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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Mammal Data Correlations</title>
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
<script src="https://cdn.jsdelivr.net/npm/regression"></script>
<style>
body {
font-family: Arial, sans-serif;
margin: 20px;
background-color: #f9f9f9;
}
.chartContainer {
width: 80%;
margin: 20px auto;
background-color: white;
padding: 20px;
border-radius: 10px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
}
.accuracy {
text-align: center;
margin-top: 20px;
}
table {
width: 80%;
margin: 20px auto;
border-collapse: collapse;
background-color: white;
border-radius: 10px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
}
table, th, td {
border: 1px solid black;
}
th, td {
padding: 8px;
text-align: center;
}
.background {
width: 80%;
margin: 20px auto;
padding: 20px;
background-color: white;
border-radius: 10px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
}
.attribution {
text-align: center;
margin-top: 20px;
font-style: italic;
color: #555;
}
</style>
</head>
<body>
<h1>Mammal Data Correlations</h1>
<!-- Background Section -->
<div class="background">
<h2>Background</h2>
<p>
This project investigates the relationship between gestation periods and various biological traits in mammals.
The central question is: <strong>How does the time for gestation correlate with brain size, baby size, and baby volume?</strong>
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.
</p>
</div>
<!-- Chart 1: Gestation vs. Brain Size -->
<div class="chartContainer">
<h2>Gestation Period vs. Brain Size</h2>
<canvas id="chart1"></canvas>
<div class="accuracy">
<p>Best Fit: <span id="bestFit1"></span> (R²: <span id="bestFitAccuracy1"></span>)</p>
<p>Equation: <span id="equation1"></span></p>
<p>Other Models:</p>
<ul>
<li>Linear: R² = <span id="linearAccuracy1"></span></li>
<li>Exponential: R² = <span id="expAccuracy1"></span></li>
<li>Quadratic: R² = <span id="quadAccuracy1"></span></li>
</ul>
</div>
</div>
<!-- Chart 2: Gestation vs. Baby Size -->
<div class="chartContainer">
<h2>Gestation Period vs. Baby Size</h2>
<canvas id="chart2"></canvas>
<div class="accuracy">
<p>Best Fit: <span id="bestFit2"></span> (R²: <span id="bestFitAccuracy2"></span>)</p>
<p>Equation: <span id="equation2"></span></p>
<p>Other Models:</p>
<ul>
<li>Linear: R² = <span id="linearAccuracy2"></span></li>
<li>Exponential: R² = <span id="expAccuracy2"></span></li>
<li>Quadratic: R² = <span id="quadAccuracy2"></span></li>
</ul>
</div>
</div>
<!-- Chart 3: Gestation vs. Baby Volume -->
<div class="chartContainer">
<h2>Gestation Period vs. Baby Volume</h2>
<canvas id="chart3"></canvas>
<div class="accuracy">
<p>Best Fit: <span id="bestFit3"></span> (R²: <span id="bestFitAccuracy3"></span>)</p>
<p>Equation: <span id="equation3"></span></p>
<p>Other Models:</p>
<ul>
<li>Linear: R² = <span id="linearAccuracy3"></span></li>
<li>Exponential: R² = <span id="expAccuracy3"></span></li>
<li>Quadratic: R² = <span id="quadAccuracy3"></span></li>
</ul>
</div>
</div>
<!-- Chart 4: Gestation vs. Brain-to-Baby Size Ratio -->
<div class="chartContainer">
<h2>Gestation Period vs. Brain-to-Baby Size Ratio</h2>
<canvas id="chart4"></canvas>
<div class="accuracy">
<p>Best Fit: <span id="bestFit4"></span> (R²: <span id="bestFitAccuracy4"></span>)</p>
<p>Equation: <span id="equation4"></span></p>
<p>Other Models:</p>
<ul>
<li>Linear: R² = <span id="linearAccuracy4"></span></li>
<li>Exponential: R² = <span id="expAccuracy4"></span></li>
