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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Mammal Data Correlations</title>
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<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/regression"></script>
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<style>
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body {
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font-family: Arial, sans-serif;
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margin: 20px;
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background-color: #f9f9f9;
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}
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.chartContainer {
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width: 80%;
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margin: 20px auto;
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background-color: white;
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padding: 20px;
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border-radius: 10px;
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box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
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}
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.accuracy {
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text-align: center;
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margin-top: 20px;
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}
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table {
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width: 80%;
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margin: 20px auto;
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border-collapse: collapse;
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background-color: white;
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border-radius: 10px;
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box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
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}
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table, th, td {
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border: 1px solid black;
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}
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th, td {
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padding: 8px;
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text-align: center;
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}
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.background {
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width: 80%;
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margin: 20px auto;
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padding: 20px;
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background-color: white;
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border-radius: 10px;
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box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
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}
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.attribution {
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text-align: center;
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margin-top: 20px;
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font-style: italic;
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color: #555;
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}
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</style>
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</head>
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<body>
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<h1>Mammal Data Correlations</h1>
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<!-- Background Section -->
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<div class="background">
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<h2>Background</h2>
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<p>
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This project investigates the relationship between gestation periods and various biological traits in mammals.
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The central question is: <strong>How does the time for gestation correlate with brain size, baby size, and baby volume?</strong>
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By analyzing data from a variety of mammals, we aim to uncover patterns and trends that can help us understand the evolutionary and biological significance of gestation periods.
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</p>
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</div>
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<!-- Chart 1: Gestation vs. Brain Size -->
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<div class="chartContainer">
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<h2>Gestation Period vs. Brain Size</h2>
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<canvas id="chart1"></canvas>
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<div class="accuracy">
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<p>Best Fit: <span id="bestFit1"></span> (R²: <span id="bestFitAccuracy1"></span>)</p>
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<p>Equation: <span id="equation1"></span></p>
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<p>Other Models:</p>
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<ul>
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<li>Linear: R² = <span id="linearAccuracy1"></span></li>
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<li>Exponential: R² = <span id="expAccuracy1"></span></li>
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<li>Quadratic: R² = <span id="quadAccuracy1"></span></li>
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</ul>
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</div>
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</div>
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<!-- Chart 2: Gestation vs. Baby Size -->
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<div class="chartContainer">
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<h2>Gestation Period vs. Baby Size</h2>
