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Math Stats Physics Data-science Code-dev. Distance-learner friendly!
Peter L.

5.0 (1,020 ratings)

5,009 hours tutoring

Your first lesson is backed by our Good Fit Guarantee
Hourly Rate: $115
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Peter L.'s Photo

Math Stats Physics Data-science Code-dev. Distance-learner friendly!
Math Stats Physics Data-science Code-dev. Distance-learner friendly!
Peter L.

5.0 (1,020 ratings)

5,009 hours tutoring

Your first lesson is backed by our Good Fit Guarantee
5.0 (1,020 ratings)

5,009 hours tutoring

Your first lesson is backed by our Good Fit Guarantee

About Peter

Bio

Perhaps I can help! I am a math/statistics/physics/data science/software development tutor based in Portland ME and Cambridge MA. If you are in greater Portland or greater Boston, please consider me for help with math from the basics to calculus to beginning and advanced statistics, ODE/PDEs, linear algebra, time series analysis or any other topic of applied math. I can help with high school or college level physics (I have a PhD in physics), general data science (I've made a career...

Perhaps I can help!

I am a math/statistics/physics/data science/software development tutor based in Portland ME and Cambridge MA. If you are in greater Portland or greater Boston, please consider me for help with math from the basics to calculus to beginning and advanced statistics, ODE/PDEs, linear algebra, time series analysis or any other topic of applied math. I can help with high school or college level physics (I have a PhD in physics), general data science (I've made a career developing data mining methods for R&D in analytical chemistry) and programming in C, C++, java, & perl.

Over half of my students are distance learners who seek the bricks-and-mortar of a coffee shop and the skin-and-bones of a tutor to help ground their education in tangible experience. I'm delighted to be smiling/frowning/laughing/worrying human element in their education.

Some background: I am the son of a professor and the brother of a professor. I married a professor's daughter. Indeed, I've been an adjunct professor at University of Southern Maine and a teaching fellow at Harvard, where I was the recitation instructor in quantum mechanics for first-year chemistry department graduate students. Currently, I tutor one 5th grader, one high school junior, several college students, and several post-grads who are taking college courses for professional advancement. Whether I'm covering the intuitive thinking behind quantum spin matrices or the proof of the Divide-by-Three rule, I approach every teaching opportunity as a chance to discover the edge of a student's conceptual limits, plant myself there, illuminate a new zone of cognition, and call him or her into it. The process is hugely creative, just plain fun while I'm doing it (for both of us), and as rewarding as anything I've ever done. Teaching is in my lineage, my blood, and my soul.

Years ago, I asked Tim O'Reilly, the publisher of the O'Reilly books on new technology, what he thought was the best way to communicate technical information. "Easy," he said. "Wait for someone

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Education

Georgetown University
Physics and History
University of California, San Diego
PhD

Policies

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Fri

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Approved Subjects

Business

Econometrics

Econometrics

For nearly a year, I have helped a Ph.D. student in economics master probability, statistics, modeling, and advanced methods such as kernel density estimation, multivariate analysis, principal component analysis, hierarchical clustering, and other machine learning methods. I have also helped countless MBA and BBA students with modeling, linear programming, and other topics in analytics. While my background is in physics rather than economics, I have managed to be useful for many students who seek help understanding and using analytics tools.

Computer

C,

C

I've never taken a class in C. I've never taught a class in C. But my computational physics PhD thesis written in my late 20s rode on the back of two years of pure C programming. I didn't learn C++ until I was in my late 30s. I read Kernighan & Ritchie's classic text in the late 80s as a graduate student at UCSD. My first copy was a freshly published 2nd edition. My thesis code, which among other things enumerated the number of self-avoiding walks in a 3x3x3 cubic lattice, was written entirely in C and made aggressive use of code recursion with changing local variables while keeping track of the enumeration using global variables. I am adept at malloc() and free(), passing by value int x,f(int x); int y=f(x) and passing by reference int x, g(int *x); int z=g(&x), and using function pointers when necessary.
C++,

C++

I have been writing C++ programs since 2001. I use the Qt libraries and the Gnu C++ compiler for my own work but am able to adjust to the development environment of students. My software has saved $75m in operational costs for a major corporation over 5 years. As a private consultant, I've been involved in every aspect of software development, from pre-sales support such as needs analysis, functional specification writing and usability and testing requirements, to the post-order development cycle such as technical and test specification writing, algorithmic architecture, to the actual coding to code reuse and library archiving to testing and validation to release management to deployment strategies to user training and post sales support. I could send thousands of lines of GUI control code or a snippet of highly recursive algorithmics, or both, if you would like.
Computer Programming,

