diff --git a/pruebas_de_hipotesis.ipynb b/pruebas_de_hipotesis.ipynb
index 9d66bdcde4f597b083a61a8bdfcd5f91f74efff8..2364da80d819a68001e9590c25d5a2774c4a7442 100644
--- a/pruebas_de_hipotesis.ipynb
+++ b/pruebas_de_hipotesis.ipynb
@@ -144,7 +144,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 864x432 with 2 Axes>"
       ]
@@ -182,7 +182,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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9++yzqqqqqmk/deqUioqK1L9/f+urBgAgwHm8xH3p0iWtWbNGbdu21dSpU/Xxxx+7Te/QoYMWLFigRYsWaenSpZo4caL+/ve/a9OmTerevbvGjh3rt+IBAAhUHgP6vffe03fffadz585p6tSptaavX79eY8eO1YsvvqgtW7ZowYIFioiIUHJyshYvXiybzeaXwgEACGQeA3rcuHEaN26cxxUNHz5cw4cPt6ImAACCHk+zAgDAQAQ0AAAGIqABADAQAQ0AgIEIaAAADERAAwBgIAIaAAADEdAAABiIgAYAwEAENAAABiKgAQAwEAENAICBCGgAAAxEQAMAYCACGgAAAxHQAAAYiICGR+UVVxu6BAAIOk0augCYzx5m0+glBxq6jHrlbBjb0CUAgOU4gwYAwEAENAAABiKgAQAwEAENAICBCGgAAAxEQAMAYCCvArqqqkq//e1vNXr0aPXp00fDhw/X2rVrVVJSUjPP//zP/+iRRx5Rnz59NGjQIL3wwguqqKjwW+EAAAQyr74HnZWVpfT0dM2cOVOJiYkqLCxURkaGPvnkE23fvl1nz57VtGnT1KdPH6Wnp+vMmTPauHGjSkpKtGrVKn/3AQCAgOMxoF0ul7KysjR58mQtWbJEkjRgwABFR0crLS1NeXl52r17t6KiovTSSy/JbrdryJAhioiI0OrVqzV79mzFxMT4vSMAAAQSj5e4S0tLNWbMGD344INu7Z07d5YkFRUV6dixY/rHf/xH2e32muk//elPdfXqVb3//vsWlwwAQODzeAYdGRmplStX1mo/evSoJKlLly767LPP1KlTJ7fprVq1UmRkpAoLCy0qFQCA4HFDd3GfPHlS27Zt0/Dhw9WiRQtJ3wf5tZo3b+52IxkAAPCOzw/LcDgcmjNnjtq1a6fVq1ervLz8uvOHhvr2N0Bubq6vJcnhcPi8TKDx5xgkJCT4bd1AIGnoY1FDb7+hBVr/fQrogwcPavny5erYsaOysrIUHR2t0tJSSar5/w+VlJQoKirKp4Li4+MVHh7u9fwOhyPoA4QxAMzQkO/DYD8ONMb+O53O656Uen16u2PHDi1evFi9e/fWnj17dMcdd0j6/jJ2TEyMzp496zb/pUuXVFpaWuuzaQAA4JlXAb1v3z6tW7dOo0aNUlZWVq2z4oEDB+o//uM/3C53Hzp0SDabTf3797e2YgAAgoDHS9yXLl3SmjVr1LZtW02dOlUff/yx2/QOHTroscce0x/+8AfNmjVLP//5z/XXv/5VL7zwgiZNmqS77rrLb8UDABCoPAb0e++9p++++07nzp3T1KlTa01fv369xo4dq+zsbK1fv16LFi1SdHS0pk+froULF/qlaAAAAp3HgB43bpzGjRvncUV9+/bVq6++akVNAAAEPZ5mBQCAgQhoAAAMREADAGAgAhoAAAMR0AAAGIiABgDAQAQ0AAAGIqABADAQAQ0AgIEIaAAADERAAwBgIAIaAAADEdAAABiIgAYAwEAENAAABiKgAQAwEAENABYor7jaoNtPSEjwOE9D1wjfNGnoAgAgENjDbBq95EBDl3FdORvGNnQJ8AFn0AAAGIiABgDAQAQ0AAAGIqABADAQAQ0AgIEIaAAADORzQOfl5SkuLk7nz593a09OTla3bt1q/ffll19aViwAAMHCp+9BnzlzRrNnz1ZlZaVbe2lpqYqLi7VkyRL179/fbVqLFi1uvkoAAIKMVwFdWVmpvXv3asOGDQoLC6s1vaCgQC6XS8OGDVOXLl0sLxIAgGDj1SVuh8OhX/3qV5oxY4aWLl1aa3peXp4iIiLUsWNHq+sDACAoeRXQXbp00dGjR7VgwQLZbLZa0wsKCtSyZUstXrxYffv2VZ8+fZSWlqbPP//c8oIBAAgGXgV069atdfvtt9c7PT8/X1988YXuuecebdmyRStWrNCHH36oRx99VGVlZZYVCwBAsLDkYRkrV66Uy+VSr169JEl9+/ZVly5dNGXKFL3xxhuaNGmS1+vKzc31efsOh8PnZQKNP8fAm6fkAGgcAvl4GWh9sySg77333lptCQkJioqKUn5+vk/rio+PV3h4uNfzOxyOoA8QxgCAtwL1WNEYj4NOp/O6J6U3/UMl3377rfbv318riKuqqlRRUaHo6Oib3QQAAEHnpgM6PDxc69at0+bNm93a3377bZWVldX6XjQAAPDspi9x22w2zZs3T+vWrdPq1as1dOhQnT59WpmZmRo2bJjuu+8+K+oEACCoWPIZ9PTp0xUZGamdO3dq3759atmypR566CEtXLjQitUDABB0fA7oCRMmaMKECbXaU1JSlJKSYklRAAAEO55mBQCAgQhoAAAMREADAGAgAhoAAAMR0AAAGIiABgDAQAQ0AAAGIqABADAQAQ0AgIEIaAAADERAAwBgIAIaAAADEdAAABiIgAYAwEAENAAABiKgAQAwEAENAICBCGgAAAxEQAMAYCACGgAAAxHQAAAYiIAGAMBABDQAAAYioAEAMJDPAZ2Xl6e4uDidP3/erf3999/XxIkT1atXLw0dOlTZ2dmWFQkAQLDxKaDPnDmj2bNnq7Ky0q39xIkTmjNnjjp37qzMzEyNHj1a69ev1/bt2y0tFgCAYNHEm5kqKyu1d+9ebdiwQWFhYbWmZ2RkqEePHnr++eclSYMHD1ZlZaW2bNmiRx55RHa73dqqAQAIcF6dQTscDv3qV7/SjBkztHTpUrdpTqdTx48f14gRI9zaR44cqcuXL+vEiRPWVQsAQJDwKqC7dOmio0ePasGCBbLZbG7TiouLVVFRoU6dOrm1x8bGSpIKCwstKhUAgODh1SXu1q1b1zvtypUrkqTIyEi39ubNm0uSSkpKbrQ2AACCllcBfT0ul+u600NDfbtRPDc31+caHA6Hz8uY4h+6x6l5s4ibWkdCQoJF1QAIdI35eOlJoPXtpgM6KipKklRaWurWXn3mXD3dW/Hx8QoPD/d6fofD0egDavSSAw1dwnXlbBjb0CUAsEhjP17WpzFmgdPpvO5J