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diff --git a/docs/probability_2/probability_2.html b/docs/probability_2/probability_2.html
@@ -541,7 +541,7 @@ <h2 data-number="18.3" class="anchored" data-anchor-id="prediction-and-inference
 <p align="center">
 <img src="images/bias_v_variance.png" width="600">
 </p>
-<p>Ideally, we want our estimator to have low bias and low variance, but how can we mathematically quantify that? See <a href="#sec-bias-variance-tradeoff"><span>Section&nbsp;18.4</span></a> for more detail.</p>
+<p>Ideally, we want our estimator to have low bias and low variance, but how can we mathematically quantify that? See <a href="#sec-bias-variance-tradeoff"><span class="quarto-unresolved-ref">sec-bias-variance-tradeoff</span></a> for more detail.</p>
 <section id="prediction-as-estimation" class="level3" data-number="18.3.1">
 <h3 data-number="18.3.1" class="anchored" data-anchor-id="prediction-as-estimation"><span class="header-section-number">18.3.1</span> Prediction as Estimation</h3>
 <p>Now that we’ve established the idea of an estimator, let’s see how we can apply this learning to the modeling process. To do so, we’ll take a moment to formalize our data collection and models in the language of random variables.</p>

diff --git a/docs/sql_I/sql_I.html b/docs/sql_I/sql_I.html
diff --git a/docs/sql_II/sql_II.html b/docs/sql_II/sql_II.html
diff --git a/index.log b/index.log
@@ -1,4 +1,4 @@
-This is XeTeX, Version 3.141592653-2.6-0.999995 (TeX Live 2023) (preloaded format=xelatex 2024.3.3)  4 APR 2024 15:03
+This is XeTeX, Version 3.141592653-2.6-0.999995 (TeX Live 2023) (preloaded format=xelatex 2024.3.3)  5 APR 2024 13:24
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diff --git a/index.pdf b/index.pdf
diff --git a/index.tex b/index.tex
diff --git a/sql_I/sql_I.qmd b/sql_I/sql_I.qmd
@@ -56,7 +56,7 @@ It is important to reiterate that SQL is an entirely different language from Pyt
 
 The syntax below will seem unfamiliar to you; for now, just focus on understanding the output displayed. We will clarify the SQL code in a bit.
 
-To start, we'll look at a database called `example_duck.db` and connect to it using SQLite.
+To start, we'll look at a database called `example_duck.db` and connect to it using DuckDB.
 
 ```{python}
 #| code-fold: true