Module-4/Intro to regression.ipynb

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    "## Intro to Regression\n",
    "\n",
    "[intro desmos](https://www.desmos.com/calculator/ywloazwete)\n",
    "\n",
    "Goals:\n",
    "- use statsmodels to build a regression model\n",
    "- use summary statistics to evaluate a model\n",
    "- differentiate between corr, cov, and R squared"
   ]
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   "source": [
    "import pandas as pd\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.formula.api import ols\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('seaborn')"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "`.cov` , `.corr`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[link to dataset](https://raw.githubusercontent.com/chasinginfinity/ml-from-scratch/master/03%20Linear%20Regression%20in%202%20minutes/data.csv)"
   ]
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   "source": [
    "model = ols(formula=f, data=df).fit()"
   ]
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   "source": [
    "## Beginner\n",
    "### Problem One: Chopsticks\n",
    "#### Is chopstick length correlated with effectiveness?"
   ]
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  {
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   "source": [
    "chopsticks = pd.read_csv(\"http://blog.yhat.com/static/misc/data/chopstick-effectiveness.csv\")"
   ]
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   "source": [
    "chopsticks.head()"
   ]
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   "source": [
    "[Link to chopsticks study](https://www.ncbi.nlm.nih.gov/pubmed/15676839)"
   ]
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   "source": [
    "## Intermediate:\n",
    "### Problem Three: Street price of weed\n",
    "[reference](http://blog.yhat.com/posts/7-funny-datasets.html)\n",
    "\n",
    "Has the price of weed been trending downward or upward over time? \n",
    "- overall?\n",
    "- different in certain states?\n",
    "- different qualities?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "weed = pd.read_csv(\"http://blog.yhat.com/static/misc/data/marijuana-street-price-clean.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "weed.head()"
   ]
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   "cell_type": "markdown",
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   "source": [
    "## Advanced\n",
    "### DC housing\n",
    "### Doing repeat OLS, which variables are related to housing price?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing = pd.read_csv(\"https://drive.google.com/uc?export=download&id=1DsbpIf4_9CAKNd-B9gaML1WKOJcMne71\")"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing.head()"
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   "execution_count": null,
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   "outputs": [],
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