Monte Carlo Simulation Engine · Statistical Toolkit
Landing page with animated moving-gradient navbar
Discrete Lab — Binomial, Geometric, Poisson (with animate button)
Continuous Lab — Normal, Exponential, Gamma, Beta, Uniform, Chi-Squared, Student-t
Hypothesis Testing — One-sample Z/T, Two-sample T, Chi-Square (GoF + Independence)
Confidence Intervals — Z-interval, T-interval, Wilson Proportion CI, Variance CI, Coverage Simulation
Bayes Theorem — Classic, Sequential updating, Beta-Binomial conjugate
Combinatorics — nPr, nCr, Multinomial, Birthday Problem, List Generator
probability_lab/
├── app_sr.py ← main app (run this)
├── requirements.txt
├── core/
│ ├── __init__.py
│ └── distributions.py ← all simulators + theory curves
└── tools/
├── __init__.py
└── stats_tools.py ← hypothesis tests, CIs, Bayes, combinatorics
git clone < your-repo>
cd probability_lab
python3 -m venv venv
source venv/bin/activate # macOS/Linux
venv\S cripts\a ctivate # Windows
pip install -r requirements.txt
streamlit run app_sr.py
Distribution
Parameters
Formula
Binomial
n, p
P(X=k) = C(n,k)pᵏ(1-p)ⁿ⁻ᵏ
Geometric
p
P(X=k) = (1-p)ᵏ⁻¹p
Poisson
λ
P(X=k) = e⁻λλᵏ/k!
〰️ Continuous Distributions
Distribution
Parameters
Normal
μ, σ
Exponential
λ
Gamma
k, θ
Beta
α, β
Uniform
a, b
Chi-Squared
df
Student-t
df
Z-test — one-sample with known σ
T-test — one-sample and two-sample
Chi-Square — goodness of fit + independence
Rejection region visualizations, p-values, critical values
Z-interval (known σ)
T-interval (unknown σ)
Wilson CI for proportions
Chi-square CI for variance
Coverage probability simulation
Classic P(H|E) calculator
Sequential Bayesian updating animation
Beta-Binomial conjugate prior/posterior
nPr, nCr with/without repetition
Pascal's Triangle visualization
Multinomial coefficients
Birthday problem curve
Full combination/permutation list generator
Built with Python · Streamlit · NumPy · SciPy · Matplotlib · plotly