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<canvas id="chart2"></canvas>
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<div class="accuracy">
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<p>Best Fit: <span id="bestFit2"></span> (R²: <span id="bestFitAccuracy2"></span>)</p>
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<p>Equation: <span id="equation2"></span></p>
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<p>Other Models:</p>
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<ul>
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<li>Linear: R² = <span id="linearAccuracy2"></span></li>
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<li>Exponential: R² = <span id="expAccuracy2"></span></li>
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<li>Quadratic: R² = <span id="quadAccuracy2"></span></li>
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</ul>
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</div>
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</div>
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<!-- Chart 3: Gestation vs. Baby Volume -->
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<div class="chartContainer">
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<h2>Gestation Period vs. Baby Volume</h2>
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<canvas id="chart3"></canvas>
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<div class="accuracy">
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<p>Best Fit: <span id="bestFit3"></span> (R²: <span id="bestFitAccuracy3"></span>)</p>
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<p>Equation: <span id="equation3"></span></p>
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<p>Other Models:</p>
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<ul>
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<li>Linear: R² = <span id="linearAccuracy3"></span></li>
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<li>Exponential: R² = <span id="expAccuracy3"></span></li>
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<li>Quadratic: R² = <span id="quadAccuracy3"></span></li>
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</ul>
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</div>
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</div>
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<!-- Chart 4: Gestation vs. Brain-to-Baby Size Ratio -->
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<div class="chartContainer">
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<h2>Gestation Period vs. Brain-to-Baby Size Ratio</h2>
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<canvas id="chart4"></canvas>
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<div class="accuracy">
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<p>Best Fit: <span id="bestFit4"></span> (R²: <span id="bestFitAccuracy4"></span>)</p>
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<p>Equation: <span id="equation4"></span></p>
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<p>Other Models:</p>
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<ul>
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<li>Linear: R² = <span id="linearAccuracy4"></span></li>
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<li>Exponential: R² = <span id="expAccuracy4"></span></li>
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<li>Quadratic: R² = <span id="quadAccuracy4"></span></li>
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</ul>
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</div>
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</div>
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<!-- Table -->
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<table>
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<thead>
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<tr>
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<th>Mammal</th>
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<th>Gestation (Days)</th>
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<th>Brain Size (grams)</th>
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<th>Baby Size (kg)</th>
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<th>Baby Volume (liters)</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td>African Elephant</td>
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<td>655</td>
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<td>2300</td>
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<td>120</td>
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<td>90</td>
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</tr>
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<tr>
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<td>Asian Elephant</td>
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<td>617</td>
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<td>2000</td>
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<td>100</td>
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<td>80</td>
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</tr>
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<tr>
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<td>Sperm Whale</td>
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<td>535</td>
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<td>7800</td>
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<td>1000</td>
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<td>1000</td>
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</tr>
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<tr>
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<td>Orca</td>
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<td>532</td>
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<td>3500</td>
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<td>180</td>
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<td>180</td>
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</tr>
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<tr>
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<td>Indian Rhinoceros</td>
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<td>478</td>
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<td>400</td>
