6_Room_Assignment.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/6_Room_Assignment.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: In a school with 120 students, 60% of them enjoy playing basketball, and the rest do not. They are randomly split into two equally sized rooms. What is the probability that a student in the first room enjoys playing basketball?\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "# 2. Standard Solution:\n",
        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        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6w6v56sG8JM5"
      },
      "source": [
        "# 3. Programing Solution"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "DfJ6ZrpE5ENT"
      },
      "outputs": [],
      "source": [
        "# P(A|R1) = P(A)\n",
        "def room_assignment(hobbie_prob):\n",
        "  return hobbie_prob"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 4. Testing"
      ],
      "metadata": {
        "id": "cGhnls8XQ4y2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "prob = room_assignment(0.60)\n",
        "assert prob == 0.60, f'Incorrect if 60% enjoy play basketball and room are equaly sized, it should be 0.60, returned:{prob}'\n",
        "\n",
        "print('Probability computed correctly')"
      ],
      "metadata": {
        "id": "-ssg19G9Q8Kl",
        "outputId": "ac5b6af5-1b7a-4887-fda5-1800d164b98b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Probability computed correctly\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "7WaBAgI5RWVp"
      },
      "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
}