Computer Programming

I am a computational scientist by training and practice. Perforce, I am a programmer with 20 years of experience in compiled/byte-compiled languages C, C++, Java, and several interpreted/scripting languages, e.g., Perl, bash, R and Javascript. I've worked in every aspect of programming from requirement collection to functional-and-test specifications to technical specification, to architecture, to coding, testing, end-user and API documentation, release management and support. I use object oriented design principles to maximize code clarity, longevity and reusablility. The best evidence of my training and experience in computer programming is MSRedux, a reusable code base that permits me to develop and release (soup-to-nuts!) custom software in my partcular area of research on a week-long time scale.
Computer Science,

Computer Science

My experience in Computer Science is practical. In various professional capacities, I've implemented all of the major functional algorithms: sort, linked lists, binary trees, Huffman encoding & compression, depth- and breadth-first search, recursion, symplex-type optimization, and mathematical algorithms, e.g., numerical integration & differentiation, Monte Carlo optimization & annealing, and FFTs for convolution and correlation. I have also worked on all of the major machine learning algorithms, including linear methods like principal cluster analysis and nonlinear methods like neural networks and unsupervised cluster analysis. I have managed data on the bit and byte levels, converting custom data structures to IEEE. Computer science includes a certain amount of code design, I'll add that I am comfortable teaching all of the major object oriented design patterns. I can teach in C/C++ or Java. I can also teach functional programming viz., R or javascript.
Data Science,

Data Science

Data Science is my major teaching emphasis. Since 2015, I have helped hundreds of data science students learn the four foundations of data science: probability theory (~Harvard Stat100), multivariable calculus (~Harv AM21A), linear algebra (~Harv AM21b), computation environment (R/python/C++, ~Harv CS50/109/165). I also teach extensively in statistics: inference (~Harv stat111), Bayesian methods and linear models. My students are mostly at the graduate and upper division undergraduate levels. I have a large number of post-grad mid-career self-study learners and on-line masters students, especially at Johns Hopkins and Georgia Tech.
Perl,

Perl

I was an early adopter of Perl in the late 80s as a graduate student at UCSD. I learned Perl from the first edition of Larry Wall's camel book "Programming Perl." Thirty years later, I continue to write Perl scripts to manage software builds and releases. As a postdoctoral fellow at Harvard in the early 90s, I wrote a lot of the glue-code for our protein folding research group, and all of the glue was in Perl. I've also written a Perl-based java-to-c++ translator. I have used Perl to write an automated C++-code generator for C-style structs, which helps with my binary file parsing work. I was the official amazon.com reviewer of a 1999 book on programming with Perl. Perl has been described as the Swiss Army Chainsaw of the Internet. I can show you how to get the chainsaw going, keep it sharp, and avoid hurting yourself (and your work) as you cover a lot of ground on your coding to-do list with a few lines of Perl.
Python,

Python

I have helped students in computer science, engineering, data science and statistics at Harvard, Stanford, Georgia Tech and many other universities in courses built around python. I use python for my research in the convex optimization and the theory of learning.
R

R

I use R/RStudio as my daily methods development environment. I exploit R's statistical and mathematical libraries for solving linear systems, performing convex optimization, evaluating frequentist hypotheses, inferring parameters through Bayesian statistics, and performing samplings and simulations. I also use R for reporting and technical document generation with R-markdown/KnitR. I'd be delighted to help you learn the R environment, including the powerful notion of R closures, and will show you some R best practices along the way.

Corporate Training

C++,

C++

I have been writing C++ programs since 2001. I use the Qt libraries and the Gnu C++ compiler for my own work but am able to adjust to the development environment of students. My software has saved $75m in operational costs for a major corporation over 5 years. As a private consultant, I've been involved in every aspect of software development, from pre-sales support such as needs analysis, functional specification writing and usability and testing requirements, to the post-order development cycle such as technical and test specification writing, algorithmic architecture, to the actual coding to code reuse and library archiving to testing and validation to release management to deployment strategies to user training and post sales support. I could send thousands of lines of GUI control code or a snippet of highly recursive algorithmics, or both, if you would like.
Statistics

Statistics

I am tutoring students in both intro level statistics (basic probability, combinatorics, binomial distributions, central limit theory, normal distributions, T-tests, P-tests, hypothesis testing) and intermediate statistics (regression, correlation, F-tests, ANOVA, hierarchical clustering, principal component analysis, multivariate analysis). I use statistics everyday in my regular scientific software consulting practice, and I very much like finding the few key conceptual threads that will unravel the field for new students.

