Publication Date

Spring 2019

Advisor(s) - Committee Chair

Dr. Ngoc Nguyen (Director), Dr. Ferhan Atici and Dr. Richard Schugart

Degree Program

Department of Mathematics

Degree Type

Master of Science


This study consists of the sensitivity analysis for two previously developed tumor growth models: Gompertz model and quotient model. The two models are considered in both continuous and discrete time. In continuous time, model parameters are estimated using least-square method, while in discrete time, the partial-sum method is used. Moreover, frequentist and Bayesian methods are used to construct confidence intervals and credible intervals for the model parameters. We apply the Markov Chain Monte Carlo (MCMC) techniques with the Random Walk Metropolis algorithm with Non-informative Prior and the Delayed Rejection Adoptive Metropolis (DRAM) algorithm to construct parameters' posterior distributions and then obtain credible intervals.


Applied Statistics