fixed typo and deleted old note

Author: jrfiedler

chapter12.ipynb

@@ -40,7 +40,9 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "from collections import OrderedDict\n",
@@ -151,7 +153,9 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "restriction_cols = [\n",
@@ -191,7 +195,9 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "nhefs['constant'] = 1\n",
@@ -417,7 +423,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We're going to be modeling with sqaured terms and some categorical features. Here we'll explicitly add squared features and dummy features to the data. In later chapters we'll use Statsmodels' formula syntax."
+    "We're going to be modeling with squared terms and some categorical features. Here we'll explicitly add squared features and dummy features to the data. In later chapters we'll use Statsmodels' formula syntax."
    ]
   },
   {
@@ -430,7 +436,9 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "for col in ['age', 'wt71', 'smokeintensity', 'smokeyrs']:\n",
@@ -803,7 +811,9 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "crosstab = pd.crosstab(subset.age, subset.qsmk).sort_index()"
@@ -1146,7 +1156,9 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "s_weights = np.zeros(nhefs.shape[0])\n",
@@ -1464,7 +1476,9 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "fAL = scipy.stats.norm.pdf(\n",
@@ -1587,7 +1601,9 @@
   {
    "cell_type": "code",
    "execution_count": 51,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "y = intensity25.wt82_71\n",
@@ -1656,13 +1672,6 @@
     "\"if interested in the causal effect of quitting smoking A (1: yes, 0: no) on the risk of death D (1: yes, 0: no) by 1992, one could consider a _marginal structural logistic model_\""
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Note: the numbers below don't match"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 53,
@@ -2277,7 +2286,9 @@
   {
    "cell_type": "code",
    "execution_count": 77,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "wls = sm.WLS(\n",
@@ -2323,6 +2334,7 @@
   }
  ],
  "metadata": {
+  "anaconda-cloud": {},
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",