Award-Winning Statistics Graduate Level Tutors
serving Denver, CO

Graduate-level statistics demands fluency with theory — sufficiency, maximum likelihood estimation, Bayesian inference, and the mathematical underpinnings that introductory courses skip. Bahaeddine earned his PhD in Statistics and teaches at the university level, so he can walk through measure-theoretic probability or asymptotic theory with the rigor a graduate program expects.

Graduate-level statistics trips up many students at the transition from descriptive methods to inferential reasoning — hypothesis testing, regression analysis, ANOVA, and the assumptions underlying each technique. Jason teaches these concepts at a technical college in Pittsburgh, which means he's constantly translating statistical theory into applied, real-world problem solving. His math and education background lets him break down dense material into steps that actually make sense.

Graduate-level statistics demands comfort with concepts like hypothesis testing, regression modeling, and ANOVA that go well beyond intro courses. Dillon's engineering background — including a master's in welding engineering technology — required heavy applied statistics work, from designing experiments to interpreting multivariate data in real research contexts. He teaches the reasoning behind each method so students can choose and defend the right analytical approach.

I am also interested in tutoring college students preparing for the GRE general test. For test preparation, I assign a decent amount of homework each week and I spend the majority of my sessions going over the questions my students answer incorrectly.

My tutoring approach is one of coaching, mentoring, and helping the student understand exactly what level and detail of help that they need to get ahead. Combining the personal discipline learned during 20 years as a Naval Officer with the unique expertise learned in one-on-one communication with peers and sailors as well as my five children, I can help you or your child succeed. A Bachelor's in Electrical Engineering, and a Math Minor help qualify me for tutoring in many subjects. My individualized tutoring methods also raised my step-son's Physics grade from a C to an A in one semester. I specialize in mathematics (basic arithmetic through calculus) but can help in many other subjects. Learning should be fun, but should also, at times, bring "Instant" results. I work to keep positive encouragement in every lesson, tutoring, or test preparation session. I speak fluent Spanish!

Graduate-level statistics often demands fluency with multivariate analysis, mixed models, and experimental design — topics Dan tackled extensively during his Master's in Plant Biology and Conservation, where statistical modeling was central to his research. He breaks down the logic behind tests like ANOVA, regression diagnostics, and maximum likelihood estimation so the methodology clicks, not just the software output. Rated 5.0 by students.

Graduate-level statistics demands fluency with proofs and derivations that introductory courses barely touch — moment-generating functions, maximum likelihood estimation, and the theory behind hypothesis testing. Victor's master's in Applied Mathematics gave him direct experience with these topics, and he brings that rigor to sessions while keeping notation and logic organized. He holds a 5.0 client rating.

Graduate-level statistics demands comfort with proofs and distributions that introductory courses barely mention — maximum likelihood estimation, Bayesian inference, multivariate hypothesis testing. Channing digs into the mathematical machinery behind these methods, connecting measure-theoretic ideas to practical applications so the theory actually sticks. His broad math background, spanning calculus through biostatistics, keeps the explanations rigorous without losing sight of real-world relevance.

Victor earned his B.S. in Economics with a statistics concentration from Purdue, where he tackled regression analysis, hypothesis testing, and probability distributions as core coursework. That quantitative foundation, combined with his time as a Supplemental Instruction Leader, means he can unpack dense concepts like multivariate analysis or ANOVA in ways that actually click. Rated 5.0 by students.

I am highly praised by my students and supervisors. Even today I still kept the communication with many students.

Graduate-level statistics demands comfort with concepts like maximum likelihood estimation, Bayesian inference, and hypothesis testing frameworks that go well beyond intro courses. Abhi's M.S. in Data Science from UIUC and current PhD work at NYU mean he uses these tools daily in research — he teaches the theory alongside the practical intuition for when and why each method applies.

Having earned a PhD in Statistics, Sam teaches graduate-level topics like maximum likelihood estimation, Bayesian inference, and multivariate analysis with the depth that comes from years of research-level work. He's particularly strong at bridging the gap between statistical theory and practical application — connecting proofs to the computational tools students actually use in their programs.