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      "source": [
        "# Chapter 18: Simple Linear Regression\n",
        "**Economic question:** How does consumption change with income in a simple model?\n",
        "\nOLS chooses the line that minimizes the sum of squared residuals.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import statsmodels.api as sm\n",
        "rng=np.random.default_rng(18)\n",
        "income=np.linspace(20,100,120)\n",
        "cons=8+0.55*income+rng.normal(0,8,120)\n",
        "res=sm.OLS(cons,sm.add_constant(income)).fit()\n",
        "print(res.summary())\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Interpretation checklist\n",
        "- State the unit of observation and units of every variable.\n",
        "- Separate association, prediction, and causation.\n",
        "- Report magnitude and uncertainty.\n",
        "- Identify the most important threat to validity.\n"
      ]
    }
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    "ceteris_lab": {
      "course_slug": "fundamentals-python-econometrics",
      "course_title": "Fundamentals of Python for Financial Econometrics",
      "chapter": 18,
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