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outliers.html
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<!DOCTYPE html>
<html lang="en">
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<title>Beyond the Regression Line: Centering Outliers in Galton’s Data</title>
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<header>
<h1>Beyond the Regression Line: Centering Outliers in Galton’s Data</h1>
</header>
<div class="content-wrapper">
<!-- Outliers Description Section -->
<section id="outliers-description">
<p>
Francis Galton’s pioneering work in regression and correlation was designed to reveal relationships within data, yet it also imposed a framework where difference became deviation—and deviation became deficiency.
</p>
<p>
The visualization below, <em>Francis Galton’s Fingerprints on Data Visualization</em>, challenges that legacy. Using Galton’s original height data, individual data points are transformed into fingerprint-like patterns, with outliers vividly marked and placed back into their family groups. These red fingerprints are more than statistical anomalies—they are families, individuals, and lives that Galton’s models could not fully capture.
</p>
<!-- Tableau Visualization Section -->
<div class="tableau-container">
<div class="tableauPlaceholder" id="viz16708869202060">
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<h2>Engage with Family #72</h2>
<p>
In the visualization above, notice Family #72, the third set of <span style="color: red;">fingerprints</span> from the bottom. Their data points drift far from Galton’s expected regression line.
</p>
<p>
Engage with the data: analyze their patterns, and question why this family doesn’t conform. Is it genetics, environment, or something data alone cannot explain?
</p>
<p>
From a purely statistical perspective, we can estimate how likely it is for a family to produce an outlier in height.
Consider the parents in Family #72:
<ul>
<li>Father: 5′8″ (68 inches)</li>
<li>Mother: 5′4″ (64 inches)</li>
</ul>
The son’s predicted height is calculated as:
<br><br>
Mid-parent height = ((68 + 64) + 5) ÷ 2 = 68.5 inches (about 5′8.5″)
</p>
<p>
Now, suppose their son grows to be 6′5.8″ (77.8 inches). This is 9.3 inches taller than the family’s average. Using a standard deviation of 2.7 inches:
<br><br>
Z-score = 9.3 ÷ 2.7 ≈ 3.44
</p>
<p>
A Z-score of 3.44 places this child in the top ~0.03% of the population—a statistical rarity occurring in roughly 1 out of 3,000 cases.
On paper, Family #72’s deviation seems improbable, but reality is rarely that simple.
</p>
<h2>But What If It’s Something More?</h2>
<p>
Statistics offer explanations, but they cannot capture the full complexity of human life. What if Family #72 isn’t simply a statistical anomaly, but a story of resilience, genetic variation, or environmental adaptation?
</p>
<p>
Galton’s models reduced people to data points, erasing individuality in favor of trends. Yet the red fingerprints of Family #72 push back. They remind us that data can hint at human stories—but never fully contain them.
</p>
<p>
Perhaps this family reflects something more beautifully messy—something closer to the unpredictable, vibrant nature of life itself.
</p>
<p>
Continue reading: <a href="family-72.html" style="text-decoration: none; color: purple;">Family #72 - A Fictional Data Analysis</a>.
</p>
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