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Semester (Sem)
1First Semester
2Second Semester
AAnnual course
Language
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
Context
Academic Year 2017/2018
School School of Industrial and Information Engineering
Name (Bachelor of Science degree)(ord. 270) - CO (360) Engineering of Computing Systems
Track IOR - Ingegneria Informatica Online - Elis
Programme Year 3

Course Details
ID Code 097798
Course Title PROBABILITY AND STATISTICS
Course Type Mono-Disciplinary Course
Credits (CFU / ECTS) 10.0
Semester First Semester
Course Description Introduction The most frequent probability models: validation. Descriptive statistics Quantitative e qualitative variable; graphical descriptions of data; fre-quency distribution; box plot; bivariate case, least squares means. Probability Combinatorics. Sample space event space, sigma algebras. Conditional probabil-ity and independence of events, reliability. Random variables Special random variables; discrete case: Bernoulli, binomial, geometric, hypergeometric, Poisson; continuous case: uniform, exponential, gamma, normal. Moment-generating functions, Tchebysheff inequality. Function of random variables. Random vectors Cumulative distribution function, independent random variables. Multino-mial normal distribution. Conditional distributions. Sampling The Central Limit Theorem, the normal approximation. Weak law of large numbers, the variables chi-square, t-student, Cauchy, Fisher. Short introduction to Monte Carlo meth-ods. Estimation Point estimation and intervals estimation for normal and Bernoulli populations. Hypothesis testing Parametric testing for parameters of normal and Bernoulli distributions. Nonparametric testing: goodness of fit, Kolmogorv-Smirnov, q-q plot, Shapiro-Wilk. Test of independence Linear models and estimation Method of least squares, inferences concerning parameters, predicting a particular value of y using simple linear regression. Multiple linear regression model, fitting the linear model by using matrices, the projection matrix.
Scientific-Disciplinary Sector (SSD)
Educational activities SSD Code SSD Description CFU
--
MAT/06
PROBABILITY AND STATISTICS
10.0

Schedule, add and removeAlphabetical groupProfessorLanguageCourse details
From (included)To (excluded)
--AZZZZPiazza Elio
manifesti v. 3.4.2 / 3.4.2
Area Servizi ICT
28/09/2020