Award-Winning Statistics Tutors
serving Chattanooga, TN

A Quantitative Methods minor at Vanderbilt means Heather spent semesters immersed in regression analysis, hypothesis testing, and probability — the exact material that trips up most statistics students. She teaches the reasoning behind each test so students can choose the right method on their own, not just follow a decision flowchart. Her 4.9 rating speaks to that approach.

I am a rising sophomore at Emory University working towards a Bachelors of Arts degree in Psychology, as well as a minor in global health, culture, and society. I tutored in multiple subject areas in high school as a peer tutor as well as a tutor to younger students in elementary and middle school. I also tutored elementary school students in multiple subject areas during my first year at Emory. I tutor in many subjects, but have always been passionate specifically about tutoring in math. I have been tutored by peers many times throughout high school and college in different subjects, including the ACT. I found unique ways to solve problems and expand my problem solving skills through this, especially because I felt as though my peers were better able to relate to me, and therefore cater to my needs as a student. My approach is catered specifically to each student by first learning how he or she best learns, and then using tactics that will benefit them the most as they learn and grow as a student.

I attended law school at Vanderbilt University and I earned an MBA and a Ph.D. in Finance (Statistics minor) from the University of Iowa. I served for over 10+ years as a finance professor, teaching assistant, and tutor at 4 Top-40 public universities, during which time I received numerous awards for exemplary teaching. I qualified for MENSA by scoring in the 99.9th percentile on standardized tests for graduate schools: LSAT, 173 (6.0+ AWA) and GMAT, 760. I use a student-centered approach and I personalize educational plans to balance student needs based on learning styles, motivations, and interests. I have experience fostering one-on-one learning in a variety of environments, including online platforms. I guide students in identifying resources to improve their ability to succeed and monitor their progress while providing ongoing feedback. I will help you thrive in your mathematics, probability/statistics, and business courses or in your preparation for standardized tests.

The jump from calculating a mean to understanding confidence intervals and hypothesis testing trips up a lot of students because statistics requires a different kind of mathematical thinking — probabilistic rather than deterministic. Lawton approaches each concept by building intuition around what a distribution actually represents before introducing formulas. His math coursework and programming skills in Python also make him a strong resource for students working with statistical software or data sets.

Studying neuroscience means Elliot reads and produces statistical analyses constantly — from hypothesis testing to regression models to understanding what a standard deviation actually tells you about a dataset. He teaches statistics by grounding every formula in a concrete question, so students understand when to use a t-test versus a z-test and why it matters.

I'm a graduate student in Applied Statistics with experience in general math and computer programming to boot. I currently have a PhD in Applied Statistics with experience in data analytics. I've had the opportunity to do some math and statistics work for hospitals and research facilities, and I enjoy getting to share my passion for math with others to assist them in their education.

Probability distributions, hypothesis testing, and regression analysis all click faster when a student understands *why* the formulas work, not just how to punch them into a calculator. Matthew connects statistical reasoning to real-world decision-making — the kind he practiced throughout his MBA and legal training. That cross-disciplinary perspective makes abstract concepts like p-values and confidence intervals feel grounded and practical.

Public health coursework at the University of Memphis means Paul lives in statistics daily — from interpreting confidence intervals in epidemiological studies to running hypothesis tests on real population data. He teaches the logic behind each method so that choosing between a t-test and a chi-square feels intuitive, not arbitrary.

I am currently a Junior at The University of Alabama pursuing degrees in both Mathematics & Economics. After I graduate, I intend to stay at Alabama to get an M.A. in Economics. I have been tutoring both Math and ACT Prep since I was a Sophomore in High School. After 4 years of experience, I continue to enjoy tutoring these subjects, and the constant challenge of improving my abilities and techniques. I get a great sense of satisfaction in helping those I tutor improve their grades, test scores, and overall understanding of the subjects I am teaching them. Not only do I focus on the subject matter being taught, but I also focus on helping students develop the study skills and habits that are imperative to success later in their academic careers. Through my four years of tutoring, I have developed the ability to mold my tutoring style around however the student learns best whether that be visually, through examples, etc. This allows me to provide an individualized tutoring session to each person I tutor. I believe no two students should be tutored the same was; every student has different learning methods and I view it as my responsibility to modify my tutoring style to fit each individual student.

I'm from New Jersey and of Italian decent, so I naturally love cooking and all things pizza. My favorite childhood book is The Giver by Lois Lowry, and favorite high school class was physics (rockets, easy winner). I enjoy playing guitar and ride my bicycle on a sunny day.

I am currently applying for medical school and working towards a masters in public health. I have experience working with many different ages ranging from middle school to college level students. Most of my experience is with math and sciences as well as test prep for English ACT exams. I can tutor in math (pre calculus, trigonometry, algebra, geometry) sciences (biological sciences, chemistry, physics) and English. My favorite subject to tutor is algebra because it is like a puzzle, and who does not like a good puzzle? My teaching philosophy consists of learning about the students' interests and providing a way to relate their interests into the work they are doing so it can be more meaningful to them. I have found that the more a subject means to a student personally, the better they do in the subject. So, in this way it is possible to turn a subject weakness into a strength and passion.

