{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(BEST)=\n",
    "# Bayesian Estimation Supersedes the T-Test\n",
    "\n",
    ":::{post} Jan 07, 2022\n",
    ":tags: hypothesis testing, model comparison, \n",
    ":category: beginner\n",
    ":author: Andrew Straw, Thomas Wiecki, Chris Fonnesbeck, Andrés suárez\n",
    ":::"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on PyMC v5.28.0+58.gf58491a3\n"
     ]
    }
   ],
   "source": [
    "import arviz as az\n",
    "import numpy as np\n",
    "import preliz as pz\n",
    "import pymc as pm\n",
    "import xarray as xr\n",
    "\n",
    "print(f\"Running on PyMC v{pm.__version__}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%config InlineBackend.figure_format = 'retina'\n",
    "az.style.use(\"arviz-variat\")\n",
    "rng = np.random.default_rng(seed=42)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Problem\n",
    "\n",
    "This model replicates the example used in **Bayesian estimation supersedes the t-test** {cite:p}`kruschke2013`.\n",
    "\n",
    "Several statistical inference procedures involve the comparison of two groups. We may be interested in whether one group is larger than another, or simply different from the other. We require a statistical model for this because true differences are usually accompanied by measurement or stochastic noise that prevent us from drawing conclusions simply from differences calculated from the observed data. \n",
    "\n",
    "The *de facto* standard for statistically comparing two (or more) samples is to use a statistical test. This involves expressing a null hypothesis, which typically claims that there is no difference between the groups, and using a chosen test statistic to determine whether the distribution of the observed data is plausible under the hypothesis. This rejection occurs when the calculated test statistic is higher than some pre-specified threshold value.\n",
    "\n",
    "Unfortunately, it is not easy to conduct hypothesis tests correctly, and their results are very easy to misinterpret. Setting up a statistical test involves several subjective choices (*e.g.* statistical test to use, null hypothesis to test, significance level) by the user that are rarely justified based on the problem or decision at hand, but rather, are usually based on traditional choices that are entirely arbitrary {cite:p}`johnson1999`. The evidence that it provides to the user is indirect, incomplete, and typically overstates the evidence against the null hypothesis {cite:p}`goodman1999`. \n",
    "\n",
    "A more informative and effective approach for comparing groups is one based on **estimation** rather than **testing**, and is driven by Bayesian probability rather than frequentist. That is, rather than testing whether two groups are different, we instead pursue an estimate of how different they are, which is fundamentally more informative. Moreover, we include an estimate of uncertainty associated with that difference which includes uncertainty due to our lack of knowledge of the model parameters (epistemic uncertainty) and uncertainty due to the inherent stochasticity of the system (aleatory uncertainty)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example: Drug trial evaluation\n",
    "\n",
    "To illustrate how this Bayesian estimation approach works in practice, we will use a fictitious example from {cite:t}`kruschke2013` concerning the evaluation of a clinical trial for drug evaluation. The trial aims to evaluate the efficacy of a \"smart drug\" that is supposed to increase intelligence by comparing IQ scores of individuals in a treatment arm (those receiving the drug) to those in a control arm (those receiving a placebo). There are 47 individuals and 42 individuals in the treatment and control arms, respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2400x535.887 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 559,
