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                  "=== Calculadora de Tamaño de Muestra Financiera ===\n",
                  "Tipo de estudio: Proporción\n",
                  "Nivel de confianza: 95%  (Z=1.96)\n",
                  "Error permitido: 5.0%\n",
                  "Proporción esperada: 50%\n",
                  "Población total: 1000\n",
                  "Tamaño de muestra necesario: 278 personas/observaciones\n",
                  "\n",
                  "💡 Consejos financieros para los alumnos:\n",
                  "- Para estudios de clientes, usar proporción p=50% si no hay datos previos, asegura tamaño máximo de muestra.\n",
                  "- Para estudios de ingresos o rendimientos, ajustar desviación estándar según datos históricos.\n",
                  "- Si la población es pequeña, considerar ajuste por población finita para no sobredimensionar la muestra.\n",
                  "- Menor error permitido o mayor confianza => mayor tamaño de muestra.\n"
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              "interactive(children=(Dropdown(description='finance_focus', options=('Proporción', 'Media'), value='Proporción…"
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              "<function __main__.calculadora_muestra(finance_focus='Proporción', nivel_confianza=95, error=5, proporcion=50, desviacion=10, poblacion_total=1000)>"
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              "         var(--colab-secondary-surface-color); padding: 8px 12px;\n",
              "         border-bottom: 1px solid var(--colab-border-color);\"><b>calculadora_muestra</b><br/>def calculadora_muestra(finance_focus=&#x27;Proporción&#x27;, nivel_confianza=95, error=5, proporcion=50, desviacion=10, poblacion_total=1000)</pre><pre class=\"function-repr-contents function-repr-contents-collapsed\" style=\"\"><a class=\"filepath\" style=\"display:none\" href=\"#\">/tmp/ipykernel_3106/940686171.py</a>Calcula tamaño de muestra según tipo de estudio:\n",
              "1. Proporción (para encuestas, clientes, riesgo)\n",
              "2. Media (para ingresos, ventas, rendimiento)\n",
              "\n",
              "Parámetros:\n",
              "- finance_focus: &#x27;Proporción&#x27; o &#x27;Media&#x27;\n",
              "- nivel_confianza: Nivel de confianza en %, típico 90, 95, 99\n",
              "- error: Error permitido en %\n",
              "- proporcion: Proporción esperada (solo para estudios de proporción)\n",
              "- desviacion: Desviación estándar estimada (solo para media)\n",
              "- poblacion_total: Tamaño total de la población (opcional)</pre></div>"
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        "# 📦 Librerías necesarias\n",
        "import numpy as np\n",
        "from ipywidgets import interact, FloatSlider, IntSlider\n",
        "import math\n",
        "\n",
        "# 🔹 Función para calcular tamaño de muestra\n",
        "def calculadora_muestra(finance_focus='Proporción', nivel_confianza=95, error=5, proporcion=50, desviacion=10, poblacion_total=1000):\n",
        "    \"\"\"\n",
        "    Calcula tamaño de muestra según tipo de estudio:\n",
        "    1. Proporción (para encuestas, clientes, riesgo)\n",
        "    2. Media (para ingresos, ventas, rendimiento)\n",
        "\n",
        "    Parámetros:\n",
        "    - finance_focus: 'Proporción' o 'Media'\n",
        "    - nivel_confianza: Nivel de confianza en %, típico 90, 95, 99\n",
        "    - error: Error permitido en %\n",
        "    - proporcion: Proporción esperada (solo para estudios de proporción)\n",
        "    - desviacion: Desviación estándar estimada (solo para media)\n",
        "    - poblacion_total: Tamaño total de la población (opcional)\n",
        "    \"\"\"\n",
        "\n",
        "    # Convertimos porcentajes a decimales\n",
        "    e = error / 100\n",
        "    p = proporcion / 100\n",
        "\n",
        "    # Valores Z para niveles de confianza comunes\n",
        "    z_dict = {90: 1.645, 95: 1.96, 99: 2.576}\n",
        "\n",
        "    if nivel_confianza not in z_dict:\n",
        "        print(\"Nivel de confianza no soportado. Usar 90, 95 o 99%.\")\n",
        "        return\n",
        "\n",
        "    z = z_dict[nivel_confianza]\n",
        "\n",
        "    # 🔹 Calculamos tamaño de muestra según tipo\n",
        "    if finance_focus == 'Proporción':\n",
        "        n0 = (z**2 * p * (1-p)) / (e**2)\n",
        "    elif finance_focus == 'Media':\n",
        "        n0 = (z**2 * (desviacion**2)) / (e**2)\n",
        "    else:\n",
        "        print(\"Seleccione un tipo válido: 'Proporción' o 'Media'\")\n",
        "        return\n",
        "\n",
        "    # 🔹 Ajuste por población finita si es relevante\n",
        "    if poblacion_total > 0:\n",
        "        n = n0 / (1 + (n0 - 1)/poblacion_total)\n",
        "    else:\n",
        "        n = n0\n",
        "\n",
        "    n = math.ceil(n)  # Redondeamos al entero siguiente\n",
        "\n",
        "    # 🔹 Mostrar resultados\n",
        "    print(\"=== Calculadora de Tamaño de Muestra Financiera ===\")\n",
        "    print(f\"Tipo de estudio: {finance_focus}\")\n",
        "    print(f\"Nivel de confianza: {nivel_confianza}%  (Z={z})\")\n",
        "    print(f\"Error permitido: {error}%\")\n",
        "\n",
        "    if finance_focus == 'Proporción':\n",
        "        print(f\"Proporción esperada: {proporcion}%\")\n",
        "    else:\n",
        "        print(f\"Desviación estándar estimada: {desviacion}\")\n",
        "\n",
        "    print(f\"Población total: {poblacion_total if poblacion_total>0 else 'No aplica'}\")\n",
        "    print(f\"Tamaño de muestra necesario: {n} personas/observaciones\")\n",
        "\n",
        "    # 🔹 Consejos prácticos\n",
        "    print(\"\\n💡 Consejos financieros para los alumnos:\")\n",
        "    print(\"- Para estudios de clientes, usar proporción p=50% si no hay datos previos, asegura tamaño máximo de muestra.\")\n",
        "    print(\"- Para estudios de ingresos o rendimientos, ajustar desviación estándar según datos históricos.\")\n",
        "    print(\"- Si la población es pequeña, considerar ajuste por población finita para no sobredimensionar la muestra.\")\n",
        "    print(\"- Menor error permitido o mayor confianza => mayor tamaño de muestra.\")\n",
        "\n",
        "# 🔹 Interactividad con sliders\n",
        "interact(\n",
        "    calculadora_muestra,\n",
        "    finance_focus=['Proporción', 'Media'],\n",
        "    nivel_confianza=IntSlider(value=95, min=90, max=99, step=1, description='Confianza (%)'),\n",
        "    error=FloatSlider(value=5, min=1, max=10, step=0.5, description='Error (%)'),\n",
        "    proporcion=IntSlider(value=50, min=0, max=100, step=5, description='Proporción (%)'),\n",
        "    desviacion=FloatSlider(value=10, min=1, max=50, step=1, description='Desviación'),\n",
        "    poblacion_total=IntSlider(value=1000, min=0, max=5000, step=50, description='Población')\n",
        ")"
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