A/B testing & experimentation
User bucketing, experiment metrics, statistical comparison, and rollout guardrails.
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.
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…Synthetic Control in Python: Mock Example
Implements synthetic control from scratch: learns donor weights via ridge regression on pre-period data, then predicts a counterfactual for the treated unit.
import numpy as np
class SyntheticControl:
def __init__(self, data, treated_index, pre_periods, post_periods):
self.data = np.array(data, dtype=float)
self.treated_index = treated_index
self.pre_periods = pre_periods
self.post_periods = post_periods
def fit_weights(sel…Browse by section
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A/B testing & experimentation — Python code examples
What you will find here
This page collects a/b testing & experimentation snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
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Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.