       "width": 2423
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fmt: off\n",
    "iq_drug = np.array([\n",
    "    101, 100, 102, 104, 102, 97, 105, 105, 98, 101, 100, 123, 105, 103, \n",
    "    100, 95, 102, 106, 109, 102, 82, 102, 100, 102, 102, 101, 102, 102,\n",
    "    103, 103, 97, 97, 103, 101, 97, 104, 96, 103, 124, 101, 101, 100,\n",
    "    101, 101, 104, 100, 101\n",
    "])\n",
    "\n",
    "iq_placebo = np.array([\n",
    "    99, 101, 100, 101, 102, 100, 97, 101, 104, 101, 102, 102, 100, 105,\n",
    "    88, 101, 100, 104, 100, 100, 100, 101, 102, 103, 97, 101, 101, 100,\n",
    "    101, 99, 101, 100, 100, 101, 100, 99, 101, 100, 102, 99, 100, 99\n",
    "])\n",
    "# fmt: on\n",
    "dt = xr.Dataset({\"iq_drug\": ([\"drug\"], iq_drug), \"iq_placebo\": ([\"placebo\"], iq_placebo)})\n",
    "az.plot_dist(dt, kind=\"ecdf\", sample_dims=[\"drug\", \"placebo\"]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first step in a Bayesian approach to inference is to specify the full probability model that corresponds to the problem. For this example, Kruschke chooses a Student-t distribution to describe the distributions of the scores in each group. This choice adds robustness to the analysis, as a T distribution is less sensitive to outlier observations, relative to a normal distribution. The three-parameter Student-t distribution allows for the specification of a mean $\\mu$, a precision (inverse-variance) $\\lambda$ and a degrees-of-freedom parameter $\\nu$:\n",
    "\n",
    "$$f(x|\\mu,\\lambda,\\nu) = \\frac{\\Gamma(\\frac{\\nu + 1}{2})}{\\Gamma(\\frac{\\nu}{2})} \\left(\\frac{\\lambda}{\\pi\\nu}\\right)^{\\frac{1}{2}} \\left[1+\\frac{\\lambda(x-\\mu)^2}{\\nu}\\right]^{-\\frac{\\nu+1}{2}}$$\n",
    "           \n",
    "The degrees-of-freedom parameter essentially specifies the \"normality\" of the data, since larger values of $\\nu$ make the distribution converge to a normal distribution, while small values (close to zero) result in heavier tails. Thus, the likelihood functions of our model are specified as follows:\n",
    "\n",
    "$$y^{(treat)}_i \\sim T(\\nu, \\mu_1, \\sigma_1)$$\n",
    "\n",
    "$$y^{(placebo)}_i \\sim T(\\nu, \\mu_2, \\sigma_2)$$\n",
    "\n",
    "As a simplifying assumption, we will assume that the degree of normality $\\nu$ is the same for both groups. We will, of course, have separate parameters for the means $\\mu_k, k=1,2$ and standard deviations $\\sigma_k$. Since the means are real-valued, we will apply normal priors on them, and arbitrarily set the hyperparameters to the pooled empirical mean of the data and twice the pooled empirical standard deviation, which applies very diffuse information to these quantities (and importantly, does not favor one or the other *a priori*).\n",
    "\n",
    "$$\\mu_k \\sim N(\\bar{x}, 2s)$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "mu_m = dt.to_array().mean().item()\n",
    "mu_s = dt.to_array().std().item() * 2\n",
    "\n",
    "with pm.Model() as model:\n",
    "    group1_mean = pm.Normal(\"group1_mean\", mu=mu_m, sigma=mu_s)\n",
    "    group2_mean = pm.Normal(\"group2_mean\", mu=mu_m, sigma=mu_s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The group standard deviations will be given a uniform prior over a plausible range of values for the variability of the outcome variable, IQ.\n",
    "\n",