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<td>60</td>
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<td>60</td>
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</tr>
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<tr>
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<td>White Rhinoceros</td>
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<td>467</td>
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<td>350</td>
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<td>50</td>
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<td>50</td>
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</tr>
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<tr>
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<td>Giraffe</td>
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<td>430</td>
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<td>500</td>
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<td>100</td>
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<td>100</td>
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</tr>
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<tr>
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<td>Bactrian Camel</td>
|
198 |
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<td>390</td>
|
199 |
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<td>300</td>
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<td>35</td>
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<td>35</td>
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</tr>
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<tr>
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<td>Bottlenose Dolphin</td>
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<td>364</td>
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<td>750</td>
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<td>15</td>
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<td>15</td>
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</tr>
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<tr>
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<td>Horse</td>
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<td>336</td>
|
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<td>400</td>
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<td>50</td>
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<td>50</td>
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</tr>
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<tr>
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<td>Human</td>
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<td>270</td>
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<td>350</td>
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<td>3.5</td>
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<td>3.5</td>
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</tr>
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<tr>
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<td>Gorilla</td>
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226 |
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<td>257</td>
|
227 |
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<td>200</td>
|
228 |
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<td>2</td>
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<td>2</td>
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</tr>
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<tr>
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<td>Chimpanzee</td>
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<td>240</td>
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<td>150</td>
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<td>1.8</td>
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<td>1.8</td>
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</tr>
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<tr>
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<td>Polar Bear</td>
|
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<td>241</td>
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<td>25</td>
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<td>0.6</td>
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<td>0.6</td>
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</tr>
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<tr>
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<td>Domestic Cat</td>
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<td>64</td>
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<td>5</td>
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<td>0.1</td>
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<td>0.1</td>
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</tr>
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<tr>
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<td>Domestic Dog</td>
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254 |
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<td>61</td>
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<td>10</td>
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<td>0.3</td>
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<td>0.3</td>
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</tr>
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<tr>
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<td>Mouse</td>
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<td>19</td>
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<td>0.1</td>
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<td>0.001</td>
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<td>0.001</td>
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</tr>
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<tr>
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<td>Rat</td>
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<td>22</td>
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<td>0.2</td>
|
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<td>0.005</td>
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<td>0.005</td>
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</tr>
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<tr>
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<td>Virginia Opossum</td>
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<td>12</td>