Homeschool

Calculus,

Calculus

I have a Ph.D. in physics and speak calculus daily in my professional life. As a tutor, I liken calculus to parallel parking, or driving a car with a stick shift, or parallel parking in a car with a stick shift -- on a hill. That is, it can seem impossible at first, but any 15-year-old can learn how to do it, and after a fashion it becomes second nature. My teaching strategy for calculus is to focus on pattern recognition in problem solving. Triage is the essential first step in assessing a problem in either differential or integral calculus and they key to picking a successful solution approach. The second step is to develop good habits and rhythms in problem solving. What to write, and where, during the solution of a problem may seem trivial, but a dedication to simple repetitive gestures keeps the solution on track and minimizes errors. Finally, I emphasize that calculus solutions can nearly always be checked, so time permitting, a 100 on the calculus exam is not an unreasonable expectation for students from any discipline.
Physics,

Physics

I have a Ph.D. in physics and work professionally in biophysics and bioanalytical chemistry. (My thesis research involved the construction and characterization of computational lattice models of protein folding kinetics.) We all know more physics than we think we do. Our physical intuitions were developed in playgrounds, riding in cars, skating, riding a bike, watching water flow. As a tutor, I try to connect this already well-developed intuition with mathematical expression. It starts hard, but it gets easy quickly for most people when they pick up the rhythm of the solve. In the last six months, I have tutored a dozen students at the high school AP and college levels, both with and without calculus.
Statistics,

Statistics

I am tutoring students in both intro level statistics (basic probability, combinatorics, binomial distributions, central limit theory, normal distributions, T-tests, P-tests, hypothesis testing) and intermediate statistics (regression, correlation, F-tests, ANOVA, hierarchical clustering, principal component analysis, multivariate analysis). I use statistics everyday in my regular scientific software consulting practice, and I very much like finding the few key conceptual threads that will unravel the field for new students.
Geometry, Precalculus

Math

Biostatistics,

Biostatistics

Since 1997, I have been principally employed developing statistical methods for defining and distinguishing groups of biological test samples based on biochemical analysis. The problem has always been to answer the question "how are these samples different from those?" In my specific sub-field, the answers come in the form of biomarkers. To elucidate a biomarker, I've developed custom implementations of unsupervised hierarchical cluster analysis, principle component analysis, ANOVA, ANCOVA, linear discriminant analysis, SIMCA, and other techniques of used widely in biostatistics, chemometrics, and general data science. I use both frequentist and Bayesian methods.
Calculus,

Calculus

I have a Ph.D. in physics and speak calculus daily in my professional life. As a tutor, I liken calculus to parallel parking, or driving a car with a stick shift, or parallel parking in a car with a stick shift -- on a hill. That is, it can seem impossible at first, but any 15-year-old can learn how to do it, and after a fashion it becomes second nature. My teaching strategy for calculus is to focus on pattern recognition in problem solving. Triage is the essential first step in assessing a problem in either differential or integral calculus and they key to picking a successful solution approach. The second step is to develop good habits and rhythms in problem solving. What to write, and where, during the solution of a problem may seem trivial, but a dedication to simple repetitive gestures keeps the solution on track and minimizes errors. Finally, I emphasize that calculus solutions can nearly always be checked, so time permitting, a 100 on the calculus exam is not an unreasonable expectation for students from any discipline.
Differential Equations,

Differential Equations

I have a Ph.D. in physics. To get the degree, I've taken advanced mathematics courses in college and graduate school. In college I've had the basic 4 semester calculus sequence plus a semester of ordinary differential equations and a semester of partial differential equations. Most of electricity and magnetism is merely applied boundary value problems from ODEs. I've also taken mathematical methods courses which went deeply into complex analysis, Greens Functions formulations, Sturm-Liouville theory, hypergeometic functions, and complex analysis. I feel comfortable facing any problem in ODEs or PDEs with little or no preparation. (The same for linear algebra.) For advanced courses in Greens functions, etc., I would need to do a bit of preparation to make most efficacious use of my tutoring contact time.
Discrete Math,

