Merge pull request CamDavidsonPilon#343 from HenrikEckermann/master

Missing word 'increases' in Ch6

Author: CamDavidsonPilon

Chapter6_Priorities/Ch6_Priors_PyMC2.ipynb

@@ -1527,7 +1527,7 @@
    "source": [
     "## Effect of the prior as $N$ increases\n",
     "\n",
-    "In the first chapter, I proposed that as the amount of observations, or data, that we posses, the less the prior matters. This is intuitive. After all, our prior is based on previous information, and eventually enough new information will shadow our previous information's value. The smothering of the prior by enough data is also helpful: if our prior is significantly wrong, then the self-correcting nature of the data will present to us a *less wrong*, and eventually *correct*, posterior. \n",
+    "In the first chapter, I proposed that as the amount of our observations or data increases, the influence of the prior decreases. This is intuitive. After all, our prior is based on previous information, and eventually enough new information will shadow our previous information's value. The smothering of the prior by enough data is also helpful: if our prior is significantly wrong, then the self-correcting nature of the data will present to us a *less wrong*, and eventually *correct*, posterior. \n",
     "\n",
     "We can see this mathematically. First, recall Bayes Theorem from Chapter 1 that relates the prior to the posterior. The following is a sample from [What is the relationship between sample size and the influence of prior on posterior?](http://stats.stackexchange.com/questions/30387/what-is-the-relationship-between-sample-size-and-the-influence-of-prior-on-poste)[1] on CrossValidated.\n",
     "\n",
@@ -2512,9 +2512,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [conda env:bayes]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "conda-env-bayes-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -2526,7 +2526,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.0"
   }
  },
  "nbformat": 4,

Chapter6_Priorities/Ch6_Priors_PyMC3.ipynb

@@ -1529,7 +1529,7 @@
    "source": [
     "## Effect of the prior as $N$ increases\n",
     "\n",
-    "In the first chapter, I proposed that as the amount of observations, or data, that we posses, the less the prior matters. This is intuitive. After all, our prior is based on previous information, and eventually enough new information will shadow our previous information's value. The smothering of the prior by enough data is also helpful: if our prior is significantly wrong, then the self-correcting nature of the data will present to us a *less wrong*, and eventually *correct*, posterior. \n",
+    "In the first chapter, I proposed that as the amount of our observations or data increases, the influence of the prior decreases. This is intuitive. After all, our prior is based on previous information, and eventually enough new information will shadow our previous information's value. The smothering of the prior by enough data is also helpful: if our prior is significantly wrong, then the self-correcting nature of the data will present to us a *less wrong*, and eventually *correct*, posterior. \n",
     "\n",
     "We can see this mathematically. First, recall Bayes Theorem from Chapter 1 that relates the prior to the posterior. The following is a sample from [What is the relationship between sample size and the influence of prior on posterior?](http://stats.stackexchange.com/questions/30387/what-is-the-relationship-between-sample-size-and-the-influence-of-prior-on-poste)[1] on CrossValidated.\n",
     "\n",
@@ -1813,9 +1813,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [conda env:bayes]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "conda-env-bayes-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1827,7 +1827,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.0"
   }
  },
  "nbformat": 4,