    "In Kruschke's original model, he uses a very wide uniform prior for the group standard deviations, from the pooled empirical standard deviation divided by 1000 to the pooled standard deviation multiplied by 1000. This is a poor choice of prior, because very basic prior knowledge about measures of human coginition dictate that the variation cannot ever be as high as this upper bound. IQ is a standardized measure, and hence this constrains how variable a given population's IQ values can be. When you place such a wide uniform prior on these values, you are essentially giving a lot of prior weight on inadmissable values. In this example, there is little practical difference, but in general it is best to apply as much prior information that you have available to the parameterization of prior distributions. \n",
    "\n",
    "We will instead set the group standard deviations to have a $\\text{Uniform}(1,10)$ prior:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "sigma_low = 10**-1\n",
    "sigma_high = 10\n",
    "\n",
    "with model:\n",
    "    group1_std = pm.Uniform(\"group1_std\", lower=sigma_low, upper=sigma_high)\n",
    "    group2_std = pm.Uniform(\"group2_std\", lower=sigma_low, upper=sigma_high)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We follow Kruschke by making the prior for $\\nu$ exponentially distributed with a mean of 30; this allocates high prior probability over the regions of the parameter that describe the range from normal to heavy-tailed data under the Student-T distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 560,
       "width": 1649
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "with model:\n",
    "    nu_minus_one = pm.Exponential(\"nu_minus_one\", 1 / 29.0)\n",
    "    nu = pm.Deterministic(\"nu\", nu_minus_one + 1)\n",
    "    nu_log10 = pm.Deterministic(\"nu_log10\", np.log10(nu))\n",
    "\n",
    "pz.plot(nu_minus_one, figsize=(6, 3));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since PyMC parametrizes the Student-T in terms of precision, rather than standard deviation, we must transform the standard deviations before specifying our likelihoods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "with model:\n",
    "    lambda_1 = group1_std**-2\n",
    "    lambda_2 = group2_std**-2\n",
    "    group1 = pm.StudentT(\"drug\", nu=nu, mu=group1_mean, lam=lambda_1, observed=iq_drug)\n",
    "    group2 = pm.StudentT(\"placebo\", nu=nu, mu=group2_mean, lam=lambda_2, observed=iq_placebo)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Having fully specified our probabilistic model, we can turn our attention to calculating the comparisons of interest in order to evaluate the effect of the drug. To this end, we can specify deterministic nodes in our model for the difference between the group means and the difference between the group standard deviations. Wrapping them in named `Deterministic` objects signals to PyMC that we wish to record the sampled values as part of the output. As a joint measure of the groups, we will also estimate the \"effect size\", which is the difference in means scaled by the pooled estimates of standard deviation. This quantity can be harder to interpret, since it is no longer in the same units as our data, but the quantity is a function of all four estimated parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "with model:\n",
    "    diff_of_means = pm.Deterministic(\"difference of means\", group1_mean - group2_mean)\n",
    "    diff_of_stds = pm.Deterministic(\"difference of stds\", group1_std - group2_std)\n",
    "    effect_size = pm.Deterministic(\n",
