Παρουσίαση/Προβολή

(9079) -  Christos Thomadakis

Περιγραφή Μαθήματος

Objectives of the course
This is a standard introductory course to Probability and Estimation. Upon completion of this
course, students will be able to

• compute probabilities of events, expected values, and variances of discrete and continuous random variables
  
• apply the central limit theorem and find estimates of unknown parameters
  
• construct confidence intervals of the mean value and the variance of a Normal population

Prerequisites and co-requisites
Knowledge of Calculus

Course content
The content of the course will be divided approximately into the following units:

• Introduction to random experiments and properties of probabilities
• Law of total probability and Bayes rule
• Discrete and continuous random variables
• Central Limit Theorem, Law of large numbers, and estimators of unknown parameters
• Unbiased estimators
• Rao-Blackwell estimator and Cramer-Rao lower bound
• Method of maximum likelihood and method of moments
• Confidence intervals for the Normal mean
• Confidence intervals for the difference of means of Normal populations
  

Recommended or required reading

• S. M. Ross, ”A first course in Probability”, 8th Edition, 2010, Prentice Hall.
• S. M. Ross, ”Introduction to Probability and Statistics for Engineers and Scientists”, 3rd Edition, 2004, Elsevier.
• G. G. Roussas, ”A Course in Mathematical Statistics”, 2nd Edition, 1997, Academic Press

Planned learning activities and teaching methods
Teaching in Class, distant learning (if necessary)

Assessment methods and criteria
Written final exam, Assignments

Ημερομηνία δημιουργίας

Δευτέρα, 9 Οκτωβρίου 2023