6U3/UEmHDh1ks9lUVFTk1l7972s/mwYAAJ7ddECHh4erb9++Onz4sNvl7kOHDikqKkrx8fE3uwkAAIKOJT/1OXfuXJ04cUJpaWl65513lJ6eru3bt2v27Nlq2rSpFZsAACCoWBLQiYmJyszM1JkzZzR//nzl5OToySefVGpqqhWrBwAg6Ph8k9iECRM0YcKEWu3JyclKTk62pCgAAIIdT7MCAMBABDQAAAYioAEAMBABDQCAgQhoAAAMREADAGAgAhoAAAMR0AAAGIiABgDAQAQ0AAAGIqABADAQAQ0AgIEIaAAADERAAwBgIAIaAAADEdAAABiIgAaAIFFecbWhS/CoMdR4qzRp6AIAALeGPcym0UsONHQZ15WzYWxDl2AMzqABADAQAQ0AgIEIaAAADERAAwBgIAIaAAADEdAAABjIsq9ZVVZW6sc//rGcTqdbe7NmzfTRRx9ZtRkAAIKCZQFdWFgop9Op5557Th07dqxpDw3lJB0AAF9ZFtD5+fkKDQ3VyJEj1bRpU6tWCwBAULLs9DYvL08dOnQgnAEAsIBlAV1QUCC73a6ZM2eqT58+6tevn1atWqWSkhKrNgEAQNCw9BJ3SUmJUlJSNGfOHOXm5iozM1OFhYXauXOnQkJCrNoUAAABz7KA3rhxo1q2bKlu3bpJkvr166fbb79dTzzxhD744AMNHDjQq/Xk5ub6vG2Hw+HzMqZISEho6BIAwCg3ekxvzFlQF8sCun///rXakpKSJH1/du1tQMfHxys8PNzr7TocDkIOAALIjRzTG2MWOJ3O656UWvIZ9KVLl7Rv3z4VFxe7tZeVlUmSoqOjrdgMAABBw5KADgkJ0apVq7R792639oMHD8pmszW6v2oAAGhollzibtWqlaZOnapdu3YpMjJSffv2lcPh0JYtWzR16lTFxsZasRkAAIKGZZ9BL1u2TDExMdq/f7+2bdummJgYLVq0SI899phVmwAAIGhYFtBhYWFKTU1VamqqVasEACBo8UPZAAAYiIAGAMBABDQAAAYioAEAMBABDQCAgQhoAAAMREADAGAgAhoAAAMR0AAAGIiABgDAQAQ0AAAGIqABADAQAQ0AgIEIaAAADERAAwBgIAIaAAADEdAAAGOUV1y9oeUSEhIsrqRuN1rfjWhyy7YEAIAH9jCbRi850NBl1Ctnw9hbti3OoAEAMBABDQCAgQhoAAAMREADAGAgAhoAAAMFdEDfytvhAQCwkqVfs/r973+vl19+WcXFxWrbtq1mz56tcePGWbkJn5h+u750a2/ZBwA0HpadQR88eFBLly7VoEGD9OKLL6p///5atmyZ/vjHP1q1CQAAgoZlZ9AbN27UqFGjtGLFCknS/fffr2+++UabNm3ST3/6U6s2AwBAULDkDLq4uFhFRUUaMWKEW/vIkSP16aefqri42IrNAAAQNCwJ6E8//VSS1KlTJ7f22NhYSVJhYaEVmwEAIGhYcon7ypUrkqTIyEi39ubNm0uSSkpKPK7D5XJJksrLy33evtPprHfabc1tPq/vVnI6ndR4k0yvTzK/RtPrk8yv0fT6JGq0wvXyxlfVeVedf9cKcdU3xQc5OTlaunSp3nrrLbVr166m/ezZsxoxYoRXn0NfuXJFp0+fvtlSAABoVLp27aqoqKha7ZacQVevuLS01K29+sy5rg1fq3nz5uratavCwsIUEhJiRVkAABjL5XKpoqKi5mrztSwJ6OrPnouKitStW7ea9rNnz7pNv57Q0FCvghwAgEARERFR7zRLbhKLjY1Vu3btan3n+fDhw+rYsaPuuusuKzYDAEDQsOx70PPnz9eKFSvUsmVLJSUl6a233tKbb76pjRs3WrUJAACChiU3iVX7t3/7N2VnZ+uzzz5T+/btNWvWrAb9qU8AABorSwMaAABYI6CfZgUAQGNFQAMAYCACGgAAAxkb0AsWLFBycnKd0y5cuKC+ffvq+PHjHtdz/PhxdevWrdZ/s2fPtrpkS9XV/zfffFMTJ05Unz59NGTIEK1YsUKXLl3yuK5XXnlFycnJuvfeezV+/Hi98847/irbUlaNwfnz5+vcBx588EF/ln/T6ur/G2+8odGjR6tXr14aOXKkdu7cWe/PBFarrKxUenq6hgwZol69emnKlCn67//+b3+WbhmrxiCQjgM/9Oyzz6pHjx4e19NY9wGr+t9YX3/LvmZlpQMHDujIkSPq0KFDrWkXL17UY489VvP7354UFBSoWbNm2rFjh1t7ixYtLKnVH+rq/8GDB5WWlqbJkycrLS1Nn3/+uTIyMjRt2jTt379fdru9znVlZWXphRde0IIFCxQXF6f9+/dr3rx52rNnj3r37n2LeuQ7K8cgPz9fkpSdne32iz3X+4GAhlZX/3NycvTEE09o+vTpeuqpp3Ty5EmtW7dOTqdTqamp9a5rzZo1+t3vfqelS5fqrrvu0o4dOzRt2jQdOHBA7du3vxXduSFWjkGgHAd+6MMPP9TOnTsVGur5PKsx7gNW9r8xvv6SJJdhzp8/7+rXr59r8ODBruHDh9e0V1VVuX7/+9+7BgwY4Orfv7+ra9eurg8//NDj+lauXOlKSUnxZ8mWqq//Y8aMcaWmprrN+1//9V+url27uo4cOVLnukpLS10JCQmu559/vqatqqrKNWnSJNfMmTP90wELWDkGLpfL9fLLL7sGDBjgt3qtVl//f/azn7lmz57tNu+yZctcgwcPrnddxcXFru7du7t+85vf1LQ5nU5XUlKSa9WqVdYXbxErx8DlCpzjQLWSkhLXsGHDXIMHD3Z17979uutqjPuAlf13uRrf61/NuDPolStXauDAgQoPD5fD4ahpP3funJYtW6aHHnpIgwYN8vrSRF5enrp37+6vci1XV/9dLpcGDBighIQEt3k7d+4s6fufWK3LyZMndeXKFbfndIeEhCg5OVkbN25UeXl5vWedDcnKMZC+3wd++BO0pqvvPZCZmakmTdzfsmFhYdd9us5f/vIXXb16VSNHjqxps9vtSkpK0p/+9CfLa7eKlWMgBcZx4IfWr1+v1q1bKzExUVu3br3uuhrjPmBl/6XG9/pXM+oz6H379unUqVN6+umna02Ljo7WH//4R61cuVJNmzb1an1Xr17V//7v/+r8+fMaP3684uPjlZSUpOzsbI+fWTWE+vofEhKiZcuWafjw4W7tR48elSTdfffdda6v+jnd1SFWLTY2VpWVlSouLraqdMtYPQbS95e4y8rK9PDDD6tnz54aMGCANmzYoIqKCus7cJOu9x7o1KlTzeXIr7/+Wvv27dPrr7+uyZMn17u+Tz/9VC1btlSrVq3c2mNjY/X3v/9dZWVl1nbAAlaPQaAcB6odO3ZMBw4c0Nq1a726vNvY9gGr+9/YXv8fMuYM+ty5c1q7dq3Wrl1ba0eSvn/aVX1P/KjPX//6V5WVlamwsFCLFy9WdHS03nrrLa1fv14lJSVatGiRVeXfNE/9v