**Course Description**

Introduction to probability spaces;The theory of measure and integration;Random variablesand limit theorems;Distribution functions, densities and characteristic functions; Convergence of random variables and their distributions; Uniform integrability and the Lebesgue convergence theorems; Weak and strong laws of large numbers, central limit theorem, conditional probabilities and Radon-Nikodym derivatives of measures; Strong and weak convergence of probability measures, measurability and observability.

- Teacher: Dr. Wycliffe Cheruiyot

linear

- Teacher: Dr. Anthony Karanjah

Multivariate Methods and Analysis

- Teacher: Dr. Anthony Karanjah