Discrete Math

As a physicist and computational scientist, my knowledge of applied mathematics incorporates many topics in discrete systems: logical grammar (if p then q); techniques of proofs; recursion relations, difference equations & their solutions; matrices operations; counting, combinatorics & probability; set theory and graph theory. My Ph.D. thesis had an exact, constrained enumeration as its springboard into statistical calculations. In order to simplify the resulting complex statistics, I reduced the problem to a graph for which I developed a kinetic model. I simulated kinetics on the graph and solved the eigenvalue problem associated with a matrix chosen to approximate the graph. To this day, I reduce high dimensional problems to low dimensional ones to provide solutions for real-world problems. I'm competent to teach both theory and practice of discrete mathematics.
Electrical Engineering,

Electrical Engineering

I tutor topics in electrical engineering that spill over into applied math and computer science, including convex analysis, stochastic analysis, graph theory, network theory (Bayesian networks in particular) and signal processing.
Finite Math,

Finite Math

Finite math is discrete math for social sciences and business. As a physicist and computational scientist, my knowledge of applied mathematics incorporates many topics in discrete, finite systems: logical grammar (if p then q); recursion relations, difference equations & their solutions; simultaneous equations; counting, combinatorics & probability; set theory and graph theory. My Ph.D. thesis had an exact, constrained enumeration as its springboard into statistical calculations. I'm competent to summarize the theory and enable the practice of finite mathematics.
Linear Algebra,

Linear Algebra

I have a Ph.D in physics, and along the way I've had to learn quantum mechanics forwards and backwards. Quantum mechanics single most powerful tool is linear algebra. I've taken the college upper division course in LA, and have studied LA's theorem-proof aspects (Hermetian operators have strictly real eigenvalues, etc.) in my various math methods courses in undergraduate and graduate physics. I've also helped friends and classmates understand null spaces, orthogonal basis sets, singular value decomposition and other tricks of the LA trade. I'm confident I can handle any question in LA with minimal prep time.
Physics,

Physics

I have a Ph.D. in physics and work professionally in biophysics and bioanalytical chemistry. (My thesis research involved the construction and characterization of computational lattice models of protein folding kinetics.) We all know more physics than we think we do. Our physical intuitions were developed in playgrounds, riding in cars, skating, riding a bike, watching water flow. As a tutor, I try to connect this already well-developed intuition with mathematical expression. It starts hard, but it gets easy quickly for most people when they pick up the rhythm of the solve. In the last six months, I have tutored a dozen students at the high school AP and college levels, both with and without calculus.
Probability,

Probability

I have always managed to keep probability as simple as possible for my own work in statistical physics. I focus on the pathways rather than the rules and have scores of hours of experience tutoring probability so that it doesn't lose touch with its foundation: basic counting and fractions. Discrete binomial, multinomial and Poisson distributions; continuous normal, exponential, T, F or Chi-squared distributions; conditional, marginal, and joint distributions; Bayes theorem and inference.
R,

R

I use R/RStudio as my daily methods development environment. I exploit R's statistical and mathematical libraries for solving linear systems, performing convex optimization, evaluating frequentist hypotheses, inferring parameters through Bayesian statistics, and performing samplings and simulations. I also use R for reporting and technical document generation with R-markdown/KnitR. I'd be delighted to help you learn the R environment, including the powerful notion of R closures, and will show you some R best practices along the way.
Statistics,

Statistics

I am tutoring students in both intro level statistics (basic probability, combinatorics, binomial distributions, central limit theory, normal distributions, T-tests, P-tests, hypothesis testing) and intermediate statistics (regression, correlation, F-tests, ANOVA, hierarchical clustering, principal component analysis, multivariate analysis). I use statistics everyday in my regular scientific software consulting practice, and I very much like finding the few key conceptual threads that will unravel the field for new students.
Geometry, Precalculus, Trigonometry

