deploy: f34e601

Author: blakebyer

assets/css/main.css.map

@@ -36,7 +36,7 @@ var store = [{
         "teaser": null
       },{
         "title": "Introduction to Statistics for Biologists",
-        "excerpt":"Why learn statistics? Statistics are the backbone of impactful, reproducible research. Properly done, statistics provide us with basis for cause and effect (known as causal inference). I wanted to write a few supplementary articles for myself and others to understand the basics of probability, statistics, and linear algebra to boost...","categories": ["blog"],
+        "excerpt":"Why learn statistics? Statistics is the backbone of impactful, reproducible research. Properly done, statistics provide us with basis for cause and effect (known as causal inference). I wanted to write a few supplementary articles for myself and others to understand the basics of probability, statistics, and linear algebra to boost...","categories": ["blog"],
         "tags": [],
         "url": "/blog/2025/07/30/statsintro.html",
         "teaser": null

assets/js/lunr/lunr-store.js

@@ -208,7 +208,7 @@ <h1 id="page-title" class="page__title" itemprop="headline">
       <section class="page__content" itemprop="text">
 
         <h2 id="why-learn-statistics">Why learn statistics?</h2>
-<p>Statistics are the backbone of impactful, reproducible research. Properly done, statistics provide us with basis for cause and effect (known as causal inference). I wanted to write a few supplementary articles for myself and others to understand the basics of probability, statistics, and linear algebra to boost their research. If you get stuck on the notation, please check the <a href="/blog/2025/07/30/mathnotation.html">Math Notation Sheet</a>. First, an inspiring image from our friends in biostatistics, a sub-field of statistics devoted to creating and applying statistical methods to biological or medical data.</p>
+<p>Statistics is the backbone of impactful, reproducible research. Properly done, statistics provide us with basis for cause and effect (known as causal inference). I wanted to write a few supplementary articles for myself and others to understand the basics of probability, statistics, and linear algebra to boost their research. If you get stuck on the notation, please check the <a href="/blog/2025/07/30/mathnotation.html">Math Notation Sheet</a>. First, an inspiring image from our friends in biostatistics, a sub-field of statistics devoted to creating and applying statistical methods to biological data.</p>
 
 <figure>
   <img src="/assets/images/ebpi_research_dep_biostatistics_2480x1529px.png" alt="Biostatistics" />

blog/2025/07/30/statsintro.html

@@ -1,4 +1,4 @@
-<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="4.4.1">Jekyll</generator><link href="https://blakebyer.github.io//feed.xml" rel="self" type="application/atom+xml" /><link href="https://blakebyer.github.io//" rel="alternate" type="text/html" /><updated>2025-07-31T00:07:57+00:00</updated><id>https://blakebyer.github.io//feed.xml</id><title type="html">Blake Byer</title><subtitle>This is the personal webpage of Blake Byer.</subtitle><author><name>Blake Byer</name><email>bbyer04@gmail.com</email></author><entry><title type="html">Math Symbols Cheat Sheet</title><link href="https://blakebyer.github.io//blog/2025/07/30/mathnotation.html" rel="alternate" type="text/html" title="Math Symbols Cheat Sheet" /><published>2025-07-30T00:00:00+00:00</published><updated>2025-07-30T00:00:00+00:00</updated><id>https://blakebyer.github.io//blog/2025/07/30/mathnotation</id><content type="html" xml:base="https://blakebyer.github.io//blog/2025/07/30/mathnotation.html"><![CDATA[<h1 id="math-notation-cheat-sheet">Math Notation Cheat Sheet</h1>
+<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="4.4.1">Jekyll</generator><link href="https://blakebyer.github.io//feed.xml" rel="self" type="application/atom+xml" /><link href="https://blakebyer.github.io//" rel="alternate" type="text/html" /><updated>2025-07-31T00:10:37+00:00</updated><id>https://blakebyer.github.io//feed.xml</id><title type="html">Blake Byer</title><subtitle>This is the personal webpage of Blake Byer.</subtitle><author><name>Blake Byer</name><email>bbyer04@gmail.com</email></author><entry><title type="html">Math Symbols Cheat Sheet</title><link href="https://blakebyer.github.io//blog/2025/07/30/mathnotation.html" rel="alternate" type="text/html" title="Math Symbols Cheat Sheet" /><published>2025-07-30T00:00:00+00:00</published><updated>2025-07-30T00:00:00+00:00</updated><id>https://blakebyer.github.io//blog/2025/07/30/mathnotation</id><content type="html" xml:base="https://blakebyer.github.io//blog/2025/07/30/mathnotation.html"><![CDATA[<h1 id="math-notation-cheat-sheet">Math Notation Cheat Sheet</h1>
 
 <h2 id="arithmetic">Arithmetic</h2>
 
@@ -516,7 +516,7 @@
 <hr />
 
 <p><em>By Dominic Walliman (2018)</em></p>]]></content><author><name>Blake Byer</name><email>bbyer04@gmail.com</email></author><category term="blog" /><summary type="html"><![CDATA[A math symbols cheat sheet]]></summary></entry><entry><title type="html">Introduction to Statistics for Biologists</title><link href="https://blakebyer.github.io//blog/2025/07/30/statsintro.html" rel="alternate" type="text/html" title="Introduction to Statistics for Biologists" /><published>2025-07-30T00:00:00+00:00</published><updated>2025-07-30T00:00:00+00:00</updated><id>https://blakebyer.github.io//blog/2025/07/30/statsintro</id><content type="html" xml:base="https://blakebyer.github.io//blog/2025/07/30/statsintro.html"><![CDATA[<h2 id="why-learn-statistics">Why learn statistics?</h2>
-<p>Statistics are the backbone of impactful, reproducible research. Properly done, statistics provide us with basis for cause and effect (known as causal inference). I wanted to write a few supplementary articles for myself and others to understand the basics of probability, statistics, and linear algebra to boost their research. If you get stuck on the notation, please check the <a href="/blog/2025/07/30/mathnotation.html">Math Notation Sheet</a>. First, an inspiring image from our friends in biostatistics, a sub-field of statistics devoted to creating and applying statistical methods to biological or medical data.</p>
+<p>Statistics is the backbone of impactful, reproducible research. Properly done, statistics provide us with basis for cause and effect (known as causal inference). I wanted to write a few supplementary articles for myself and others to understand the basics of probability, statistics, and linear algebra to boost their research. If you get stuck on the notation, please check the <a href="/blog/2025/07/30/mathnotation.html">Math Notation Sheet</a>. First, an inspiring image from our friends in biostatistics, a sub-field of statistics devoted to creating and applying statistical methods to biological data.</p>
 
 <figure>
   <img src="/assets/images/ebpi_research_dep_biostatistics_2480x1529px.png" alt="Biostatistics" />