VOLUME I
Coming Soon
Statistical
Thinking.
A native, interactive desktop application designed to build intuition for uncertainty and inference. Read the theory, manipulate visual models, and write real Python code to uncover the mechanics of probability that govern the real world.
STATISTICAL THINKING
APP
Case Studies
Data has a story. We find the ending.
Real clinical data. A real regression model. A real p-value that decides whether your blood pressure prediction is statistically meaningful — or just noise. Follow along step by step.
Browse the ArchiveReal-time Predictor
Live Data
Predicted Pressure
134.2
Hypertensive Stage 1
BSA Index
1.82 m²
Duration
4.5 yrs
N=72,000 OBS
R² = 0.89
Workshop
The math is right. Prove it with code.
Translating intuition into a working hypothesis test is where most students get lost. The Workshop gives you a live Python environment to run the actual test — import scipy, compute the p-value, and see the statistics speak.
Enter the WorkshopResearch_Log.ipynb
# Verify the Null Hypothesis
import numpy as np
from scipy import stats
# Draw from a population
sample = np.random.normal(mu=0, sigma=1, n=30)
def test_hypothesis(data):
t, p = stats.ttest_1samp(data, 0)
return f"p={p:.4f}"