    "        \"effect size\", diff_of_means / np.sqrt((group1_std**2 + group2_std**2) / 2)\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we can fit the model and evaluate its output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [group1_mean, group2_mean, group1_std, group2_std, nu_minus_one]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c2440169541d4d84b7501444509cb15e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 11 seconds.\n"
     ]
    }
   ],
   "source": [
    "with model:\n",
    "    idata = pm.sample()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can plot the stochastic parameters of the model. Arviz's `plot_posterior` function replicates the informative histograms portrayed in {cite:p}`kruschke2013`. These summarize the posterior distributions of the parameters, and present a 95% credible interval and the posterior mean. The plots below are constructed with the final 1000 samples from each of the 2 chains, pooled together."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2880x837.092 with 8 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 860,
       "width": 2903
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.plot_dist(\n",
    "    idata,\n",
    "    var_names=[\"group1_mean\", \"group2_mean\", \"group1_std\", \"group2_std\", \"nu\", \"nu_log10\"],\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at the group differences below, we can conclude that there are meaningful differences between the two groups for all three measures. For these comparisons, it is useful to use zero as a reference value (`ref_val`); providing this reference value yields cumulative probabilities for the posterior distribution on either side of the value. Thus, for the difference of means, at least 97% of the posterior probability are greater than zero, which suggests the group means are credibly different. The effect size and differences in standard deviation are similarly positive.\n",
    "\n",
    "These estimates suggest that the \"smart drug\" increased both the expected scores, but also the variability in scores across the sample. So, this does not rule out the possibility that some recipients may be adversely affected by the drug at the same time others benefit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 3600x535.887 with 3 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 559,
       "width": 3623
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pc = az.plot_dist(\n",
    "    idata,\n",
    "    var_names=[\"difference of means\", \"difference of stds\", \"effect size\"],\n",
    ")\n",
    "az.add_lines(pc, 0);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When `plot_forest` is called on a trace with more than one chain, it also plots the potential scale reduction parameter, which is used to reveal evidence for lack of convergence; values near one, as we have here, suggest that the model has converged."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LklJSUgwv7jp58qTmzZunq666yvJxMzIytHTpUsN43759FRER4VXfkZGRat26tbp27aquXbuqSpUqpu0TEhKUkJCg6tWrq3nz5pKk48eP64svvtCrr76qgwcPGv7smjVr9Omnn2rgwIFezdUdx44d05gxY87432NiYjRs2DBdf/31KleuXIk/27BhQ1188cUaOnSotmzZoqSkJNvm6a7w8HA1a9ZMXbt2Vbdu3Vz+UouLi1NcXJyqVq2q5ORkDRw4UI899pgWLlyoV155Rb/99pvhz+7atUsTJ07UPffcY/XLOM3DDz+sgoKC0/63sLAwpaam6q677jJcg8nJyerTp48efvhhzZ49Wy+//LIyMzMNxzl06JAeffRRvfbaa5bO30ozZ87UlClTTNvExMToqquu0o033qjKlSuX2KZy5cqqXLmyGjZsqCuvvFKHDh3Sq6++qlmzZqmwsLDEn9mxY4eefPJJPffcc76+DAAAAAAAAJQiZh9aSVL16tVtG7tcuXKqVKmS4YMKXM3N0/Z2vhZXfXv6Wpxo6dKlOnz4sGE8ISHB9g/WfvjhB1166aWG8ZMnT+rkyZM6evSodu3apVWrVv0dq1y5srp166aBAweqQYMGts4TsBN53xpOzvv79u1Thw4dDOOFhYXKz89Xdna29u7dqzVr1mj27NmSpMTERF1yySX6v//7P7Vo0cK2OTppHQN2c9J+Ie8Hj6ysLC1YsMC0Tf/+/f00m//hvA84K+/DM4F87//q3+iPejIyMpSXl6eYmBi3+mIdA+5jv8BfqO8DwYG8D1eo75tjHSPUsF9gB+r7QHAj93svLS3NNN6qVSu/XFTrLWr81gj1dYzSh/3ivVDP+/5GjT+0hNzKbdSokekCcrVhvTV37twzLjr6p9TUVI/7jI+P15AhQ7R48WK9++67uvbaa11e2mWkXLlyGjBggL744gulpKSYtp04caLy8/O9Gscd2dnZysnJOe1/a9WqlebPn6+hQ4caXtr1bw0bNlSlSpXsmKJbypYtq6uuukpfffWVPv74Y91yyy1e33AbFRWlnj17as6cORoyZIhp2/fff9/wF6ZVNmzYcNp/j4mJ0cSJE/XMM8+4tQajo6M1cOBAzZkzR82aNTNtu3DhQn311Vc+zdcuu3fv1ujRo03bNG7cWJ999pkeeOABw0u7SlK5cmU99dRTev31103/z01aWppWrFjhdr8AAAAAAADAvn37TONnnXWWreOb1W0zMzN1/Phxt/ty9VrsfLhD2bJlFRsbaxh3NbfS4N133zWNd+3a1fYPSYuKirz+2UOHDmnatGnq16+fbrzxRq1fv97CmQH+Q963hpPzvtkTPF3JysrS7NmzdfXVV6t///5avny5hTP7HyetY8BuTtov5P3gMXfuXNPvCtWoUUNt2rTx44z+xHkfcFbeh2eC+b2XPPtdGcyvhXWMYMN+gb9Q3weCA3kfrlDfd411jFDCfoEdqO8DwY3c752cnBxNnz7dtE337t39NBvvBPN7L1HjB+zCfvGOE/K+v1HjDy0hd3GXJNOLqX766Sft3LnT8jHNLgRr3Lix6tWr51F/V111lb799lvdd999Hl0G5Ep8fLzGjBmja665xrDNwYMHNXfuXMvGdKVt27aaPHmypa/Tbl27dtXixYs1atQory/rKkl0dLTuu+8+3XfffYZtjh8/rmnTplk2pitlypTRW2+9pS5dunj8s1WqVNG7776rCy64wLTd888/b+tlcd569NFHdeLECcN4jx499PHHH6tGjRpej3HRRRdp6tSpppd3vfDCC173DwAAAAAAgNInMzPTNG7nH79LclnrdTU/T9ra/QGm2b/V0aNHffqidKhbunSpVq5cadrmiiuu8M9kLLBixQoNGDBATzzxhPLy8gI9HcAj5H3rkPfNbdiwQTfddJPuvPNOw6dyestJ6xiwm5P2C3k/eMycOdM0npqaqrCwMD/Nxnqc9xHKnJT34RknvfdOei2A3dgv8Afq+0DwIO/DX6jvA8GB/QI7UN8Hghu53ztvvPGGjh49ahiPjY1Vt27d/DgjzznpvXfSawHsxn7xjhPyvj9R4w89IXlxV9++fRUZGWkYN7tkyxvbtm3Tpk2bDOOpqake99mqVSvFxcX5Mi1Tjz32mFq3bm0Yt/rfyEitWrX0+uuvq1y5cn4ZzyrJycmqWLGibf0PGTJEl19+uWE8LS3Nb18QfeKJJ9SqVSuvfz42NlYTJkww/ULtH3/8oTlz5ng9hh0WLVqk77//3jDevHlzvfDCC4qOjvZ5rMaNG2vUqFGG8U2bNmnx4sU+jwMAAAAAAIDSISsryzQeHx9v6/iu+nc1P0/aJiQkuN2XN8z6LywsVHZ2tq3jB6uTJ0/q6aefNm3TrFmzgDyx01cfffSRUlJStGvXrkBPBXAbed865H33zJ8/X/369dO6dess69NJ6xiwm5P2C3k/OGzatEmbN282jIeHh3v13adgxHkfochJeR+ecdJ776TXAtiN/QK7Ud8Hggt5H/5GfR8ILPYLrEZ9Hwh+5H7P7dixQ1OmTDFtc80119h6B4MVnPTeO+m1AHZjv3jOKXnfX6jxh6aQvLirUqVK6tSpk2F87ty5ll56NHv2bMNYVFSUevfubdlYVgkLC9MjjzyiiIiIEuNr1qyx/CkKJRk1alTIXdrlLyNHjlRsbGyJsT/++MP0sjirtG7d2pLiTFJSku655x7TNq5+ofrbhAkTDGPx8fGaOHGiypQpY9l4/fr1U8+ePQ3jH3/8sWVjAQAAAAAAwNnMnjgjyfYPrlz172p+7raNioqy5GJ9M1a+FicZO3asdu7cadrm7rvv9s9kbLBr1y4NHDhQ69evD/RUALeQ961D3ndfenq6rr/+en333XeW9OekdQzYzUn7hbwfHGbOnGka79Chg84++2w/zcZ+nPcRapyU9+GZYH/vPflif7C/FtYxggn7BXajvg8EF/I+AoH6PhA47BdYjfo+EPzI/Z4pLCzUAw88oPz8fMM2CQkJuummm/w4K+8E+3tPjR+wB/vFM07K+/5CjT80RQZ6At5KTU3V4sWLS4z98ccfWr16tdq2bevzOIWFhZo7d65hvHPnzqpQoYLP49ihYcOGatGihdasWXNGrLi4WKtXr1avXr1sG79Hjx5q166dbf2HuqSkJHXr1k1paWklxleuXKnGjRvbNn54eLgeeeQRy/pLTU3VtGnTtHHjxhLjv/76q9avX6/k5GTLxvTWzz//bDhPSbr11ltVqVIly8cdNmyYvvrqqxJjS5cu1ZEjR2wZFwAAAAAAAM6Sl5dnGo+JibF1fFf9u5qfu22NHnxgJStfi1N89913eu+990zb9OjRQ+3bt7d9LjExMTr//PNVv3591atXT9WqVVN8fLzi4+MVGRmpo0ePKisrS+np6Vq7dq2+//577d27162+s7KydMstt2jatGk677zzbH4lgG/I+9ZxYt6Pior6O1fWr19fNWvWVFxcnOLj41WmTBllZ2crKytLR44c0c8//6w1a9Zox44dbvV94sQJDR8+XJMnT1br1q19mqeT1jFgNyftF/J+4OXn5+vzzz83bTNgwAA/zeZ0nPeBPzkp78Mzwf7eHz9+3O2+gv21sI4RTNgvsBP1fSD4kPdhhvq+e1jHCCXsF1iJ+j7nfYQGcr9nxo4d6/KijrvuuksVK1b004y8F+zvPTV+wB7sF884Ke/7AzX+0BWyF3d17txZiYmJhjd+pqWlWXJx17Jly5Senm4YT0lJ8XkMO11yySUlXtwlSb/88outF3cNHDjQtr6d4pJLLjG8uOuXX36xfeyGDRta1l9YWJiGDRumO+64w7DNvHnzguLirhkzZhjGzjrrLN1www22jNuwYUO1bdtWq1atOiNWWFioZcuW6fLLL7dlbAAAAAAAADjHqVOnTONRUVG2ju+q/4KCArf7MnstkZH2f4Rh5Wtxgr179+r+++9XcXGxYZvExERLHwrxb1WqVFHXrl3VuXNntW3bVtHR0W793JVXXilJ2r59uyZPnqwvvvjC5fuXlZWl22+/XTNnzrT9KVeAL8j71nFK3k9MTNSll16qSy65RB06dHD78pu/Ptveu3evpkyZohkzZrj8ot7Jkyd15513Ki0tzaenNTtpHQN2c9J+Ie8H3oIFC0yfplyhQgVdeumlfpsP533gTE7K+/CMq/fe7t+V/vqd785YvmIdI5SwX2AX6vtAcCLv49+o73uOdYxQwn6Blajvc95HaCD3u2/BggV6++23Tdu0aNFC11xzjZ9m5Btq/NYJpXUMsF/c57S8bzdq/KEtPNAT8FZ0dLR69+5tGJ8/f74lNwIaXaokSRUrVtRFF13k8xh2ql+/vmFs+/btto1btWpVtWvXzrb+ncLs/dm2bZutY/fp08fyPi+++GIlJCQYxpctW2b5mJ4qLi7WokWLDOPdu3d3+5eINzp27GgYW7lypW3jAgAAAAAAwDlcfZARERFh6/iuvlDg6kPJfzJ7LXa/DnfG8OS1hLqcnBwNGzbM9Et/kvT444+rSpUqlo4dFhamtm3bavz48Vq8eLEee+wxXXTRRV7VauvVq6fnnntO8+fPV6tWrVy237Vrl5588klvpg34DXnfOqGe95OTkzVmzBgtWbJEzz77rLp37+72H/X8U/Xq1fXoo49q0aJF6tatm8v2mZmZGjlypDdT/puT1jFgNyftF/J+4M2cOdM03q9fP1u/IyFx3gdccVLeh2dcvfd2/1GPv37nS6xj4J/YL7AD9X0geJH38Rfq+95jHSOUsF9gJer7nPcRGsj97tm6davLy0hiYmL03HPPKTw8NK6+oMZvnVBZx4DEfnGXE/O+najxh76QXsV/PTGgJHl5efr666996v/YsWNauHChYbxv376233roq7POOsswtmvXLtvG7dSpE0nSDWbvz549e1RUVGTLuDExMbbcqB4dHW1a/N++fbsyMjIsH9cTGzZs0JEjRwzjvXr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      "text/plain": [
       "<Figure size 2400x715.172 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 738,
       "width": 2423
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.plot_forest(idata, var_names=[\"group1_mean\", \"group2_mean\"]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2400x806.451 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 829,
       "width": 2423
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.plot_forest(idata, var_names=[\"group1_std\", \"group2_std\", \"nu\"]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>sd</th>\n",
       "      <th>eti89_lb</th>\n",
       "      <th>eti89_ub</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>difference of means</th>\n",
       "      <td>1</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.32</td>\n",
       "      <td>1.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>difference of stds</th>\n",
       "      <td>1</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.37</td>\n",
       "      <td>1.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>effect size</th>\n",
       "      <td>0.64</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.18</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     mean    sd eti89_lb eti89_ub\n",
       "difference of means     1  0.43     0.32      1.7\n",
       "difference of stds      1  0.45     0.37      1.8\n",
       "effect size          0.64  0.29     0.18      1.1"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "az.summary(\n",
    "    idata, var_names=[\"difference of means\", \"difference of stds\", \"effect size\"], kind=\"stats\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Autorship"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Authored by Andrew Straw in Dec, 2012 ([best](https://github.com/strawlab/best))\n",
    "* Ported to PyMC3 by Thomas Wiecki in 2015\n",
    "* Updated by Chris Fonnesbeck in Dec, 2020\n",
    "* Ported to PyMC4 by Andrés Suárez in Ene, 2022 ([pymc-examples#52](https://github.com/pymc-devs/pymc-examples/issues/52))\n",
    "* Updated by Osvaldo Martin in Dec, 2025\n",
    "* Rerun by Osvaldo Martin in Apr, 2026"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ":::{bibliography}\n",
    ":filter: docname in docnames\n",
    ":::"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Watermark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last updated: Sat, 25 Apr 2026\n",
      "\n",
      "Python implementation: CPython\n",
      "Python version       : 3.14.4\n",
      "IPython version      : 9.12.0\n",
      "\n",
      "arviz : 1.1.0\n",
      "numpy : 2.4.4\n",
      "preliz: 0.24.0\n",
      "pymc  : 5.28.0+58.gf58491a3\n",
      "xarray: 2026.4.0\n",
      "\n",
      "Watermark: 2.6.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -n -u -v -iv -w"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ":::{include} ../page_footer.md\n",
    ":::"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "arviz_1",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.14.4"
  },
  "latex_envs": {
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