1ZRUZGee+45xcXFadCgQXXOU/00sWvHrfrf1z59rKH5Ywy+++47FRUV6ZtvvtETTzyhtLQ0/eUvf9G2bdt08eJFPffcc1Z344Z52//c3FxNnDhRkhQfH6/p06fXO29JSUmt57RL7vuASZ/F+2MMAuk4cOXKFf3iF7/QokWLvHoIkdS49gF/9L8xvf7XMiKgXS6XnnrqKQ0ZMsTtMszNiomJ0a9//Wt1795dP/rRjyRJiYmJKisr069//WvNmDGjzh33VvO1/2fOnNHMmTPVpEkTpaen1/tXpKe/Dk16rKe/xsBmsyk7O1tt27atudmkf//+CgsLU3p6uubOnauOHTta2ZUb4kv/27Rpo507d+rcuXNKT0/XlClT9O///u91HmQDdR/wZQwC6Tjw7LPPqk2bNpo2bZpP670eU/YBf/W/sbz+dTEioPfs2aOCggLl5OSosrJS0v/vVJWVlbLZbDe0E0VGRmrw4MG12pOSkrRv3z4VFhaqZ8+eN1e8BXzp/3/+539q4cKFatasmV555ZV673CU3J/T/cMd0JfndN8q/hoDu92uxMTEWu1JSUlKT09Xfn6+EQHtS/9bt26t1q1bS5Lat2+vf/qnf9KRI0c0evToWuuNjIys80pJ9T5g0oHJn2MQCMeBd999V3/4wx+0f/9+VVVV1fxXPT00NLTOP1Qbyz7gz/43hte/LkYE9KFDh/TVV1/VeZkyLi5Oa9eu1YQJE3xeb0FBgRwOh1JSUhQWFlbTXv2ZS3R09I0XbSFv+3/w4EE9+eST6tSpk7KyshQTE3Pd9f7wOd0//K7g2bNnZbfbjXoMqL/GoLi4WB988IGSk5PdLpk1tn3gl7/8paKiotSjRw+3ewqqX9eLFy/Wud7OnTvr66+/1jfffKOWLVvWtJ89e1bt2rUz6iZBf41BoBwH2rZtK6fTWef39+Pi4rRgwQItXLiw1rTGsg/4q/+N5fWvixEB/cwzz9T6C+/FF19UXl6eNm/erHbt2t3Qes+ePatnnnlGMTExGjZsWE37wYMH1a5dO7Vt2/am6raKN/1/7733tHTpUiUkJOjll1/26q/ePn36qFmzZjp06FDNQczlcunIkSPq16+fMW9MyX9jcPnyZa1atUpOp1OPPvpoTfvBgwdrDvYm8Kb/I0aM0NChQ90+Nz927JgkqWvXrnWud8CAAZK+P/hNmjRJklReXq4//elPuv/++/3RlRvmrzEIlONASEhIrcvVr776qvbv36+9e/fqjjvuqHO9jWUf8Ff/G8vrXxcjAvrau4wl6bbbbpPdbvfp0kNJSYk++eQTdejQQa1atVJSUpLi4uL09NNP68svv1SbNm2Uk5Ojt99+W5mZmcZ89uKp/+Xl5frFL36h5s2ba86cOfrkk0/c5r3zzjsVExOj8vJyffzxx2rTpo3atGmjpk2basaMGXrppZdks9nUq1cv7d+/X6dOndLOnTtvVfe84q8xiIuL09ChQ7Vx40ZVVVXpnnvu0TvvvKNdu3Zp+fLlxlzm9+Y9MGfOHK1fv14/+tGPNHDgQBUUFGjz5s0aOHBgzVnHte+Btm3bavz48Vq9erW+/fZbxcbGaseOHbp8+bIee+yxW9pHT/w1BoFyHKhL9dekfji9se4D/up/Y3n962JEQFvl1KlTevTRR2suh9rtdmVlZSk9PV2bN2/Wl19+qXvuuUebN2+u9XUdk508eVIXLlyQJM2YMaPW9Mcff1zz5s3TxYsXNXnyZLdLPfPnz5fNZtOrr76qrKws3X333XrppZdqfZ/YdDczBhs2bNBLL72kXbt26eLFi+rQoYP+5V/+RSkpKbe0Dzdr5syZatGihXbu3KmdO3cqOjpaDz30kBYuXFhzkLn2PSBJ//zP/6wWLVpo27Zt+vbbbxUXF6cdO3YoNja2IbtzQ25kDALlOOCtQN8HPAmk15/nQQMAYCCjfqgEAAB8j4AGAMBABDQAAAYioAEAMBABDQCAgQhoAAAMREADAGAgAhoAAAMR0AAAGOj/AGX5K6rHi5EmAAAAAElFTkSuQmCC\n",
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PHzBJR/0u8jrQOY+B3W5v8QTV7bCuqKjQ/PnzVVFRoT179ig6OrrVbXr37i1JKi8vd7cbAADwHW6Ftd1u18KFC/Xtt9/qN7/5jdtnyUVFRZKkXr16tb1CAAACXKt3g9fV1Wnp0qX6/PPPlZ2drYSEhEZtKisr5XA4Gm330ksvKSgoSCkpKV4rGACAQNPqmfWGDRv03nvvady4cSorK5PVanWti4iIUGpqqr788kutWLFCkydP1sCBA1VdXa1Dhw4pPz9f8+fP14ABA3w6CAAA/FmrYf3VV19Jkt5//329//77Ddb169dPqamp6tu3r5KSknTkyBGdP39eQUFBGjJkiDZs2KDp06f7pnIAAAJEq2G9a9euVncyYMAAPf/8814pCAAANMQjMgEAMBxhDQCA4QhrAAAMR1gDAGA4whoAAMMR1gAAGI6wBgDAcIQ1AACGI6wBADAcYQ0AgOEIawAADEdYAwBgOMIaAADDEdYAABiOsAYAwHCENdzmqK3r6BIAICB17egC0HmEhgRrygprR5fRooNZ6R1dAgB4HWfWAAAYjrAGAMBwhDUAAIYjrAEAMBxhDQCA4QhrAAAM1+pHt44fP6433nhDeXl5On36tHr27KnExEQtXbpUt9xyS4O2R48e1bPPPqsTJ06oe/fumjRpklasWKFu3br5bAAAAPi7VsP65Zdf1tGjRzVx4kTFxsaqtLRUu3fv1rRp07R//37ddtttkqSCggLNnTtXt99+u1atWqWSkhJt27ZNxcXFysnJ8flAAADwV62G9dy5c5WZmanQ0FDXsrS0NE2ZMkW5ubnasGGDJGnjxo3q2bOndu3apYiICElS//79tWbNGn300UdKSUnx0RAAAPBvrb5nnZSU1CCoJWnQoEEaMmSICgsLJUmVlZX68MMPNW3aNFdQS1J6errCw8N16NAhL5cNAEDgaNMNZk6nU+fPn1dUVJQk6eTJk7py5Yri4+MbtAsNDdXw4cNVUFDQ/koBAAhQbQrrAwcO6OzZs5o0aZIkqbS0VJIUHR3dqG10dLTOnTvXjhIBAAhsHj/Io7CwUGvXrlVycrLS0689NKGmpkaSGl0ulySLxeJa76n8/HyPt7HZbG3qy1/4cvzJyck+2zfgbzrytSjQXwcl/zsGHoV1aWmpHn/8cd10003Kzs5WUNC1E/OwsDBJksPhaLSN3W53rfdUfHy8LBaL2+1tNltAB0qgjx8wSUf9LvI60DmPgd1ub/EE1e2wrqio0Pz581VRUaE9e/Y0uORd///1l8OvV1paqpiYGE9qBgAA13HrPWu73a6FCxfq22+/1UsvvaTBgwc3WD906FB17dq10V8FDodDBQUFGj58uPcqBgAgwLQa1nV1dVq6dKk+//xzZWdnKyEhoVGbyMhIpaSkyGq1qqqqyrXcarWqurpaEydO9GrRAAAEklYvg2/YsEHvvfeexo0bp7KyMlmtVte6iIgIpaamSpKWLVum2bNnKyMjQzNnzlRJSYm2b9+usWPHatSoUb4bAQAAfq7VsP7qq68kSe+//77ef//9Buv69evnCuu4uDht375dmZmZWr9+vbp3764HHnhAy5cv90HZAAAEjlbDeteuXW7vbMSIEdq7d2+7CgIAAA3xiEwAAAxHWAMAYDjCGgAAwxHWAAAYjrAGAMBwhDUAAIYjrAEAMBxhDQCA4QhrAAAMR1gDAGA4whoAAMMR1gAAGI6wBgDAcIQ1AACGI6wBADAcYQ0AXuaoreuwvpOTk91q15E1wnNdO7oAAPA3oSHBmrLC2tFltOhgVnpHlwAPcGYNAIDhCGsAAAxHWAMAYDjCGgAAwxHWAAAYjrAGAMBwbn1069y5c9q5c6eOHTum/Px8VVdXa+fOnRo5cmSDdvfcc4/++te/Ntp+/vz5WrlypXcqBgAgwLgV1t98841yc3N1yy23KDY2Vp999lmzbePi4vToo482WDZ06ND2VQkAQABzK6zj4uL08ccfKyoqSu+8844WL17cbNvevXsrPZ0P2wMA4C1uhXX37t092qnD4VBdXZ26devWpqIAAMDfef0Gsz/96U9KSEhQQkKCUlNT9corr3i7CwAAAopXvxt86NChGjFihAYNGqS//e1vevXVV/XLX/5S5eXlWrBggTe7AgAgYHg1rHNychr8+0c/+pEeeughbdmyRQ8++KAiIyM92l9+fr7HNdhsNo+38Se+HL+7T/MB0Dn48+ulv43Np0/dCg4O1qOPPqply5bps88+09ixYz3aPj4+XhaLxe32NpstoAMl0McPwDP++nrRGV8L7XZ7iyeoPv9SlN69e0uSysvLfd0VAAB+yedhXVRUJEnq1auXr7sCAMAveS2sy8rKdPXq1QbL7Ha7tm7dqoiICCUkJHirKwAAAorb71lv2bJFklRYWChJslqtstls6tGjh+bMmaP33ntPOTk5mjBhgvr166eysjK98cYb+vbbb/WrX/1KERERvhkBAAB+zu2wzs7ObvDv1157TZLUr18/zZkzR0OHDtXgwYNltVp18eJFhYaGKi4uTqtWrdK4ceO8WzUAAAHE7bA+efJki+vj4+MbfXQLAAC0H4/IBADAcIQ1AACGI6wBADAcYQ0AgOEIawAADEdYAwBgOMIaAADDEdYAABiOsAYAwHCENQAAhiOsAQAwHGENAIDhCGsAAAxHWAMAYDjCGgAAwxHWAAAYjrAGAMBwhDUAAIYjrAEAMBxhDQCA4QhrAAAMR1gDAGA4whoAAMO5Fdbnzp1TZmamMjIylJiYqNjYWOXl5TXZ9t1339X06dN1xx136Ac/+IE2b96sK1eueLVoAAACiVth/c033yg3N1dnz55VbGxss+0++OADLV68WDfddJN+8YtfKDU1VS+88ILWr1/vtYIBAAg0Xd1pFBcXp48//lhRUVF65513tHjx4ibbPfPMM/rHf/xHbd26VcHBwZKkiIgI/ed//qcyMjI0aNAgrxUOAECgcOvMunv37oqKimqxzddff62vv/5as2bNcgW1JD300EO6evWqjhw50r5KAQAIUF67wezEiROSpPj4+AbLb775ZvXu3du1HgAAeMZrYV1aWipJio6ObrQuOjpa586d81ZXAAAEFLfes3ZHTU2NJCk0NLTROovFosuXL3u8z/z8fI+3sdlsHm9jimHD4xQRHtbm7ZOTk71YDQB/15lfL1vjb2PzWliHhV0LGYfD0Wid3W53rfdEfHy8LBaL2+1tNlunD6wpK6wdXUKzDmald3QJALyos79eNqczZoHdbm/xBNVrl8HrL3/XXw6/XmlpqWJiYrzVFQAAAcVrYT18+HBJjS9dnz17ViUlJa71AADAM14L6yFDhmjw4MF65ZVXVFdX51q+Z88eBQUF6d577/VWVwAABBS337PesmWLJKmwsFCSZLVaZbPZ1KNHD82ZM0eS9NOf/lSLFi3Sv/zLvygtLU2nTp3S7t27NWvWLN16660+KB8AAP/ndlhnZ2c3+Pdrr70mSerXr58rrMeNG6fNmzdr8+bNWrdunXr16qVFixbpxz/+sRdLBgAgsLgd1idPnnSrXWpqqlJTU9tcEAAAaIhHZAIAYDjCGgAAwxHWAAAYjrAGAMBwhDUAAIYjrAEAMBxhDQCA4QhrAAAMR1gDAGA4whoAAMMR1gAAGI6wBgDAcIQ1AACGI6wBADAcYQ0AgOEIawAIQI7auo4uoUWm13ejde3oAgAAN15oSLCmrLB2dBnNOpiV3tElGIUzawAADEdYAwBgOMIaAADDEdYAABiOsAYAwHCENQAAhvPqR7fy8vL0yCOPNLnu7bff1m233ebN7gAACAg++Zz1o48+qri4uAbLbr75Zl90BQCA3/NJWN99991KTU31xa4BAAg4PnvPurKyUleuXPHV7gEACBg+ObP+yU9+ourqanXt2lUjR47Uz372M8XGxvqiKwAA/J5XwzokJEQTJkzQ2LFjFRUVpZMnT2rbtm166KGHtH//ft16663e7A4AgIDg1bBOSkpSUlKS69/jx4/XPffco/vvv1+bN29WVlaWR/vLz8/3uAabzebxNqZITk7u6BIAwBjteT3vzFnQFJ8/dWvYsGFKSUnRxx9/7PG28fHxslgsbre32WwEHgD4iba+nnfGLLDb7S2eoN6QL0Xp06ePysvLb0RXAAD4nRsS1kVFRYqKiroRXQEA4He8GtYXL15stOzTTz9VXl6exowZ482uAAAIGF59z3rp0qXq1q2bEhMTFRUVpf/5n//RK6+8oqioKD355JPe7AoAgIDh1bBOTU3VwYMHtX37dlVWVqpXr16aPHmynnzySfXt29ebXQEAEDC8GtaPPPJIsw/yAAAAbcMjMgEAMBxhDQCA4QhrAAAMR1gDAGA4whoAAMMR1gAAGI6wBgDAcIQ1AACGI6wBADAcYQ0AgOEIawAADEdYAwBgOMIaAADDEdYAABiOsAYAwHCENQDAOI7aujZvm5yc7MVKmteeGj3V9Yb1BACAm0JDgjVlhbWjy2jRwaz0G9YXZ9YAABiOsAYAwHCENQAAhiOsAQAwHGENAIDhAiasb+Qt9gAAeJPXP7rlcDiUnZ0tq9WqS5cuadiwYVq2bJlSUlK83ZVH+BgAAKCz8vqZ9apVq7Rjxw5NnTpVP//5zxUUFKT58+frs88+83ZXAAAEBK+G9fHjx/XWW29p5cqV+ulPf6pZs2Zpx44d6tOnjzIzM73ZFQAAAcOrYf373/9eISEhmjlzpmuZxWLRjBkzZLPZdO7cOW92BwBAQPBqWBcUFOjWW29VREREg+V33nmnnE6nCgoKvNkdAAABwas3mJWWlurmm29utDw6OlqS3D6zdjqdkq7drOYpu93