Skip to content

Commit 49cdf30

Browse files
committed
Correct typos
1. "scraping" replaces "scrapping" 2. Correct spelling of equivalence 3. Add hyperlink for Reference 2
1 parent 6a11db4 commit 49cdf30

File tree

1 file changed

+4
-4
lines changed

1 file changed

+4
-4
lines changed

Chapter4_TheGreatestTheoremNeverTold/LawOfLargeNumbers.ipynb

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -489,7 +489,7 @@
489489
"cell_type": "markdown",
490490
"metadata": {},
491491
"source": [
492-
"One way to determine a prior on the upvote ratio is that look at the historical distribution of upvote ratios. This can be accomplished by scrapping Reddit's comments and determining a distribution. There are a few problems with this technique though:\n",
492+
"One way to determine a prior on the upvote ratio is that look at the historical distribution of upvote ratios. This can be accomplished by scraping Reddit's comments and determining a distribution. There are a few problems with this technique though:\n",
493493
"\n",
494494
"1. Skewed data: The vast majority of comments have very few votes, hence there will be many comments with ratios near the extremes (see the \"triangular plot\" in the above Kaggle dataset), effectively skewing our distribution to the extremes. One could try to only use comments with votes greater than some threshold. Again, problems are encountered. There is a tradeoff between number of comments available to use and a higher threshold with associated ratio precision. \n",
495495
"2. Biased data: Reddit is composed of different subpages, called subreddits. Two examples are *r/aww*, which posts pics of cute animals, and *r/politics*. It is very likely that the user behaviour towards comments of these two subreddits are very different: visitors are likely friend and affectionate in the former, and would therefore upvote comments more, compared to the latter, where comments are likely to be controversial and disagreed upon. Therefore not all comments are the same. \n",
@@ -995,7 +995,7 @@
995995
"& b = 1 + N - S \\\\\\\\\n",
996996
"\\end{align}\n",
997997
"\n",
998-
"where $N$ is the number of users who rated, and $S$ is the sum of all the ratings, under the equivilance scheme mentioned above. "
998+
"where $N$ is the number of users who rated, and $S$ is the sum of all the ratings, under the equivalence scheme mentioned above. "
999999
]
10001000
},
10011001
{
@@ -1133,7 +1133,7 @@
11331133
"### References\n",
11341134
"\n",
11351135
"1. Wainer, Howard. *The Most Dangerous Equation*. American Scientist, Volume 95.\n",
1136-
"2. Clarck, Torin K., Aaron W. Johnson, and Alexander J. Stimpson. \"Going for Three: Predicting the Likelihood of Field Goal Success with Logistic Regression.\" (2013): n. page. Web. 20 Feb. 2013.\n",
1136+
"2. Clarck, Torin K., Aaron W. Johnson, and Alexander J. Stimpson. \"Going for Three: Predicting the Likelihood of Field Goal Success with Logistic Regression.\" (2013): n. page. [Web](http://www.sloansportsconference.com/wp-content/uploads/2013/Going%20for%20Three%20Predicting%20the%20Likelihood%20of%20Field%20Goal%20Success%20with%20Logistic%20Regression.pdf). 20 Feb. 2013.\n",
11371137
"3. http://en.wikipedia.org/wiki/Beta_function#Incomplete_beta_function"
11381138
]
11391139
},
@@ -1236,4 +1236,4 @@
12361236
"metadata": {}
12371237
}
12381238
]
1239-
}
1239+
}

0 commit comments

Comments
 (0)