Course Content (Syllabus)
Statistical methods in data analysis using the R language: Descriptive statistics and graphical representation of data. Discrete and continuous distributions, random numbers generators and distributions. Statistical inference with parametric and non-parametric methods. Hypothesis tests and confidence intervals by resampling methods. Regression models (linear regression and generalized models for continuous, binary, categorical, count dependent variables and mixed independent variables). Non-parametric regression. Multivariate analysis: Factor analysis, cluster analysis and correlation analysis.
Course Content (Syllabus)
Mathematical represantation, metrics and models of processes and transactions on the Web. Game Theory. Strategies and optimization. Data and statistical analysis. Introduction to Multiagent Systems. Agent Communication & Interaction Protocols. Contract Net. Negotiation. Auctions. Agent Applications.
Course Content (Syllabus)
Data analysis with statistical program (SPSS). Coding and data entry. Definition of variables. Descriptive statistics (tables, plots and numerical measures). Statistical inference. Parametric and non-parametric hypothesis tests. Statistical models and prediction. The course hosts lectures on issues related to Research Methodology as: Aims of the survey methodology. Selection and delineation of the research. Use of available time and the treatment of Stress. Overview of Special Contributors.