Reference library

A/B testing & experimentation

User bucketing, experiment metrics, statistical comparison, and rollout guardrails.

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A/B testing & experimentation medium

Bayesian A/B Test Credible Interval in Python

Simulates A/B test data and computes posterior credible intervals and the probability that variant B outperforms A using Bayesian Beta-Binomial inference.

bayesian ab-testing credible-interval
Python
import numpy as np
from scipy import stats

# Simulated A/B test data
n_A = 1000
n_B = 1000
conversions_A = 120
conversions_B = 140

# Prior: Beta(1, 1) uniform
alpha_prior, beta_prior = 1, 1

# Posterior parameters
alpha_A = alpha_prior + conversions_A
beta_A = beta_prior + n_A - conversions_A
alpha_B = alpha_prior +…
15 0 Open
A/B testing & experimentation medium

Benjamini Hochberg FDR Correction in Python

Implement the Benjamini-HHochberg false discovery rate (FDR) procedure in Python to control the expected proportion of false positives among rejected hypotheses.

fdr multiple testing hypothesis testing
Python
import numpy as np

def benjamini_hochberg(p_values, alpha=0.05):
    p_values = np.array(p_values)
    n = len(p_values)
    sorted_idx = np.argsort(p_values)
    sorted_p = p_values[sorted_idx]
    
    thresholds = (np.arange(1, n + 1) / n) * alpha
    significant = sorted_p <= thresholds
    
    if not significan…
15 0 Open
A/B testing & experimentation medium

How to Create an Interrupted Time Series Mock in Python

Generate simulated interrupted time series data with a pre/post-intervention trend, level shift, and noise to test segmented regression models.

interrupted-time-series simulation numpy
Python
import numpy as np

# Mock interrupted time series data
np.random.seed(42)
n_pre = 50
n_post = 50
time = np.arange(0, n_pre + n_post)

# Pre-intervention: linear trend + noise
pre_trend = 0.05 * time[:n_pre] + np.random.normal(0, 0.5, n_pre)

# Post-intervention: new slope + level shift + noise
post_trend = 0.05 * tim…
15 0 Open
A/B testing & experimentation medium

How to Generate an Orthogonal Array for A/B Testing in Python

Generate a mock orthogonal array for multi-layer experiments with NumPy, ensuring balanced level combinations across experiment groups.

ab-testing orthogonal-array numpy
Python
import numpy as np

def orthogonal_mock_layers(n_experiments: int, n_layers: int, n_levels: int) -> np.ndarray:
    """Generate an orthogonal array for multi-layer experiment design using base-level logic."""
    ortho = np.indices((n_levels,) * n_layers).reshape(n_layers, -1).T
    ortho = ortho % n_levels  # Classic…
14 0 Open
A/B testing & experimentation medium

Thompson Sampling Mock Bandit in Python

Implement a Thompson sampling multi-armed bandit to explore and exploit reward probabilities across multiple options, updating Beta distributions over time.

thompson-sampling bandit-algorithms exploration-exploitation
Python
import random

class ThompsonSamplingBandit:
    def __init__(self, num_arms, alpha=1.0, beta=1.0):
        self.num_arms = num_arms
        self.alpha = [alpha] * num_arms
        self.beta = [beta] * num_arms

    def select_arm(self):
        samples = [random.betavariate(a, b) for a, b in zip(self.alpha, self.beta…
12 0 Open

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A/B testing & experimentation — Python code examples

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