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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "eb81ed47",
+   "metadata": {},
+   "source": [
+    "# Example 3: Bootstrap intuition - Mean vs Median\n",
+    "\n",
+    "**Students tasks**\n",
+    "\n",
+    "## Task A : Descriptive stats\n",
+    "\n",
+    "- [ ] Compute and report: mean, median, SD, IQR, five-number\n",
+    "- [ ] Plot (histogram and boxplot)\n",
+    "- [ ] Identify outlier using the 1.5IQR rule\n",
+    "\n",
+    "## Task B: Sampling variability\n",
+    "\n",
+    "- [ ] using the provided population, run repeated samplings for n=30, 50,100\n",
+    "- [ ] Plot the sampling distribution (3 histograms)\n",
+    "- [ ] Make a table with the empirical standard error (SD) vs n size\n",
+    "\n",
+    "## Task C: Bootstrap mean vs median\n",
+    "\n",
+    "- [ ] Bootstrap (resample with replacement from data) the mean and median (B=5000) for dataset with outliers (*)\n",
+    "- [ ] Plot both bootstrap distributions\n",
+    "- [ ] Compute 95% percentils CIs for the mean and median\n",
+    "- [ ] Repeat after removing the the outliers and compare:\n",
+    "    - [ ] Which statistics changes more (mean or median)?\n",
+    "    - [ ] Which bootstrap distribution is wider, and why?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6abe3332",
+   "metadata": {},
+   "source": [
+    "- [ ] Texto"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}