Most Popular

Calculus,

Calculus

I have a Ph.D. in physics and speak calculus daily in my professional life. As a tutor, I liken calculus to parallel parking, or driving a car with a stick shift, or parallel parking in a car with a stick shift -- on a hill. That is, it can seem impossible at first, but any 15-year-old can learn how to do it, and after a fashion it becomes second nature. My teaching strategy for calculus is to focus on pattern recognition in problem solving. Triage is the essential first step in assessing a problem in either differential or integral calculus and they key to picking a successful solution approach. The second step is to develop good habits and rhythms in problem solving. What to write, and where, during the solution of a problem may seem trivial, but a dedication to simple repetitive gestures keeps the solution on track and minimizes errors. Finally, I emphasize that calculus solutions can nearly always be checked, so time permitting, a 100 on the calculus exam is not an unreasonable expectation for students from any discipline.
Physics,

Physics

I have a Ph.D. in physics and work professionally in biophysics and bioanalytical chemistry. (My thesis research involved the construction and characterization of computational lattice models of protein folding kinetics.) We all know more physics than we think we do. Our physical intuitions were developed in playgrounds, riding in cars, skating, riding a bike, watching water flow. As a tutor, I try to connect this already well-developed intuition with mathematical expression. It starts hard, but it gets easy quickly for most people when they pick up the rhythm of the solve. In the last six months, I have tutored a dozen students at the high school AP and college levels, both with and without calculus.
Statistics,

Statistics

I am tutoring students in both intro level statistics (basic probability, combinatorics, binomial distributions, central limit theory, normal distributions, T-tests, P-tests, hypothesis testing) and intermediate statistics (regression, correlation, F-tests, ANOVA, hierarchical clustering, principal component analysis, multivariate analysis). I use statistics everyday in my regular scientific software consulting practice, and I very much like finding the few key conceptual threads that will unravel the field for new students.
Geometry, Precalculus

Science

Biostatistics,

Biostatistics

Since 1997, I have been principally employed developing statistical methods for defining and distinguishing groups of biological test samples based on biochemical analysis. The problem has always been to answer the question "how are these samples different from those?" In my specific sub-field, the answers come in the form of biomarkers. To elucidate a biomarker, I've developed custom implementations of unsupervised hierarchical cluster analysis, principle component analysis, ANOVA, ANCOVA, linear discriminant analysis, SIMCA, and other techniques of used widely in biostatistics, chemometrics, and general data science. I use both frequentist and Bayesian methods.
Econometrics,

Econometrics

For nearly a year, I have helped a Ph.D. student in economics master probability, statistics, modeling, and advanced methods such as kernel density estimation, multivariate analysis, principal component analysis, hierarchical clustering, and other machine learning methods. I have also helped countless MBA and BBA students with modeling, linear programming, and other topics in analytics. While my background is in physics rather than economics, I have managed to be useful for many students who seek help understanding and using analytics tools.
Electrical Engineering,

Electrical Engineering

I tutor topics in electrical engineering that spill over into applied math and computer science, including convex analysis, stochastic analysis, graph theory, network theory (Bayesian networks in particular) and signal processing.
Physics,

Physics

I have a Ph.D. in physics and work professionally in biophysics and bioanalytical chemistry. (My thesis research involved the construction and characterization of computational lattice models of protein folding kinetics.) We all know more physics than we think we do. Our physical intuitions were developed in playgrounds, riding in cars, skating, riding a bike, watching water flow. As a tutor, I try to connect this already well-developed intuition with mathematical expression. It starts hard, but it gets easy quickly for most people when they pick up the rhythm of the solve. In the last six months, I have tutored a dozen students at the high school AP and college levels, both with and without calculus.
Physical Science

Summer

Calculus,

Calculus

I have a Ph.D. in physics and speak calculus daily in my professional life. As a tutor, I liken calculus to parallel parking, or driving a car with a stick shift, or parallel parking in a car with a stick shift -- on a hill. That is, it can seem impossible at first, but any 15-year-old can learn how to do it, and after a fashion it becomes second nature. My teaching strategy for calculus is to focus on pattern recognition in problem solving. Triage is the essential first step in assessing a problem in either differential or integral calculus and they key to picking a successful solution approach. The second step is to develop good habits and rhythms in problem solving. What to write, and where, during the solution of a problem may seem trivial, but a dedication to simple repetitive gestures keeps the solution on track and minimizes errors. Finally, I emphasize that calculus solutions can nearly always be checked, so time permitting, a 100 on the calculus exam is not an unreasonable expectation for students from any discipline.
Physics,

