1.ipynb

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    "$u$ will be the unmeasured variable that causes a person to enter into the test. $u$ will just be the propensity to visit. \n",
    "\n",
    "We'll use $u$ to get $vi$, which is a binary variable for whether or not the user visits at time $t_i$, and then calculate the treatment assignment $a$. The assignment variable will have three states, even though this is an AB test! This is one of the key differences. We're assigning to all site users, $U$, and not just the ones entering the test, $T$. The assignments are 2 (test group), 1 (control group), and 0 (not assigned). The user is assigned whenever they visit the site.\n",
    "\n",
    "Notice $a=0$ whenever $v_i=0$: if a user doesn't visit the site ($v_i=0$) then they can't be assigned to test or control (so $a=0$).  $a$ is 1 (control) or 2 (test) otherwise."
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    "u = 1. / (1. + np.exp(-np.random.normal(size=N)))\n",
    "vi = np.random.binomial(1, u)\n",
    "a = vi*(1+np.random.binomial(1, 0.5, size=N))"
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