<li>Quadratic: R² = <span id="quadAccuracy4"></span></li>
</ul>
</div>
</div>
<!-- Table -->
<table>
<thead>
<tr>
<th>Mammal</th>
<th>Gestation (Days)</th>
<th>Brain Size (grams)</th>
<th>Baby Size (kg)</th>
<th>Baby Volume (liters)</th>
</tr>
</thead>
<tbody>
<tr>
<td>African Elephant</td>
<td>655</td>
<td>2300</td>
<td>120</td>
<td>90</td>
</tr>
<tr>
<td>Asian Elephant</td>
<td>617</td>
<td>2000</td>
<td>100</td>
<td>80</td>
</tr>
<tr>
<td>Sperm Whale</td>
<td>535</td>
<td>7800</td>
<td>1000</td>
<td>1000</td>
</tr>
<tr>
<td>Orca</td>
<td>532</td>
<td>3500</td>
<td>180</td>
<td>180</td>
</tr>
<tr>
<td>Indian Rhinoceros</td>
<td>478</td>
<td>400</td>
<td>60</td>
<td>60</td>
</tr>
<tr>
<td>White Rhinoceros</td>
<td>467</td>
<td>350</td>
<td>50</td>
<td>50</td>
</tr>
<tr>
<td>Giraffe</td>
<td>430</td>
<td>500</td>
<td>100</td>
<td>100</td>
</tr>
<tr>
<td>Bactrian Camel</td>
<td>390</td>
<td>300</td>
<td>35</td>
<td>35</td>
</tr>
<tr>
<td>Bottlenose Dolphin</td>
<td>364</td>
<td>750</td>
<td>15</td>
<td>15</td>
</tr>
<tr>
<td>Horse</td>
<td>336</td>
<td>400</td>
<td>50</td>
<td>50</td>
</tr>
<tr>
<td>Human</td>
<td>270</td>
<td>350</td>
<td>3.5</td>
<td>3.5</td>
</tr>
<tr>
<td>Gorilla</td>
<td>257</td>
<td>200</td>
<td>2</td>
<td>2</td>
</tr>
<tr>
<td>Chimpanzee</td>
<td>240</td>
<td>150</td>
<td>1.8</td>
<td>1.8</td>
</tr>
<tr>
<td>Polar Bear</td>
<td>241</td>
<td>25</td>
<td>0.6</td>
<td>0.6</td>
</tr>
<tr>
<td>Domestic Cat</td>
<td>64</td>
<td>5</td>
<td>0.1</td>
<td>0.1</td>
</tr>
<tr>
<td>Domestic Dog</td>
<td>61</td>
<td>10</td>
<td>0.3</td>
<td>0.3</td>
</tr>
<tr>
<td>Mouse</td>
<td>19</td>
<td>0.1</td>
<td>0.001</td>
<td>0.001</td>
</tr>
<tr>
<td>Rat</td>
<td>22</td>
<td>0.2</td>
<td>0.005</td>
<td>0.005</td>
</tr>
<tr>
<td>Virginia Opossum</td>
<td>12</td>
<td>0.05</td>
<td>0.002</td>
<td>0.002</td>
</tr>
<tr>
<td>Kangaroo</td>
<td>42</td>
<td>5</td>
<td>0.8</td>
<td>0.8</td>
</tr>
</tbody>
</table>
<!-- Attribution -->
<div class="attribution">
<p>Made by Julian Herrera for 2025 Bio Class - Jan 14</p>
</div>
<script>
// Data from the table
const data = {
mammals: [
"African Elephant", "Asian Elephant", "Sperm Whale", "Orca", "Indian Rhinoceros",
"White Rhinoceros", "Giraffe", "Bactrian Camel", "Bottlenose Dolphin", "Horse",
"Human", "Gorilla", "Chimpanzee", "Polar Bear", "Domestic Cat", "Domestic Dog",
"Mouse", "Rat", "Virginia Opossum", "Kangaroo"
],
gestation: [
655, 617, 535, 532, 478, 467, 430, 390, 364, 336, 270, 257, 240, 241, 64, 61, 19, 22, 12, 42
],
brainSize: [
2300, 2000, 7800, 3500, 400, 350, 500, 300, 750, 400, 350, 200, 150, 25, 5, 10, 0.1, 0.2, 0.05, 5
],
babySize: [
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
],
babyVolume: [
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
]
};
// Function to remove outliers using IQR
function removeOutliers(xData, yData) {
const combinedData = xData.map((x, i) => ({ x, y: yData[i] }));
// Calculate quartiles and IQR for yData
const sortedY = yData.slice().sort((a, b) => a - b);
const Q1 = sortedY[Math.floor(sortedY.length * 0.25)];
const Q3 = sortedY[Math.floor(sortedY.length * 0.75)];
const IQR = Q3 - Q1;
const lowerBound = Q1 - 1.5 * IQR;
const upperBound = Q3 + 1.5 * IQR;
// Filter out outliers
const filteredData = combinedData.filter(point => point.y >= lowerBound && point.y <= upperBound);
// Separate x and y data
const filteredX = filteredData.map(point => point.x);
const filteredY = filteredData.map(point => point.y);
return { filteredX, filteredY };
}
// Function to format the equation
function formatEquation(type, coefficients) {
