<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Probability | Zhu Xuelin</title><link>https://linstats.github.io/tags/probability/</link><atom:link href="https://linstats.github.io/tags/probability/index.xml" rel="self" type="application/rss+xml"/><description>Probability</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Sat, 25 Jan 2025 00:00:00 +0000</lastBuildDate><image><url>https://linstats.github.io/media/icon_hu15689388221013369737.png</url><title>Probability</title><link>https://linstats.github.io/tags/probability/</link></image><item><title>How Many Cups of Coffee Can I Buy with $10?</title><link>https://linstats.github.io/teaching/coffee-sim/</link><pubDate>Sat, 25 Jan 2025 00:00:00 +0000</pubDate><guid>https://linstats.github.io/teaching/coffee-sim/</guid><description>&lt;p>Imagine this: I’m a coffee lover with only 10 dollars to spend. But here’s the twist—each cup of coffee costs a random price between 0 and 10 dollars. So, on average, how many cups can I actually buy?&lt;/p>
&lt;p>If you’re curious about the answer, check out the video!&lt;/p>
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&lt;p style="text-align: center; width: 100%;">Buying Coffee&lt;/p>
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&lt;p>For a theoretical justification (a little probability theory is needed), you can watch the video (in Chinese) below:&lt;/p>
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&lt;iframe src="https://www.youtube.com/embed/DpiuByapGmA" scrolling="no" border="0" frameborder="no" framespacing="0" allowfullscreen="true" width="800" height="450"> &lt;/iframe>
&lt;/div></description></item><item><title>What Is the Sample Space in Statistics?</title><link>https://linstats.github.io/teaching/sample-space/</link><pubDate>Wed, 13 Nov 2024 00:00:00 +0000</pubDate><guid>https://linstats.github.io/teaching/sample-space/</guid><description>&lt;p>In statistics, we often work with independently and identically distributed (iid) samples. For instance, consider a set of observations:
$
(X_1, X_2,\dots,X_{10}).
$
However, what is the underlying sample space (a foundational concept from probability) associated with these samples?&lt;/p>
&lt;p>Specifically, let&amp;rsquo;s take an element
$
\omega\in\Omega,
$
where this
$
\omega
$
represent an individual like Alice. How, then, could we use
$
X_1
$
to denote Alice and, simultaneously,
$
X_2
$
to denote another individual, say Bob?&lt;/p>
&lt;p>This question once confused me for years. If you are having the same trouble, check out the video!&lt;/p>
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&lt;source src="images/6120-v1tut-space.mp4" type="video/mp4">
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&lt;p style="text-align: center; width: 100%;">Sample Space&lt;/p>
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