e7LqeEcEe7+9GstvtRtdoen2S+TWaXp9kfo2m1ydRozeYXp/Uct54qj7v6vPvu7o4m1vTBqmpqbr99tuVk5PTYHlRUZFSU1P1i1/8QnPmzGl1PxUVFTp16pS3ygIAoFMYOnSoIiMjGy336pl1WFiYamtrGy2v/+vDYrG4tZ+IiAgNHTpUISEh6tKlizdLBADAOE6nU7W1tY3eRq7n1bCOjo5u8lJ3aWmpJCkmJsat/QQFBTX5lwUAAP4qLCys2XVevcFs2LBh+uabb1RVVdVg+bFjx1zrAQCAZ7wa1hMnTlRtba327dvnWuZwOPT6668rKSmpyZvPAABAy7x6Gfyuu+7SxIkTlZmZqdLSUg0cOFBvvPGGTp8+rfXr13uzKwAAAoZX7waXrt1M9txzz+ngwYMqLy9XbGysli9frlGjRnmzGwAAAobXwxoAAHhXwDwiEwCAzoqwBgDAcIQ1AACGMzqsc3NzFRsbq/T09AbL3377ba1cuVITJkxQbGysMjIy3N5ncXGxYmNjm/zvv//7v709hHZpavyXL1/W7t27NW/ePI0ZM0aJiYmaPn269uzZo7q6Orf3vW/fPk2aNEl33HGHJkyYoN27d/tiCO3iq/E39/Pfs2ePr4bSZs39DmzatEn333+/Ro4cqTvvvFOTJk3S5s2bVV1d7fa+O+sckNo/fn+YA9errKzU6NGjFRsbq3feecftfXfmOXC9toy/M80Bycsf3fKm0tJSvfjiiwoPD2+0bs+ePcrPz1d8fLzKysratP+pU6dqzJgxDZaZ9KUtzY2/qKhI69atU0pKiubOnavu3bvrj3/8o371q1/piy++0NNPP93qvvfu3at///d/18SJEzVv3jx9+umnWrt2rex2ux577DFfDckjvhy/JI0ZM0ZTp05tsOyuu+7yWv3e0NLvQH5+vhISEpSenq6wsDB99dVXeumll5SXl6edO3e2+jW9nXkOSO0fv9T558D1XnjhBY/+UJM6/xy4XlvGL3WOOVDP2LDOyspSfHy8nE6nLl261GDdM888o5iYGAUHB7f411ZL4uLi2rztjdDc+P/hH/5BBw8e1JAhQ1zLZs+erdWrV+u1117TokWLNGDAgGb3W1NTo02bNmn8+PHKzs6WJD3wwAO6evWqNm/erJkzZxrxVa++Gn+9wYMHG/3zl1r+Hdi6dWuj9gMGDNCGDRuUn5+vO+64o9n9dvY5ILVv/PU6+xyo980332jXrl1auHCh/uM//sOt/frDHKjXlvHX6wxzoJ6Rl8GPHz+uAwcOaPXq1U2u79Onj4KD2//otOrq6jY9htPXWhp/r169GgRVvR/+8IeSpP/93/9tcd95eXkqKyvTQw891GD5ww8/rKqqKiPeCvDl+K9XU1Pj1UfceVNrvwNN6du3r6RrT61rSWefA81xd/zX84c5sH79eo0bN07/9E//5Pa+/WkOtGX81zN5DlzPuLB2Op1at26dpk2bpuHDh/usn+zsbCUmJurOO+/UrFmz9Mknn/isL0+0dfznz5+XJEVFRbXY7sSJE5Kk+Pj4Bsvj4uIUFBTkWt9RfD3+evv371dCQoLuvPNOTZkyRX/4wx/aVK8vuHsM6urqdPHiRZ09e1Z//OMf9dxzzykyMrLRz/a7/GUOtHX89fxhDnzwwQf68MMP9ZOf/MSj/fvLHGjr+OuZPAe+y7jL4G+++aa+/vprvfDCCz7Zf1BQkMaMGaMf/vCHiomJ0V/+8hdt3bpV8+bN029+8xuNGDHCJ/26qy3jdzgc2rFjhwYOHNjqC1VpaalCQ0PVs2fPBsvrlzX11LQbydfjl6TExESlpaWpf//+OnPmjHbu3KknnnhCWVlZmjx5cnvK9wp3j0FhYaGmTJni+vett96qLVu2qEePHi1u5y9zoK3jl/xjDtTW1urpp59WRkaGBg4cqDNnzri9f3+YA+0Zv2T+HPguo8K6srJSWVlZWrBggduP0/RU3759G73flZaWpvvuu0+ZmZnau3evT/p1R1vHv27dOhUWFio3N1dBQS1fLKmpqVFISEiT6ywWS4deDroR45fU6Gc8ffp0TZ48Wc8++6zuu+++Dn2GuifHoH///tq+fbuqq6t17Ngx/elPf2r0xLum+MscaOv4Jf+YAzt37lR5ebkWLVrkcR/+MAfaM37J7DnQFKMug7/44osKCQnRvHnzbmi/N998s+677z4dO3ZMly9fvqF9X68t43/55Zf16quvavny5frnf/7nVtuHhYU1+z693W6XxWJxu29vuxHjb0p4eLhmz56tkpISj97z9gVPjkF4eLhGjRql1NRUrVixQv/6r/+qH//4x/rqq69a3M5f5kBbx9/cvjrTHDh//ry2bNmiJ5980q0rCd/V2edAe8ffFJPmQFOMObM+d+6cduzYoSVLlrjef5SuTZza2loVFxcrMjJSN910k0/679Onj65evapLly6pW7duPumjJW0Z/+uvv67MzEw9/PDDWrBggVv9REdHq7a2VmVlZQ0ugTkcDpWVlfnsikZrbtT4m9OnTx9JUnl5ebv20x7t/R1ITU1VUFCQ3nrrrRY/huhPc+B67o6/OZ1pDuTk5CgyMlJjxoxRcXGxpL/ft3HhwgUVFxerX79+zZ4ddvY50N7xN8eEOdAcY8L6woULqq2tVWZmpjIzMxutHz9+vObPn6+VK1f6pP+ioiIFBwf77I+B1ng6/nfeeUdr1qzRvffeqzVr1rjdT/3NGvn5+Q0+Z56fn6+rV6/69Ka+ltyo8TenqKhI0rW7zTtKe38HamtrVVdX1+rd0P4yB77L3fE3pzPNgdOnT+vMmTO69957G7X55S9/Kena3dTNnSF39jnQ3vE3x4Q50Bxjwrp///5N3kzw3HPPqbq6Wk899ZQGDRrk0T4rKip07tw5xcTEuD4zePHixUY/iL/85S966623NGLECIWFhbV5DO3hyfg/+eQTLV++XCNGjFBmZmaz79NevnxZp0+fVlRUlGvM3//+99WzZ0/99re/bfBLumfPHoWHh2vs2LHeH5wbbtT4m/r5/+1vf9Nvf/tb9e/f3+M55k3uHoPKykqFhoYqNDS0Qbv9+/fL6XQqLi7Otcwf50B7x+8Pc6Cqqko/+tGPGrQ5deqUsrOztWDBAt11112u96T9cQ60d/wmz4HmGBPWkZGRSk1NbbR8x44dCg4ObrDuk08+cX3U6sKFC6qoqNCWLVskSffcc4/rEtgf/vAHrV69WuvXr3f9YJ999lkVFRXp+9//vmJiYvR///d/rhsNfvazn/l0jC1xd/x//etftWjRInXp0kUTJkzQoUOHGrRPSkpyfSnI8ePH9cgjj+iJJ57Qk08+Kenae1X/9m//prVr12rJkiUaM2aMPv30Ux04cEArV6702vs/nrpR49+9e7feffdd/eAHP1Dfvn119uxZvfLKK7p48aLPPoHgLnePQV5enlasWKFJkyZp0KBBqqurk81m0+HDhxt92Y8/zoH2jt8f5kBz20rXvoHr+nb+OAea21Zyb/wmz4HmGBPWnvj444+1efPmBsvqv4Wnd+/eLb5fNXr0aO3du1f/9V//pYqKCvXo0UOjR4/WE0880eSXbZimuLjYdZlv7dq1jdavX7++1W/wevjhhxUSEqJt27bp3XffVZ8+ffTzn/9cjzzyiE9q9qb2jj8xMVFHjx7Vvn37VF5ervDwcCUkJOjxxx9XcnKyz+r2pltuuUVjx47VBx98oH379qmurk4DBw7UwoULNX/+/EZnnE3pzHOgveP3hzngDZ15DrRXZ5wDXZxOp7OjiwAAAM0z6qNbAACgMcIaAADDEdYAABiOsAYAwHCENQAAhiOsAQAwHGENAIDhCGsAAAxHWAMAYDjCGgAAw/0/HHfGK2Ehkt8AAAAASUVORK5CYII=\n",
