diff --git a/Untitled.ipynb b/Untitled.ipynb
new file mode 100644
index 0000000..4c89156
--- /dev/null
+++ b/Untitled.ipynb
@@ -0,0 +1,144 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## Confidence intervals\n",
+    "\n",
+    "n=10\n",
+    "mu = 12\n",
+    "sigma = 2\n",
+    "alpha = 0.05\n",
+    "data <- rnorm(n,mu,sigma)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Test "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<ol class=list-inline>\n",
+       "\t<li>12.4969281981402</li>\n",
+       "\t<li>15.2124504834396</li>\n",
+       "\t<li>9.15066856262369</li>\n",
+       "\t<li>13.0723317193259</li>\n",
+       "\t<li>14.4227012164485</li>\n",
+       "\t<li>11.6310612991374</li>\n",
+       "\t<li>11.950142226449</li>\n",
+       "\t<li>12.5612071713377</li>\n",
+       "\t<li>10.8086625361726</li>\n",
+       "\t<li>10.9905693475738</li>\n",
+       "</ol>\n"
+      ],
+      "text/latex": [
+       "\\begin{enumerate*}\n",
+       "\\item 12.4969281981402\n",
+       "\\item 15.2124504834396\n",
+       "\\item 9.15066856262369\n",
+       "\\item 13.0723317193259\n",
+       "\\item 14.4227012164485\n",
+       "\\item 11.6310612991374\n",
+       "\\item 11.950142226449\n",
+       "\\item 12.5612071713377\n",
+       "\\item 10.8086625361726\n",
+       "\\item 10.9905693475738\n",
+       "\\end{enumerate*}\n"
+      ],
+      "text/markdown": [
+       "1. 12.4969281981402\n",
+       "2. 15.2124504834396\n",
+       "3. 9.15066856262369\n",
+       "4. 13.0723317193259\n",
+       "5. 14.4227012164485\n",
+       "6. 11.6310612991374\n",
+       "7. 11.950142226449\n",
+       "8. 12.5612071713377\n",
+       "9. 10.8086625361726\n",
+       "10. 10.9905693475738\n",
+       "\n",
+       "\n"
+      ],
+      "text/plain": [
+       " [1] 12.496928 15.212450  9.150669 13.072332 14.422701 11.631061 11.950142\n",
+       " [8] 12.561207 10.808663 10.990569"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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ffAJgEApJKLJwAAIiHsAAAikX3fik0m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\nACIh7AAAIvEXeX9XZs31l18AAAAASUVORK5CYII=",
+      "text/plain": [
+       "plot without title"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot(data,rep(0,n),col=\"blue\")\n",
+    "abline(v=mu,col=\"red\")\n",
+    "abline(v=mean(data),col=\"blue\")\n",
+    "\n",
+    "#Draw confidence box\n",
+    "margin_of_error <- sigma/sqrt(n)*qnorm(1-alpha/2)\n",
+    "lb=mean(data)-margin_of_error\n",
+    "ub=mean(data)+margin_of_error\n",
+    "\n",
+    "rect(lb,-0.2,ub,0.2)\n",
+    "\n",
+    "text(mean(data)-0.4,1,labels = \"mean\",col=\"blue\")\n",
+    "text(mu+0.3,-1,labels = \"mu\",col=\"red\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "R",
+   "language": "R",
+   "name": "ir"
+  },
+  "language_info": {
+   "codemirror_mode": "r",
+   "file_extension": ".r",
+   "mimetype": "text/x-r-source",
+   "name": "R",
+   "pygments_lexer": "r",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}