10_Getting_Black_Ball_and_White_Ball.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/gmdeorozco/Probability-Problems-Python-Solutions/blob/main/10_Getting_Black_Ball_and_White_Ball.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3_Nw-GnY5lRT"
      },
      "source": [
        "# 1. Problem: If you have a bag with 10 black balls and 5 white balls, what is the probability of drawing a black ball on the first draw and a white ball on the second draw without replacement?\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "# 2. Standard Solution:\n",
        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)\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6w6v56sG8JM5"
      },
      "source": [
        "# 3. Programing Solution"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "id": "DfJ6ZrpE5ENT",
        "outputId": "3979ed88-5bae-4e23-a60b-8a9141c4d356",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.23809523809523808\n"
          ]
        }
      ],
      "source": [
        "def prob_getting_black_ball_then_white_ball():\n",
        "  # P(Black Ball) = #black_balls / total_balls\n",
        "  prob_black_ball = 10/15\n",
        "\n",
        "  #P(White Ball | Given Black ball was taken) = #white_balls / remaining_balls\n",
        "  prob_white_ball = 5 /(15-1)\n",
        "\n",
        "  prob_event = prob_black_ball * prob_white_ball\n",
        "  return prob_event\n",
        "\n",
        "print(prob_getting_black_ball_then_white_ball())\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "M8TsxGWJv1W8"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "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": "3.12.0"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}