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<td>0.05</td>
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<td>0.002</td>
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<td>0.002</td>
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</tr>
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<tr>
|
281 |
+
<td>Kangaroo</td>
|
282 |
+
<td>42</td>
|
283 |
+
<td>5</td>
|
284 |
+
<td>0.8</td>
|
285 |
+
<td>0.8</td>
|
286 |
+
</tr>
|
287 |
+
</tbody>
|
288 |
+
</table>
|
289 |
+
|
290 |
+
<!-- Attribution -->
|
291 |
+
<div class="attribution">
|
292 |
+
<p>Made by Julian Herrera for 2025 Bio Class - Jan 14</p>
|
293 |
+
</div>
|
294 |
+
|
295 |
+
<script>
|
296 |
+
// Data from the table
|
297 |
+
const data = {
|
298 |
+
mammals: [
|
299 |
+
"African Elephant", "Asian Elephant", "Sperm Whale", "Orca", "Indian Rhinoceros",
|
300 |
+
"White Rhinoceros", "Giraffe", "Bactrian Camel", "Bottlenose Dolphin", "Horse",
|
301 |
+
"Human", "Gorilla", "Chimpanzee", "Polar Bear", "Domestic Cat", "Domestic Dog",
|
302 |
+
"Mouse", "Rat", "Virginia Opossum", "Kangaroo"
|
303 |
+
],
|
304 |
+
gestation: [
|
305 |
+
655, 617, 535, 532, 478, 467, 430, 390, 364, 336, 270, 257, 240, 241, 64, 61, 19, 22, 12, 42
|
306 |
+
],
|
307 |
+
brainSize: [
|
308 |
+
2300, 2000, 7800, 3500, 400, 350, 500, 300, 750, 400, 350, 200, 150, 25, 5, 10, 0.1, 0.2, 0.05, 5
|
309 |
+
],
|
310 |
+
babySize: [
|
311 |
+
120, 100, 1000, 180, 60, 50, 100, 35, 15, 50, 3.5, 2, 1.8, 0.6, 0.1, 0.3, 0.001, 0.005, 0.002, 0.8
|
312 |
+
],
|
313 |
+
babyVolume: [
|
314 |
+
90, 80, 1000, 180, 60, 50, 100, 35, 15, 50, 3.5, 2, 1.8, 0.6, 0.1, 0.3, 0.001, 0.005, 0.002, 0.8
|
315 |
+
]
|
316 |
+
};
|
317 |
+
|
318 |
+
// Function to format the equation
|
319 |
+
function formatEquation(type, coefficients) {
|
320 |
+
if (type === 'Linear') {
|
321 |
+
return `y = ${coefficients[0].toFixed(2)}x + ${coefficients[1].toFixed(2)}`;
|
322 |
+
} else if (type === 'Exponential') {
|
323 |
+
return `y = ${coefficients[0].toFixed(2)}e^(${coefficients[1].toFixed(2)}x)`;
|
324 |
+
} else if (type === 'Quadratic') {
|
325 |
+
return `y = ${coefficients[0].toFixed(2)}x² + ${coefficients[1].toFixed(2)}x + ${coefficients[2].toFixed(2)}`;
|
326 |
+
}
|
327 |
+
return '';
|
328 |
+
}
|
329 |
+
|
330 |
+
// Function to create a chart with best-fit regression
|
331 |
+
function createChart(canvasId, xData, yData, xLabel, yLabel, bestFitId, bestFitAccuracyId, equationId, linearAccuracyId, expAccuracyId, quadAccuracyId) {
|
332 |
+
const chartData = xData.map((x, index) => ({ x: x, y: yData[index] }));
|
333 |
+
|
334 |
+
// Perform regressions
|
335 |
+
const linear = regression.linear(chartData.map(point => [point.x, point.y]));
|
336 |
+
const exp = regression.exponential(chartData.map(point => [point.x, point.y]));
|
337 |
+
const quad = regression.polynomial(chartData.map(point => [point.x, point.y]), { order: 2 });
|
338 |
+
|
339 |
+
// Determine the best fit (highest R²)
|
340 |
+
const regressions = [
|
341 |
+
{ type: 'Linear', r2: linear.r2, points: linear, coefficients: [linear.equation[1], linear.equation[0]] },
|
342 |
+
{ type: 'Exponential', r2: exp.r2, points: exp, coefficients: [exp.equation[0], exp.equation[1]] },
|
343 |
+
{ type: 'Quadratic', r2: quad.r2, points: quad, coefficients: [quad.equation[2], quad.equation[1], quad.equation[0]] }
|
344 |
+
];
|
345 |
+
const bestFit = regressions.reduce((best, current) => (current.r2 > best.r2 ? current : best));
|
346 |
+
|
347 |
+
// Generate points for the best-fit regression
|
348 |
+
const bestFitPoints = chartData.map(point => ({
|
349 |
+
x: point.x,
|
350 |
+
y: bestFit.points.predict(point.x)[1]
|
351 |
+
}));
|
352 |
+
|
353 |
+
// Render the chart
|
354 |
+
const ctx = document.getElementById(canvasId).getContext('2d');
|
355 |
+
const chart = new Chart(ctx, {
|
356 |
+
type: 'scatter',
|
357 |
+
data: {
|
358 |
+
datasets: [
|
359 |
+
{
|
360 |
+
label: 'Data Points',
|
361 |
+
data: chartData,
|
362 |
+
backgroundColor: 'rgba(75, 192, 192, 0.6)',
|
363 |
+
borderColor: 'rgba(75, 192, 192, 1)',
|
364 |
+
pointRadius: 5
|
365 |
+
},
|
366 |
+
{
|
367 |
+
label: `${bestFit.type} Regression`,
|
368 |
+
data: bestFitPoints,
|
369 |
+
backgroundColor: 'rgba(255, 99, 132, 0)',
|
370 |
+
borderColor: 'rgba(255, 99, 132, 1)',
|
371 |
+
type: 'line',
|
372 |
+
pointRadius: 0
|
373 |
+
}
|
374 |
+
]
|
375 |
+
},
|
376 |
+
options: {
|
377 |
+
scales: {
|
378 |
+
x: {
|
379 |
+
type: 'linear',
|
380 |
+
position: 'bottom',
|
381 |
+
title: {
|
382 |
+
display: true,
|
383 |
+
text: xLabel
|
384 |
+
}
|
385 |
+
},
|
386 |
+
y: {
|
387 |
+
type: 'linear',
|
388 |
+
title: {
|
389 |
+
display: true,
|
390 |
+
text: yLabel
|
391 |
+
}
|
392 |
+
}
|
393 |
+
}
|
394 |
+
}
|
395 |
+
});
|
396 |
+
|
397 |
+
// Display best fit, accuracy, and equation
|
398 |
+
document.getElementById(bestFitId).textContent = bestFit.type;
|
399 |
+
document.getElementById(bestFitAccuracyId).textContent = bestFit.r2.toFixed(4);
|
400 |
+
document.getElementById(equationId).textContent = formatEquation(bestFit.type, bestFit.coefficients);
|
401 |
+
|
402 |
+
// Display accuracy for all models
|
403 |
+
document.getElementById(linearAccuracyId).textContent = linear.r2.toFixed(4);
|
404 |
+
document.getElementById(expAccuracyId).textContent = exp.r2.toFixed(4);
|
405 |
+
document.getElementById(quadAccuracyId).textContent = quad.r2.toFixed(4);
|
406 |
+
}
|
407 |
+
|
408 |
+
// Create charts
|
409 |
+
createChart('chart1', data.gestation, data.brainSize, 'Gestation Period (Days)', 'Brain Size (grams)', 'bestFit1', 'bestFitAccuracy1', 'equation1', 'linearAccuracy1', 'expAccuracy1', 'quadAccuracy1');
|
410 |
+
createChart('chart2', data.gestation, data.babySize, 'Gestation Period (Days)', 'Baby Size (kg)', 'bestFit2', 'bestFitAccuracy2', 'equation2', 'linearAccuracy2', 'expAccuracy2', 'quadAccuracy2');
|
411 |
+
createChart('chart3', data.gestation, data.babyVolume, 'Gestation Period (Days)', 'Baby Volume (liters)', 'bestFit3', 'bestFitAccuracy3', 'equation3', 'linearAccuracy3', 'expAccuracy3', 'quadAccuracy3');
|
412 |
+
createChart('chart4', data.gestation, data.brainSize.map((brain, i) => brain / data.babySize[i]), 'Gestation Period (Days)', 'Brain-to-Baby Size Ratio', 'bestFit4', 'bestFitAccuracy4', 'equation4', 'linearAccuracy4', 'expAccuracy4', 'quadAccuracy4');
|
413 |
+
</script>
|
414 |
+
</body>
|
415 |
+
</html>
|