statistical data analysis. It is intended to provide basic knowledge of inferential statistics. The first part of the course will be devoted to the study of the probabilistic language. The main topics of the course will be: point estimation, hypothesis testing, multiple regression and analysis of variance. Program: Elements of probability: Random vectors, joint distribution functions, joint and marginal probability density functions. Mean, variance, covariance, correlation. Estimation and hypothesis testing: Point and interval estimation, sampling distributions from a normal population, tests, type I and type II errors, size and level of the test, power function, p-value. Tests on the mean and the variance of a normal population. Test on a proportion. Inference for the differences between two normal means, between two proportions and for the ratio between two variances of normal populations. Regression: Multiple regression, least square estimation, confidence interval and hypothesis testing concerning the regression coefficients, prediction of a future response, coefficient of determination and adjusted R2, analysis of residuals: assessing the model. Introduction to the analysis of variance.
Scientific-Disciplinary Sector (SSD)
Educational activities SSD Code SSD Description CFU
Innovative teaching The course includes  1.0  credits in Innovative Teaching as follows:
  • Blended Learning & Flipped Classroom

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manifesti v. 3.5.17 / 3.5.17
Area Servizi ICT