Probability & Statistics for Quant Interviews

Master probability and statistics with our comprehensive collection of 100+ practice problems, step-by-step solutions, and real interview questions from Jane Street, Citadel, Two Sigma, and other top quantitative trading firms.

Core Probability & Statistics Topics

Basic Probability

Fundamental probability concepts, sample spaces, and basic calculations.

  • • Sample spaces and events
  • • Probability axioms
  • • Combinatorics
  • • Basic probability rules
Conditional Probability

Bayes' theorem, independence, and conditional probability applications.

  • • Bayes' theorem
  • • Independence
  • • Conditional expectation
  • • Medical testing problems
Distributions

Common probability distributions and their applications in finance.

  • • Normal distribution
  • • Binomial distribution
  • • Poisson distribution
  • • Exponential distribution
Expected Value

Expected value calculations, variance, and risk assessment.

  • • Expected value formulas
  • • Variance and standard deviation
  • • Risk-return analysis
  • • Portfolio optimization
Hypothesis Testing

Statistical hypothesis testing and significance testing.

  • • Null and alternative hypotheses
  • • P-values
  • • Type I and Type II errors
  • • Confidence intervals
Regression Analysis

Linear regression, correlation, and statistical modeling.

  • • Linear regression
  • • Correlation coefficients
  • • R-squared
  • • Residual analysis

Practice Problems

Coin Flipping Problem
Easy
Classic probability problem

Question:

You flip a fair coin 10 times. What's the probability of getting exactly 7 heads?

Solution:

Use binomial probability: P(X=7) = C(10,7) × (0.5)^7 × (0.5)^3 = 120 × (0.5)^10 = 120/1024 ≈ 0.117

Bayes' Theorem Problem
Medium
Medical testing scenario

Question:

A disease affects 1% of the population. A test is 99% accurate for both positive and negative cases. If someone tests positive, what's the probability they actually have the disease?

Solution:

P(Disease|Positive) = P(Positive|Disease) × P(Disease) / P(Positive) = 0.99 × 0.01 / (0.99 × 0.01 + 0.01 × 0.99) = 0.5

Expected Value Problem
Hard
Gambling scenario

Question:

You roll a die until you get a 6. What's the expected number of rolls?

Solution:

E[X] = 1/p = 1/(1/6) = 6 rolls. This is the expected value of a geometric distribution.

Firm-Specific Probability Problems

Jane Street Problems
Market making and probability
  • • Coin flipping until consecutive heads
  • • Expected value of trading strategies
  • • Risk management scenarios
  • • Market microstructure problems
Citadel Problems
Advanced statistical modeling
  • • Complex probability trees
  • • Statistical inference
  • • Monte Carlo simulations
  • • Risk modeling
Two Sigma Problems
Data science and statistics
  • • Statistical significance testing
  • • Regression analysis
  • • Machine learning probability
  • • A/B testing scenarios

Probability & Statistics Study Guide

8-Week Study Plan
Comprehensive preparation for probability and statistics interviews

Weeks 1-2: Fundamentals

  • • Basic probability rules and axioms
  • • Combinatorics (permutations, combinations)
  • • Sample spaces and events
  • • Conditional probability basics

Weeks 3-4: Advanced Probability

  • • Bayes' theorem and applications
  • • Independence and conditional independence
  • • Expected value and variance
  • • Common probability distributions

Weeks 5-6: Statistics

  • • Descriptive statistics
  • • Hypothesis testing
  • • Confidence intervals
  • • P-values and significance

Weeks 7-8: Applications

  • • Regression analysis
  • • Correlation and causation
  • • Financial applications
  • • Mock interviews and practice

Frequently Asked Questions

What probability topics are most important for quant interviews?

Focus on conditional probability, Bayes' theorem, expected value calculations, common distributions (normal, binomial, Poisson), and basic combinatorics. These topics appear in 80% of quant interviews.

How should I approach probability problems in interviews?

Start by clearly defining the sample space and events. Use systematic approaches like tree diagrams or Bayes' theorem. Always explain your reasoning step by step and check your answer makes intuitive sense.

What's the best way to practice probability problems?

Practice with real interview questions from top firms. Focus on understanding the underlying concepts rather than memorizing formulas. Time yourself to simulate interview pressure and practice explaining solutions out loud.

Master Probability & Statistics Today
Practice with 100+ probability and statistics problems, get step-by-step solutions, and ace your quantitative trading interviews.