if (type === 'Linear') {
return `y = ${coefficients[0].toFixed(2)}x + ${coefficients[1].toFixed(2)}`;
} else if (type === 'Exponential') {
return `y = ${coefficients[0].toFixed(2)}e^(${coefficients[1].toFixed(2)}x)`;
} else if (type === 'Quadratic') {
return `y = ${coefficients[0].toFixed(2)}x² + ${coefficients[1].toFixed(2)}x + ${coefficients[2].toFixed(2)}`;
}
return '';
}
// Function to create a chart with best-fit regression
function createChart(canvasId, xData, yData, xLabel, yLabel, bestFitId, bestFitAccuracyId, equationId, linearAccuracyId, expAccuracyId, quadAccuracyId) {
// Remove outliers
const { filteredX, filteredY } = removeOutliers(xData, yData);
const chartData = filteredX.map((x, index) => ({ x, y: filteredY[index] }));
// Perform regressions
const linear = regression.linear(chartData.map(point => [point.x, point.y]));
const exp = regression.exponential(chartData.map(point => [point.x, point.y]));
const quad = regression.polynomial(chartData.map(point => [point.x, point.y]), { order: 2 });
// Determine the best fit (highest R²)
const regressions = [
{ type: 'Linear', r2: linear.r2, points: linear, coefficients: [linear.equation[1], linear.equation[0]] },
{ type: 'Exponential', r2: exp.r2, points: exp, coefficients: [exp.equation[0], exp.equation[1]] },
{ type: 'Quadratic', r2: quad.r2, points: quad, coefficients: [quad.equation[2], quad.equation[1], quad.equation[0]] }
];
const bestFit = regressions.reduce((best, current) => (current.r2 > best.r2 ? current : best));
// Generate points for the best-fit regression
const bestFitPoints = chartData.map(point => ({
x: point.x,
y: bestFit.points.predict(point.x)[1]
}));
// Render the chart
const ctx = document.getElementById(canvasId).getContext('2d');
const chart = new Chart(ctx, {
type: 'scatter',
data: {
datasets: [
{
label: 'Data Points',
data: chartData,
backgroundColor: 'rgba(75, 192, 192, 0.6)',
borderColor: 'rgba(75, 192, 192, 1)',
pointRadius: 5
},
{
label: `${bestFit.type} Regression`,
data: bestFitPoints,
backgroundColor: 'rgba(255, 99, 132, 0)',
borderColor: 'rgba(255, 99, 132, 1)',
type: 'line',
pointRadius: 0
}
]
},
options: {
scales: {
x: {
type: 'linear',
position: 'bottom',
title: {
display: true,
text: xLabel
}
},
y: {
type: 'linear',
title: {
display: true,
text: yLabel
}
}
}
}
});
// Display best fit, accuracy, and equation
document.getElementById(bestFitId).textContent = bestFit.type;
document.getElementById(bestFitAccuracyId).textContent = bestFit.r2.toFixed(4);
document.getElementById(equationId).textContent = formatEquation(bestFit.type, bestFit.coefficients);
// Display accuracy for all models
document.getElementById(linearAccuracyId).textContent = linear.r2.toFixed(4);
document.getElementById(expAccuracyId).textContent = exp.r2.toFixed(4);
document.getElementById(quadAccuracyId).textContent = quad.r2.toFixed(4);
}
// Create charts
createChart('chart1', data.gestation, data.brainSize, 'Gestation Period (Days)', 'Brain Size (grams)', 'bestFit1', 'bestFitAccuracy1', 'equation1', 'linearAccuracy1', 'expAccuracy1', 'quadAccuracy1');
createChart('chart2', data.gestation, data.babySize, 'Gestation Period (Days)', 'Baby Size (kg)', 'bestFit2', 'bestFitAccuracy2', 'equation2', 'linearAccuracy2', 'expAccuracy2', 'quadAccuracy2');
createChart('chart3', data.gestation, data.babyVolume, 'Gestation Period (Days)', 'Baby Volume (liters)', 'bestFit3', 'bestFitAccuracy3', 'equation3', 'linearAccuracy3', 'expAccuracy3', 'quadAccuracy3');
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');
</script>
</body>
</html>