Award-Winning Statistics Tutors
serving Memphis, TN

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.

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 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.

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.

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.

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!

Engineering at Dartmouth meant Rachel lived in data — running experiments, interpreting distributions, and making decisions based on probability and hypothesis testing. She brings that practical fluency to statistics tutoring, connecting concepts like standard deviation and confidence intervals to real scenarios instead of leaving them as abstract formulas.

Most students memorize the formulas for z-scores or standard deviation without ever seeing where they come from — Kathleen's math degree from Washington University means she can derive them from scratch and explain each piece along the way. She treats every statistics concept as an extension of the algebra and calculus her students already know, which makes new material feel like a logical next step rather than a disconnected set of rules.

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.

Every research methods course in Daniel's neuroscience program at Penn relies heavily on statistics — from designing experiments with proper controls to running t-tests and interpreting p-values. That daily exposure to real data analysis gives him a practical lens on probability distributions, hypothesis testing, and regression that most stats tutors can't offer.

Graduating from an IB high school with top marks and then completing a math degree at Brown means Zofia encountered statistics from both sides — the structured hypothesis testing and chi-square analyses of the IB curriculum, and the rigorous probability theory that underpins it all at the university level. She breaks down concepts like conditional probability and sampling distributions by connecting them to the mathematical machinery students rarely get to see in a standard stats course. Her 3.87 GPA in a demanding program speaks to the precision she brings to every session.

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.

Studying economics at Brown meant Carter lived inside datasets — running regressions, testing hypotheses, and interpreting distributions long before he started tutoring. That firsthand experience makes him especially effective at teaching concepts like standard deviation, normal models, and conditional probability in ways that feel grounded rather than abstract. He's rated 5.0 by students.

Emily's computational biology concentration at Cornell is essentially applied statistics — she uses probability distributions, confidence intervals, and regression analysis to interpret biological data every week. That hands-on context lets her explain statistical reasoning through concrete examples rather than abstract formulas.

Understanding when to use a t-test versus a z-test, or why a sampling distribution behaves the way it does, requires more than formula sheets — it takes genuine statistical intuition. Brian built that intuition through his economics coursework at Caltech, where statistical analysis was a daily tool, and he walks students through each concept with concrete data examples.

Understanding statistics means learning to think critically about variability, probability, and what data can actually tell you. Tashina applies statistical methods daily in her PhD research in brain sciences — hypothesis testing, confidence intervals, regression — and she unpacks each concept by connecting it to the kind of real analysis questions that make the material stick.

Probability distributions, hypothesis testing, and confidence intervals all require a kind of careful reasoning about uncertainty that Allen sharpened through his economics coursework at Yale. He teaches statistics as a way of making arguments with data — interpreting p-values, choosing the right test, and understanding what a result actually means in context. His 5.0 rating speaks to how clearly he communicates these ideas.

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.