       "text/plain": [
        "<Figure size 576x432 with 1 Axes>"
       ]
@@ -267,7 +267,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -306,12 +306,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 720x576 with 1 Axes>"
       ]
@@ -417,12 +417,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 576x432 with 1 Axes>"
       ]
@@ -463,7 +463,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -802,12 +802,12 @@
     "\\end{align}\n",
     "$$\n",
     "\n",
-    "Where $\\hat{p} = (X_A + X_B)/(n_A + n_B)$"
+    "Donde $\\hat{p} = (X_A + X_B)/(n_A + n_B)$"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -844,7 +844,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -867,7 +867,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -1320,6 +1320,423 @@
     "3. Usar los conceptos y funciones definidas en este notebook para realizar una prueba de hipotesis, que pruebe o desmienta si los pasajeros mas ricos del Titanic tenian mayor tasa de supervivencia."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "titanic=pd.read_csv('./train-titanic.csv')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "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>PassengerId</th>\n",
+       "      <th>Survived</th>\n",
+       "      <th>Pclass</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Sex</th>\n",
+       "      <th>Age</th>\n",
+       "      <th>SibSp</th>\n",
+       "      <th>Parch</th>\n",
+       "      <th>Ticket</th>\n",
+       "      <th>Fare</th>\n",
+       "      <th>Cabin</th>\n",
+       "      <th>Embarked</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Braund, Mr. Owen Harris</td>\n",
+       "      <td>male</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>A/5 21171</td>\n",
+       "      <td>7.2500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
+       "      <td>female</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>PC 17599</td>\n",
+       "      <td>71.2833</td>\n",
+       "      <td>C85</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Heikkinen, Miss. Laina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>STON/O2. 3101282</td>\n",
+       "      <td>7.9250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>113803</td>\n",
+       "      <td>53.1000</td>\n",
+       "      <td>C123</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Allen, Mr. William Henry</td>\n",
+       "      <td>male</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>373450</td>\n",
+       "      <td>8.0500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   PassengerId  Survived  Pclass  \\\n",
+       "0            1         0       3   \n",
+       "1            2         1       1   \n",
+       "2            3         1       3   \n",
+       "3            4         1       1   \n",
+       "4            5         0       3   \n",
+       "\n",
+       "                                                Name     Sex   Age  SibSp  \\\n",
+       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