Physics

I have a Ph.D. in physics and work professionally in biophysics and bioanalytical chemistry. (My thesis research involved the construction and characterization of computational lattice models of protein folding kinetics.) We all know more physics than we think we do. Our physical intuitions were developed in playgrounds, riding in cars, skating, riding a bike, watching water flow. As a tutor, I try to connect this already well-developed intuition with mathematical expression. It starts hard, but it gets easy quickly for most people when they pick up the rhythm of the solve. In the last six months, I have tutored a dozen students at the high school AP and college levels, both with and without calculus.
Statistics,

Statistics

I am tutoring students in both intro level statistics (basic probability, combinatorics, binomial distributions, central limit theory, normal distributions, T-tests, P-tests, hypothesis testing) and intermediate statistics (regression, correlation, F-tests, ANOVA, hierarchical clustering, principal component analysis, multivariate analysis). I use statistics everyday in my regular scientific software consulting practice, and I very much like finding the few key conceptual threads that will unravel the field for new students.
Geometry

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Ratings and Reviews

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5.0 (1,020 ratings)
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Reviews

Best statistics teacher I've ever had

Peter is a lifesaver! I needed statistics help with my Master's thesis, and he was able to quickly understand the data I'm working with, suggest statistical tests that would be a better fit, and explain these tests in a very easy-to-understand manner! His teaching style helped me understand stats more quickly than any professor I've ever had. He was also able to identify certain biases and where the statistical results might be misleading, which helps me avoid several tough questions that could have arisen during my thesis defense. He is a fantastic tutor and I recommend him to everyone!

Jillian, 2 lessons with Peter

Very experienced and Knowledgeable!

Peter is highly skilled and knowledgeable in the area of optimizations. He possesses a wealth of expertise that makes him the go-to lecturer when you find yourself facing challenges or obstacles. His depth of knowledge and ability to explain complex concepts in a clear and concise manner make him an invaluable resource for anyone seeking guidance in this field. Peter's passion for teaching and his commitment to helping others succeed make him a trusted and respected mentor.

Nelson, 2 lessons with Peter

A knowledgeable tutor and a joy to speak with

As a beginner with R, I was struggling a bit with creating complex functions. I understood how to make simple ones (converting cm to inches, for example), but I couldn't get complex, multi-step functions to work. In an hour and 15 minutes, Peter not only helped me complete the assignment that troubled me, but also helped me understand what I was doing wrong and showed me some neat tricks to debug my code when I have problems I don't understand in the future. I would recommend Peter's services to anyone who is struggling with R.

Daniel, 1 lesson with Peter

Knowledgeable and informative

Peter helped me go over my cluster analysis and really helped me to better understand the process and results. We also had a great conversation on future academic paths and opportunities. I'd highly recommend Peter as a tutor and advisor.

John, 1 lesson with Peter

Accessible explanations!

Peter demonstrates the intuition behind concepts. Solving becomes simpler when Peter is providing foundational knowledge. He helped me with my graduate school coursework on Bayesian Statistics.

Anne, 1 lesson with Peter

Knowledgeable and patient tutor

Peter is extremely knowledgeable with the subject. Very patiently, step-by-step he worked through each problem. He understood the urgency of the situation and made time the very next day. Just to have a tutor who is proficient is very reassuring. Very methodical and makes the student understand the concepts. Highly recommended.

Jeena, 5 lessons with Peter

Superb data scientist

Peter is my go-to guy for data science; he provides clear explanations and is very responsive. He is very well versed in both R and Python. Highly recommended!

Simran, 5 lessons with Peter

Outstanding tutor

Quant. Peter L. is the best tutors I have ever had. I learn so much, thanks to him! He is patient and understandable. He has so much knowledge and experience. What a brave person. I am so pleased I got to know him!

Katherine, 4 lessons with Peter

A Real Teacher!

I’m a Master’s international student who never had an Econometrics course before. I have struggled with the course for a while as the course’s pace was too fast for me. I met Peter twice before my midterm and he actually explained almost the entire course in two sessions! He illustrated the concepts in real life easy to understand examples. He was patient, understanding, and he was also funny. Thanks to Peter, I actually got an A+ on my midterm!

Bashera, 2 lessons with Peter

Knowledgeable and helpful tutor

Peter helped me with Econometrics, he helped me by providing answers to my questions both by words and numbers, so I have more options to absorb the material that way.

Rafael, 3 lessons with Peter
Hourly Rate: $115
Response time: 2 hours
Contact Peter