Math Tutor with Exam Prep, Practice Drills, Test Strategies
Private tutor - Soumya Aggarwal
Masters degree
$28
$26
/ hour
Improved problem-solving skills
90% of students report faster and more efficient problem-solving.
Trusted by 90% of parents
Parents see their child’s grades improving within a few months.
Focus on real-world applications
85% of students find math concepts more relevant to real-life problems.
About your tutor
I’m Soumya Aggarwal, a passionate and committed Mathematics tutor with a strong academic background. I hold a Bachelor’s in Economics (Honours), an M.Com, a B.Ed., and an M.A. in Psychology. My academic journey has deeply shaped my approach to teaching—analytical, empathetic, and student-centered. Over the years, I’ve developed a teaching style that focuses on: Concept clarity over rote learning Interactive problem-solving Step-by-step guidance tailored to individual learning speeds I believe that every student can master Maths when it’s taught with patience, simplicity, and real-life context. I aim to build not just subject knowledge but also confidence and curiosity in my students. My sessions include regular practice, doubts clarification, and periodic assessments to ensure continuous progress. I blend traditional methods with modern tools to keep learning both effective and engaging. Teaching, for me, is not just about formulas and equations—it's about unlocking potential and helping each student realize that they are capable of more than they think.
Specialities of your tutor
Quick Math Games
New Zealand Curriculum - NZC (NZ)
A-Levels (UK)
Gamification of Math
Test Strategy
Learning Plans
Australian Curriculum (AU)
Test prep strategies
Problem Solving
Mental Math
Class overview
As a Mathematics tutor, I follow a concept-driven, student-focused teaching methodology that blends academic rigor with psychological understanding. 🧠 1. Conceptual Clarity First I strongly believe that when students understand the why behind the how, they gain confidence. I break down every topic into simple, logical steps and use real-life examples to make abstract concepts relatable. 📊 2. Structured & Progressive Learning My classes follow a well-planned structure: Foundation Building: Revisiting basics where required Step-by-Step Progression: Gradually moving from easy to complex Practice-Oriented Learning: Focus on problem-solving through guided and independent practice 💬 3. Interactive Sessions I encourage two-way communication. Students are free to ask doubts at any time, and I ensure they are never afraid to make mistakes—that’s where real learning happens. 🧩 4. Psychology-Based Support With my background in Psychology, I’m sensitive to the emotional and cognitive needs of learners. I adapt my teaching style according to each student’s pace and mindset, helping them overcome fear and mental blocks related to Maths. 📝 5. Regular Testing & Feedback Frequent short quizzes and assignments for retention Feedback loops to address weaknesses and reinforce strengths Continuous performance tracking for parents and students 🎯 6. Application & Relevance Whether it’s a class test or competitive exam, I help students connect what they learn to practical applications, improving both their exam performance and real-world understanding.
Student types for classes
Kids
Beginners
Middle School students
Elementary School students
ADHD
Anxiety or Stress Disorders
Home schooled
Interactive lessons
Record lessons
Note taking
Pets are welcomed
Parent feedback
Mobile joining
Teaching tools used by tutor
Assessment
Practice worksheets
Lesson Planning Tools
Quizzes
Solvers & Calculators
Digital whiteboard
Math Games
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Your tutor also teaches
Elementary School Math
Geometry
Middle School Math
Probability
Statistics
Trigonometry
Free lesson slots
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Mathematics concept taught by Soumya
Soumya and Harjot reviewed econometrics, including R-squared, tests for heteroscedasticity (White, Breusch-Pagan), autocorrelation (Breusch-Godfrey), time series forecasting, and long-run multiplier effects. They worked through practice questions, focusing on hypothesis testing and model assumptions. They plan to review the material further and scheduled the next class.
Long-Run Multiplier
R-squared vs. Adjusted R-squared
White Test for Heteroskedasticity
Breusch-Godfrey Test for Autocorrelation
Soumya Aggarwal tutored Harjot Kaur, guiding her through a practice economics exam covering regression analysis, hypothesis testing, and model specification. They worked through multiple-choice and short-answer questions, focusing on understanding the underlying concepts and formulas. Soumya assigned Harjot to review the material and practice problems, with a follow-up session scheduled for the next day to continue exam preparation.
Multiple Choice Strategies
Null and Alternative Hypothesis
T-tests
Confidence Intervals
Soumya assisted Harjot in preparing for an upcoming exam by reviewing key concepts in time series analysis, including serial correlation, the Breusch-Godfrey test, HAC standard errors, and static vs. dynamic models. Harjot is working on practice questions to reinforce these concepts. They scheduled another session for Wednesday to complete the remaining topics and address any questions Harjot may have.
HAC Standard Errors
Static vs. Dynamic Models
Trend
Seasonality
Soumya Aggarwal tutored Harjot Kaur on heteroscedasticity, covering its definition, consequences, detection through informal and formal tests (Breusch-Pagan and White tests), and methods to address it. They also introduced serial correlation. Harjot was assigned questions on heteroscedasticity tests, and their next class is scheduled for Tuesday.
Breusch-Pagan Test
White Test
Special White Test & Fixing Heteroscadasticity
Serial Correlation
Cyclic Quadrilateral
Angle in a Semicircle
Inscribed Angle Theorem
Angles in the Same Segment
Harjot tutored Soumya on OLS properties and assumptions, covering topics such as multiple linear regression, R-squared, the OLS estimator, orthogonality, the BLUE property, and the classical linear regression assumptions. They also discussed the implications of zero error, normally distributed errors, the Law of Iterated Expectations, and the variance of the OLS estimator. Their plan is to complete tutorials 7 and 8.
Variance of OLS Estimator
BLUE Property of OLS
Classical Linear Regression Assumptions
Linearity in Parameters