Award-Winning Statistics Graduate Level Tutors
serving Madison, WI

Graduate-level statistics demands comfort with proofs and derivations that undergraduate courses often skip — moment-generating functions, maximum likelihood estimation, and the theoretical machinery behind hypothesis testing. Aaron brings a PhD mathematician's rigor to these topics, walking through measure-theoretic ideas and convergence arguments with the care they require.

Graduate-level statistics demands fluency with techniques like regression modeling, ANOVA, and hypothesis testing frameworks that go well beyond introductory coursework. Scott applies these methods actively in his doctoral research at NYU, where he analyzes complex datasets on human development — so he can walk through both the theory and the practical decision-making behind choosing the right analysis for a given research question.

Graduate-level statistics demands comfort with mathematical proofs and distributional theory that go far beyond introductory courses — maximum likelihood estimation, Bayesian inference, and multivariate analysis all require real mathematical maturity. Yasaman's Ph.D. research in Electrical and Computer Engineering at McMaster has her working with advanced statistical methods regularly, so she can unpack both the theory and the computational implementation behind each technique.

Graduate-level statistics demands comfort with mathematical proofs and distribution theory that undergraduate courses barely touch — moment-generating functions, maximum likelihood estimation, Bayesian inference. Sabry's Ph.D. training in Chemical and Biomolecular Engineering required rigorous statistical modeling for experimental data, so he approaches these topics as tools with real stakes, not just textbook exercises. He's particularly effective at connecting abstract theory to applied research contexts.

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.

Graduate-level statistics throws curveballs that intro courses never touch — multivariate regression, hierarchical modeling, interaction effects in complex datasets. As a psychology PhD student who runs her own research analyses in SPSS, Kate teaches these methods through real study designs rather than abstract formulas, making output interpretation second nature.

Graduate-level statistics throws students into the deep end — maximum likelihood estimation, mixed-effects models, Bayesian inference — and expects fluency, not just familiarity. Elliot's PhD in Neuroscience required designing and analyzing complex experimental datasets, so he teaches these methods as tools for answering real research questions. Rated 5.0 by students.

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 throws curators of data into the deep end — multivariate analysis, mixed-effects models, Bayesian inference — and Michael's biology master's work required him to live in that world daily. He teaches the logic behind each method so students can choose the right test for their research design, not just run code blindly. Rated 5.0 by students.

Master's grad with 10+ YOE teaching Artificial Intelligence, Agentic Programming, Math, Economics, Econometrics, Statistics and Data Science programming from middle school to University. I'm an economist with multiple areas of expertise, and experience helping students achieve their goals in academic and professional life. My sessions are structured, goal-oriented, and designed to help students improve quickly, whether they are preparing for exams, struggling with weekly problem sets, or working on data-based assignments.

Graduate-level statistics often means wrestling with multivariate methods, hierarchical models, and software like SPSS, Stata, or R while simultaneously trying to apply them to a thesis or dissertation dataset. Hidefusa's doctoral work in clinical neuropsychology gave him hands-on experience designing studies, running complex analyses, and interpreting output — skills he now breaks down for other graduate students navigating their own research.

I am listening to and learning about him or her as an individual. I can also discover what motivates the student during this conversation and plan for how to frame future tutoring sessions in terms of what the student already knows and enjoys.

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.