Steve Zelaznik zelaznik

Attempt #2, Using Normal Distribution

Find the combined click-through rate:

$$\widehat{\mu} = \frac{k_a + k_b}{n_a + n_b} = \frac{10 + 13}{100 + 100} = \frac{23}{200} = 0.115 $$

Find the variance of the click through rate:

You can look up the mean and variance of a distribution on Wikipedia. This is the distribution of a single visitor and whether this visitor signs up (1) or not (0).

A/B Testing Statistics

Find the average click through rate:

We're assuming the opposite, so we're assuming there's one average click through rate for both pages:

$$\widehat{\mu} = \frac{k_a + k_b}{n_a + n_b} = \frac{10 + 13}{100 + 100} = \frac{23}{200} = 0.115 $$

Now we also have to find the variance of the click through rate:

Power is Nothing Without Control

Using Deterministic Controls to Harness the Power of Agentic AI

The Anchor

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https://www.alamy.com/stock-photo-1990s-uk-pirelli-magazine-advert-85361428.html?imageid=FF50E53A-9F51-4B71-9235-322BE9B7D5DE&pn=1&searchId=8d875d0f24101d78cd7ffdc386cb1009&searchtype=0

	CREATE OR REPLACE FUNCTION my_count_state(state integer, value anyelement)
	RETURNS integer AS $$
	BEGIN
	IF value IS NOT NULL THEN
	RETURN state + 1;
	ELSE
	RETURN state;
	END IF;
	END;
	$$ LANGUAGE plpgsql;

	CREATE TYPE avg_state AS (
	total numeric,
	count integer
	);

	CREATE OR REPLACE FUNCTION my_avg_state(state avg_state, value numeric)
	RETURNS avg_state AS $$
	BEGIN
	IF value IS NOT NULL THEN
	state.total := state.total + value;

	// A pure Javscript implementation of binomial distribution
	// This is for educational purposes. These numbers can become unreliable
	// when the numerators and denominators get too big. This is because
	// of floating point arithmetic.
	//
	// Use a more robust statistical library for mission critical calculations

	function factorial(n) {
	let total = 1;
	for(let i=n; i>1; i--) {

	#!/usr/bin/env bash
	# red-green-refactor-validator.sh
	# Validates test-driven development red-green-refactor workflow
	#
	# Exit codes:
	# 0 - Validation successful (tests failed on old code, passed on new code)
	# 1 - Validation failed (no tests changed, or tests didn't follow red-green pattern)
	# 2 - Precondition failed (unstaged changes exist)
	# 3 - Script error (stash/restore failed)