+       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
+       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
+       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
+       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
+       "\n",
+       "   Parch            Ticket     Fare Cabin Embarked  \n",
+       "0      0         A/5 21171   7.2500   NaN        S  \n",
+       "1      0          PC 17599  71.2833   C85        C  \n",
+       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
+       "3      0            113803  53.1000  C123        S  \n",
+       "4      0            373450   8.0500   NaN        S  "
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "titanic.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 891 entries, 0 to 890\n",
+      "Data columns (total 12 columns):\n",
+      " #   Column       Non-Null Count  Dtype  \n",
+      "---  ------       --------------  -----  \n",
+      " 0   PassengerId  891 non-null    int64  \n",
+      " 1   Survived     891 non-null    int64  \n",
+      " 2   Pclass       891 non-null    int64  \n",
+      " 3   Name         891 non-null    object \n",
+      " 4   Sex          891 non-null    object \n",
+      " 5   Age          714 non-null    float64\n",
+      " 6   SibSp        891 non-null    int64  \n",
+      " 7   Parch        891 non-null    int64  \n",
+      " 8   Ticket       891 non-null    object \n",
+      " 9   Fare         891 non-null    float64\n",
+      " 10  Cabin        204 non-null    object \n",
+      " 11  Embarked     889 non-null    object \n",
+      "dtypes: float64(2), int64(5), object(5)\n",
+      "memory usage: 83.7+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "titanic.info()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### La hipotesis nula creo que sería: Los pasajeros ricos del Titanic NO tenian una tasa de sobrevivencia mas alta.\n",
+    "\n",
+    "## Hipotesis p\n",
+    "\n",
+    "\n",
+    "### La hipotesis B sería: Los pasajeros ricos del Titanic SI tenian una tasa de sobrevivnecia mas alta\n",
+    "\n",
+    "### ¿Que es un exito de A (o de la hipotesis nula)?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Int64Index: 342 entries, 1 to 889\n",
+      "Data columns (total 12 columns):\n",
+      " #   Column       Non-Null Count  Dtype  \n",
+      "---  ------       --------------  -----  \n",
+      " 0   PassengerId  342 non-null    int64  \n",
+      " 1   Survived     342 non-null    int64  \n",
+      " 2   Pclass       342 non-null    int64  \n",
+      " 3   Name         342 non-null    object \n",
+      " 4   Sex          342 non-null    object \n",
+      " 5   Age          290 non-null    float64\n",
+      " 6   SibSp        342 non-null    int64  \n",
+      " 7   Parch        342 non-null    int64  \n",
+      " 8   Ticket       342 non-null    object \n",
+      " 9   Fare         342 non-null    float64\n",
+      " 10  Cabin        136 non-null    object \n",
+      " 11  Embarked     340 non-null    object \n",
+      "dtypes: float64(2), int64(5), object(5)\n",
+      "memory usage: 34.7+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Hacemos un dataframe donde solo aparecen que sobrevivieron\n",
+    "sobrevivieron=titanic[titanic[\"Survived\"]==1]\n",
+    "sobrevivieron.info()\n",
+    "#print(sobrevivieron.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Int64Index: 136 entries, 1 to 889\n",
+      "Data columns (total 12 columns):\n",
