This course introduces the complete randomization of one factor, the Latin, Greco-Latin square, the factorial design, the block design, the mixed models, and the fractional replication, etc.
Regression analysis is prerequisite.
Mathematical statistics 1 is prerequisite. This course is focused on Random walk, Reflection principle, Arcsine law, Stopping time, the basic concepts of Poisson process, Jump process, birth and death process, Brownian motion, Diffusion process, and Probability measure theory. Simple random, stratified, cluster, and double sampling. Sampling with unequal probabilities. Properties of various estimators including ratio, regression, and difference estimators.