Course title: Statistics and Random Processes
Number of credits (ECTS): 6
Weekly number of classes: 3+2+0+0
Prerequisite for enrollment of the subject: Passed: Probability
Course Goals (acquired competencies): Adopt the basic concepts and methods from random processes and systems. Development of analytical thinking, critical abilities, problem solving, ability to analyze and synthesize.
Total available number of classes: 180
Course Syllabus: Descriptive statistics. Data and types of data. Displaying data. Estimation of parameters. Method moment. Maximum-Likelihood Estimation method. Confidence intervals. Testing of parametric hypotheses. Testing nonparametric tests. Pirsons test, Kolmogorov, Kolmogorov-Smirnov test. Random processes-general terms. Markov chains. Poisson’s process. Generalization of the Poisson process. Queuening systems.
|John A. Rice||Mathematical Statistics and Data Analysis||Ars Lamina||2014|
|А. Field||Discovering statistics using SPSS||SAGE Publications||2005|
|Oliver C. Ibe||Fundamentals of Applied Probability and Random Processes||Elsevier||2005|
|S. Brandt||Data Analysis, Statistical and Computational Methods for Scientists and Engineers||Springer||1998|