+      " #   Column       Non-Null Count  Dtype  \n",
+      "---  ------       --------------  -----  \n",
+      " 0   PassengerId  136 non-null    int64  \n",
+      " 1   Survived     136 non-null    int64  \n",
+      " 2   Pclass       136 non-null    int64  \n",
+      " 3   Name         136 non-null    object \n",
+      " 4   Sex          136 non-null    object \n",
+      " 5   Age          122 non-null    float64\n",
+      " 6   SibSp        136 non-null    int64  \n",
+      " 7   Parch        136 non-null    int64  \n",
+      " 8   Ticket       136 non-null    object \n",
+      " 9   Fare         136 non-null    float64\n",
+      " 10  Cabin        117 non-null    object \n",
+      " 11  Embarked     134 non-null    object \n",
+      "dtypes: float64(2), int64(5), object(5)\n",
+      "memory usage: 13.8+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Hacemos un DataFrame con los pobres que sobrevivieron\n",
+    "pobres_sobreviven=sobrevivieron[sobrevivieron[\"Pclass\"]==1]\n",
+    "pobres_sobreviven.info()\n",
+    "\n",
+    "#print(total_de_pobres_sobreviven)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Int64Index: 206 entries, 2 to 880\n",
+      "Data columns (total 12 columns):\n",
+      " #   Column       Non-Null Count  Dtype  \n",
+      "---  ------       --------------  -----  \n",
+      " 0   PassengerId  206 non-null    int64  \n",
+      " 1   Survived     206 non-null    int64  \n",
+      " 2   Pclass       206 non-null    int64  \n",
+      " 3   Name         206 non-null    object \n",
+      " 4   Sex          206 non-null    object \n",
+      " 5   Age          168 non-null    float64\n",
+      " 6   SibSp        206 non-null    int64  \n",
+      " 7   Parch        206 non-null    int64  \n",
+      " 8   Ticket       206 non-null    object \n",
+      " 9   Fare         206 non-null    float64\n",
+      " 10  Cabin        19 non-null     object \n",
+      " 11  Embarked     206 non-null    object \n",
+      "dtypes: float64(2), int64(5), object(5)\n",
+      "memory usage: 20.9+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Hacemos un DataFrame con los Ricos que sobrevivieron\n",
+    "ricos_sobreviven=sobrevivieron[sobrevivieron[\"Pclass\"]!=1]\n",
+    "ricos_sobreviven.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Total de Sobreviventes 342\n",
+      "Total de Pobres que Sobrevivieron 136\n",
+      "Total de Ricos que Sobreviveron 206\n"
+     ]
+    }
+   ],
+   "source": [
+    "total_sobreviventes=sobrevivieron.shape[0]\n",
+    "print(\"Total de Sobreviventes\",total_sobreviventes)\n",
+    "\n",
+    "total_pobres_sobreviventes=pobres_sobreviven.shape[0]\n",
+    "print(\"Total de Pobres que Sobrevivieron\",total_pobres_sobreviventes)\n",
+    "\n",
+    "total_ricos_sobreviventes=ricos_sobreviven.shape[0]\n",
+    "print(\"Total de Ricos que Sobreviveron\",total_ricos_sobreviventes)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "valor z = 5.353, pvalue = 0.000\n"
+     ]
+    }
+   ],
+   "source": [
+    "zscore_titanic, pvalue_titanic = test_de_dos_proporciones(136, 342, 206, 342)\n",
+    "print('valor z = {:.3f}, pvalue = {:.3f}'.format(zscore_titanic, pvalue_titanic))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -1344,6 +1761,13 @@
     "- [Slideshare: 4 Steps Toward Scientific A/B Testing](https://www.slideshare.net/RJMetrics/4-steps-toward-scientific-ab-testing)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": null,