I am a junior at Vanderbilt University studying Child Development and Art History, and I have always had a passion for tutoring and mentorship. Although most of my tutoring experience has been for elementary students in reading and math, I am most excited about tutoring middle and high schoolers because the subjects that are learned during these times are so much more detailed, dynamic, and interesting! These were also the years where my love of learning really took shape, and getting the opportunity to foster this same love and appreciation for learning in other students excites me.

I'm a recent graduate from Lehigh University where I majored in behavioral neuroscience, and I am now pursuing my Master's in Public Health with George Washington University. I am very enthusiastic about tutoring and I have three years of experience working with students of all different backgrounds in a wide variety of subjects, from middle school English to college level biology. My number one priority is to get to know you, both as a student and as a person, in order to create a solid foundation in your learning experience. I firmly believe that everyone's learning styles are different and what works for one student may not work for another. Teaching and learning is a highly collaborative process, and through open communication and understanding your learning style I strive to make the learning process fun and engaging. I can assure you that as your tutor, there is no question not worth asking and I am dedicated to making your learning experience tailored to your strengths in order to yield to most successful results!

An economics degree means Maggie didn't just study statistics in a textbook — she applied distributions, hypothesis testing, and regression analysis to real datasets. She teaches students to interpret what a p-value actually tells them and how to choose the right test for a given scenario, building the kind of statistical intuition that carries through exams and research projects alike.

A PhD in economics at Yale means Anthony doesn't just teach statistics — he relies on it daily, from econometric modeling to designing empirical studies that require careful handling of inference, sampling, and regression. His dual undergraduate background in physics and math gives him an unusual ability to trace statistical methods back to their mathematical roots, making concepts like maximum likelihood estimation or the central limit theorem genuinely intuitive. Rated 5.0 by students.

Running regression analyses, interpreting p-values, and choosing between parametric and nonparametric tests are things Martha does routinely in her social psychology research at Michigan. That hands-on fluency means she can explain not just how to compute a standard deviation or set up a hypothesis test, but why each step matters and what the results actually tell you. Rated 5.0 by students.

Probability distributions, hypothesis testing, and regression analysis each require a different kind of thinking — and Rahi distinguishes clearly between the conceptual reasoning and the mechanical calculation so students know which skill a problem is actually testing. His applied mathematics background means he can explain the logic behind formulas like the Central Limit Theorem instead of just handing students a recipe to follow.

Studying Comparative Human Development at the doctoral level means Gabriel has spent years designing studies, interpreting data sets, and running statistical analyses firsthand. He teaches statistics by grounding concepts like probability distributions, hypothesis testing, and regression in real research questions rather than abstract formulas. That practical lens makes the subject click for students who struggle with the textbook approach.

Studying conducting at Juilliard means Molly lives in data — analyzing scores, interpreting patterns, and making decisions based on complex information. She brings that same analytical mindset to statistics, breaking down probability distributions, hypothesis testing, and data interpretation into logical steps. Her 5.0 client rating speaks to how clearly she communicates even the trickiest concepts.

A PhD statistician who also holds a biomedical engineering degree, Sam teaches introductory and intermediate statistics with an unusual amount of real-world context. Whether the topic is hypothesis testing, confidence intervals, or regression, he unpacks the logic behind each method so students can interpret results critically, not just run calculations.

Probability distributions, hypothesis testing, and regression analysis are central to both engineering and business — and Caroline has graduate-level training in both. Her mechanical engineering M.S. from WashU built her statistical modeling skills, while her current MBA at MIT Sloan sharpens how she interprets data for real-world decisions. She teaches the reasoning behind each method so formulas stop feeling like black boxes.

Most students walk into statistics expecting another math class and get blindsided by the emphasis on interpretation — explaining what a confidence interval actually means, or why correlation isn't causation. Amber tackles that interpretive layer head-on, teaching students to read context before crunching numbers. Her theater background gives her a knack for making abstract concepts like probability distributions feel concrete and memorable.

Probability distributions, hypothesis testing, and regression analysis click faster when a tutor can show where these tools get deployed in practice. Firas uses statistics daily in his machine learning research at Princeton, which means he can walk through concepts like Bayesian inference or p-values with real datasets and concrete examples instead of abstract formulas.

Yi's graduate training in research and experimental psychology required heavy use of statistical methods — from hypothesis testing and ANOVA to regression modeling and interpreting p-values in published studies. That hands-on experience with real data analysis means she teaches statistics as a tool for answering questions, not just a set of formulas to memorize.

Probability distributions and hypothesis testing trip students up when they try to memorize formulas without understanding what a p-value actually represents or why a sample size matters. Abismael connects statistical reasoning back to real engineering applications — quality control, experimental design, process variation — which makes abstract concepts like confidence intervals tangible. He's the kind of tutor who will quiz you with problems you haven't seen before, because that's what exams do.