probabilistic-analysis-toolkit

# Probabilistic Analysis Toolkit ## Purpose Provides expert guidance on analyzing randomized algorithms using probability theory and concentration inequalities. ## Capabilities - Expected value calculations - Chernoff and Hoeffding bound applications - Markov and Chebyshev inequality analysis - Moment generating function analysis - Concentration inequality selection - Las Vegas and Monte Carlo analysis ## Usage Guidelines 1. **Random Variable Identification**: Define relevant random variables 2. **Expectation Computation**: Calculate expected values 3. **Concentration Selection**: Choose appropriate bounds 4. **Bound Application**: Apply concentration inequalities 5. **Result Interpretation**: Interpret probabilistic guarantees ## Tools/Libraries - Symbolic probability - Statistical libraries - SymPy