Jay Kaushik

Master Mathematics with Structured, Exam-Focused & Concept-Driven Learning Pro

4.8(32)

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Jay Kaushik

Masters degree

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Each lesson is 55 min

50 lessons


20% off

/ lesson

30 lessons


15% off

/ lesson

20 lessons


10% off

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10 lessons


5% off

/ lesson

5 lessons


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/ lesson

1 lessons


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/ lesson

Jay - Know your tutor

With over 7 years of experience in teaching Mathematics, I specialize in concept-based, personalized instruction for students from Classes 9–12 across CBSE, ICSE, IB, and competitive exam tracks. My expertise covers Algebra, Trigonometry, Coordinate Geometry, Calculus, Probability, Statistics, and Mathematical Reasoning, with strong emphasis on problem-solving techniques and exam-oriented strategies. I design structured learning plans tailored to each student’s strengths and learning pace, incorporating step-by-step explanations, regular practice sets, doubt-clearing sessions, and exam simulations. My teaching approach focuses on building strong fundamentals, logical thinking, and confidence, helping students transition from basic understanding to advanced application. I support students with homework, assignments, board exam preparation, and competitive exam readiness, ensuring clarity, accuracy, and consistent improvement in performance.

Jay graduated from NSUT ( Netaji Shubas University of Technology )

Jay  graduated from NSUT ( Netaji Shubas University of Technology )
Jay  graduated from NSUT ( Netaji Shubas University of Technology )

Specialities of your tutor

Practice Tests icon

Practice Tests

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Test prep strategies

Learning Plans icon

Learning Plans

Test Strategy icon

Test Strategy

Problem Solving icon

Problem Solving

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Quick Math Games

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Practice Drills

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Exam Simulation

International Baccalaureate (IB) icon

International Baccalaureate (IB)

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Gamification of Math

Common Core State Standards - CCSS (USA) icon

Common Core State Standards - CCSS (USA)

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Homework help

Student types for classes

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Mathematics for Kids

Learning Disabilities icon

Learning Disabilities

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ASD

Anxiety or Stress Disorders icon

Anxiety or Stress Disorders

High School students icon

High School students

Mathematics for Beginners icon

Mathematics for Beginners

Elementary School students icon

Elementary School students

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Home schooled

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ADHD

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Middle School students

Class overview

My teaching methodology in Mathematics is structured, concept-driven, and student-centric. I begin by assessing a student’s current understanding and learning style, then design a customized study plan with clear short-term and long-term goals. Each topic is introduced from first principles, ensuring strong conceptual clarity before moving to formulas and applications. I emphasize step-by-step problem-solving, logical reasoning, and multiple solution approaches to develop analytical thinking. Regular practice through graded assignments, worksheets, and exam-oriented questions is combined with periodic tests and detailed feedback. I use real-life examples, visual explanations, and error-analysis techniques to address misconceptions and improve accuracy. Continuous doubt-solving, revision strategies, and progress tracking ensure steady improvement, confidence building, and strong exam performance.

Jay also teaches

Discrete Math

Discrete Math

Elementary School Math

Elementary School Math

Geometry

Geometry

High School Math

High School Math

Linear Algebra

Linear Algebra

Middle School Math

Middle School Math

Flexible Scheduling

Allows 1h early scheduling

Allows 1h early rescheduling

Can wait for 20 mins after joining

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10 day Refund

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Mathematics concepts taught by Jay

Student learned 3 days ago

The Tutor and Student delved into Chapter 7, focusing on the distribution of sample means and the Central Limit Theorem. They practiced calculating sampling error, standard error, and z-scores for sample means, and determining probabilities associated with them. The session concluded with a plan for the Student to complete practice assignments over the next three days.

Distribution of Sample Means

Sampling Error

Central Limit Theorem (CLT)

Standard Error (SE)

Z-Score for Sample Means

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Student learned 4 days ago

The Tutor and Student began a new topic, probability, explaining its role as a bridge between samples and populations and its basic definition and properties. They then covered random sampling, probability graphs, normal distributions, and the use of the Unit Normal Table to find probabilities using z-scores. The session ended with practicing calculations for finding probabilities of raw scores and finding scores from probabilities, and planning to cover Chapter 7 next.

The Bridge Between Samples and Population

Z-Scores and the Unit Normal Table

Normal Distribution and the Bell Curve

Random Sampling: The Foundation for Reliable Probability

The Range of Probability: Zero to One

Defining Probability: A Simple Fraction

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Student learned 5 days ago

The tutor and student continued their study of logarithmic functions, focusing on evaluating logarithmic expressions, applying logarithm properties, and understanding the base change formula. They practiced converting bases and determining the sign of logarithmic values, with plans to continue further math topics after a week off.

Evaluating Logarithms

Logarithm Properties for Evaluation

Change of Base Formula

Determining the Sign of a Logarithm

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Student learned 5 days ago

The session focused on teaching the concept of z-scores, including their calculation, interpretation, and application in standardizing distributions and inferential statistics. The student practiced calculating z-scores and worked through problems related to transforming scores and determining population parameters.

Z-Scores in Inferential Statistics

Standardized Distributions

Z-Score: Purpose and Interpretation

Calculating the Z-Score

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Student learned 7 days ago

The class reviewed key statistical concepts from Chapters 3 and 4, focusing on measures of central tendency (mean, median, mode) and variability (range, standard deviation). The tutor guided the student through formulas and calculation steps, including a detailed explanation of how to compute standard deviation using both definitional and computational formulas for populations and samples. The session concluded with a plan to begin Chapter 5 in the next class.

Variability

Standard Deviation Calculation Methods

Population vs. Sample Standard Deviation

Central Tendency

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Student learned 8 days ago

The Tutor and Student reviewed the concept of logarithmic functions as inverses of exponential functions. They practiced converting between these forms, identified domain and range, and worked through various practice problems from an assignment booklet to solidify their understanding.

Logarithmic Functions as Inverses

Conditions for Logarithms

Graphing Logarithmic Functions

Common and Natural Logarithms

Solving Logarithmic Equations

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Teaching tools used by tutor

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Lesson Planning Tools

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Quizzes

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Lesson Planner

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Digital whiteboard

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Graphing Tools

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Solvers & Calculators

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Practice worksheets

Interactive lessons

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Parent feedback

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Record lessons

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Weekend lessons

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Note taking

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Open Q&A

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Every tutor is interviewed and selected for subject expertise and teaching skill.