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Glossary
Semester (Sem)
1First Semester
2Second Semester
AAnnual course
Educational activities
CSimilar or integrative activities
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 Civil
Environmental and Land Management Engineering
Name (Master of Science degree)(ord. 270) - MI (489) Environmental and Land Planning Engineering
Track M2D - MONITORAGGIO E DIAGNOSTICA AMBIENTALE
Programme Year 1

Course Details
ID Code 089112
Course Title STATISTICAL MODELS AND STOCHASTIC PROCESSES
Course Type Mono-Disciplinary Course
Credits (CFU / ECTS) 6.0
Semester First Semester
Course Description Statistical model, parametric and non parametric cases; random sample, definition of statistic. Estimators, mean square error, unbiased estimators; consistent estimators. Sample moments; sample mean and sample variance. Sampling from normal populations and related distribution functions. Construction of estimators: the method of moments and the maximum likelihood method. Invariance and asymptotic properties for maximum likelihood estimators. Confidence intervals and bounds; significance level and confidence coefficient. Interval estimates for the mean and the variance in the case of a normal population, for the proportion in the case of a Bernoulli population, for parameters of a generic population in the case of large samples. Statistical hypotheses; two-hypotheses testing; error types. Non-randomized tests; critical region; power function and test amplitude; uniformly most powerful tests. Test statistics; observed size or p-value. Tests for the mean and variance in normal populations (z-test, t-test, Fisher-Snedecor test). The chi square test. Normality tests. Examples and applications. Linear statistical model. Regression. Prevision models. Least square method. Linear statistical models. Simple and multiple linear regression. Inference on the regression parameters; confidence intervals and tests. Prediction. Residue analysis and model evaluation. Examples and applications. Random processes Definition of a random process, finite dimensional distributions, mean value function and covariance function. Montecarlo's Method. Markov processes; definitions and main properties. Homogeneous Markov chains with discrete parameter. One-time probability distributions; n-step transition probabilities. Equilibrium distributions. Waiting times, mean waiting times and relation with the equilibrium distribution. Examples and applications.
Scientific-Disciplinary Sector (SSD)
Educational activities SSD Code SSD Description CFU
C
MAT/06
PROBABILITY AND STATISTICS
6.0

Schedule, add and removeAlphabetical groupProfessorLanguageCourse details
From (included)To (excluded)
--AZZZZEpifani Ilenia
manifesti v. 3.4.3 / 3.4.3
Area Servizi ICT
20/10/2020