Course Overview:
Probability Theory Tutor in Delhi and is the mathematical study of randomness, uncertainty, and chance. It provides the foundation for statistics, data science, machine learning, actuarial science, operations research, and risk management. This course equips students with the tools to model random events, compute probabilities, and analyze random variables and their distributions.

Probability Theory Tutor in Delhi

Syllabus Outline

1. Fundamentals of Probability

• Basic concepts: experiments, outcomes, sample space, and events
• Axioms of probability and properties
• Conditional probability and independence
• Bayes’ theorem and applications

2. Combinatorial Probability

• Counting techniques: permutations and combinations
• Probability in finite sample spaces
• Classical probability problems (e.g., cards, dice, urn models)

3. Random Variables

• Discrete and continuous random variables
• Probability mass function (PMF) and probability density function (PDF)
• Cumulative distribution function (CDF)
• Expectation, variance, and higher moments

4. Standard Probability Distributions

• Discrete distributions: Bernoulli, Binomial, Geometric, Poisson, Negative Binomial
• Continuous distributions: Uniform, Exponential, Normal, Gamma, Beta
• Properties and applications of these distributions

5. Joint Distributions

• Joint, marginal, and conditional distributions
• Covariance and correlation
• Functions of random variables
• Moment generating functions (MGFs)

6. Limit Theorems

• Law of Large Numbers (LLN)
• Central Limit Theorem (CLT) and its importance

7. Advanced Topics (optional depending on course level)

• Markov chains and stochastic processes
• Conditional expectation
• Inequalities in probability (Chebyshev’s, Jensen’s, etc.)

probability theory tutor in delhi

By the end of the course, students will be able to:

• Apply probability rules to solve real-world problems.
• Model random phenomena using discrete and continuous distributions.
• Compute expectations, variances, and correlations.
• Understand and use the Central Limit Theorem in approximation.
• Build a strong mathematical foundation for further study in statistics, data science, and machine learning.
• 🌟 Why Learn Probability Theory?
  Probability Theory is the mathematics of uncertainty. It forms the backbone of statistics, data science, artificial intelligence, finance, risk analysis, and engineering. Whether you’re a high school student preparing for exams, a college student tackling probability courses, or a professional upgrading your skills, mastering probability is essential.
  
  🎯 What I Offer in Probability Tutoring
  Foundations Made Simple – Learn the core concepts: sample spaces, events, and probability rules.
  Step-by-Step Problem Solving – From basic probability puzzles to advanced theorems.
  Exam Preparation – Targeted practice for school, college, and competitive exams.
  Real-Life Applications – Understand how probability works in gambling, insurance, machine learning, and decision-making.
  Customized Learning – Lessons tailored to your pace, level, and academic goals.