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Use correct statistical terminology #2

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Use correct statistical terminology #2

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8 changes: 4 additions & 4 deletions Percentiles.ipynb
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Expand Up @@ -200,11 +200,11 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"## The Central Limit Theorem\n",
"## The Law of Large Numbers\n",
"\n",
"Before we continue with our story, let's review some stats.\n",
"\n",
"You may recall from school that there's a handy thing called the [Central Limit Theorem](https://en.wikipedia.org/wiki/Central_limit_theorem). The CLT basically says this: The average of a large enough sample will be pretty close to the \"real\" average, give or take some error.\n",
"You may recall from school that there's a handy thing called the [Law of large numbers](https://en.wikipedia.org/wiki/Law_of_large_numbers). The LLN basically says this: The average of a large enough sample will be pretty close to the \"real\" average, give or take some error.\n",
"\n",
"This is pretty handy for measuring a lot of things—it means that even a relatively small sample can give us a pretty good measure of the population average.\n",
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I'd like to see this statement quantified. I don't think the LLN makes guarantees about sample sizes out of the box, but is a general statement on expectations.

"\n",
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"cell_type": "markdown",
"metadata": {},
"source": [
"Nice, the average of all of our sample averages is pretty damn close to the real average. This is the central limit theorem in action!"
"Nice, the average of all of our sample averages is pretty damn close to the real average. This is the law of large numbers in action!"
]
},
{
Expand All @@ -280,7 +280,7 @@
"source": [
"## Percentiles are trickier\n",
"\n",
"Unfortunately, the central limit theorem doesn't apply to percentiles. As proof, let's try the same procedure, but for the 99th percentile. As a reminder, the \"real\" p99 of our dataset is this:"
"Unfortunately, the law of large numbers doesn't apply to percentiles. As proof, let's try the same procedure, but for the 99th percentile. As a reminder, the \"real\" p99 of our dataset is this:"
]
},
{
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