mirror of
https://github.com/freeCodeCamp/freeCodeCamp.git
synced 2025-12-22 03:26:02 -05:00
3c1353fbe0
Co-authored-by: Naomi <nhcarrigan@gmail.com> Co-authored-by: Sem Bauke <semboot699@gmail.com>
5.9 KiB
5.9 KiB
id, title, challengeType, dashedName
| id | title | challengeType | dashedName |
|---|---|---|---|
| 6352fe473d53592a40ae403b | Step 50 | 0 | step-50 |
--description--
Within your empty .reduce() callback, declare a variable difference and set it to the value of el minus mean. Then declare a squared variable, and set it to the value of difference to the power of 2. Finally, return the value of acc plus squared.
--hints--
Your reduce callback should have a difference variable.
assert.match(getVariance.toString(), /variance\s*=\s*array\.reduce\(\s*function\s*\(\s*acc\s*,\s*el\s*\)\s*\{\s*var\s+difference\s*=/);
Your difference variable should be set to the value of el minus mean.
assert.match(getVariance.toString(), /variance\s*=\s*array\.reduce\(\s*function\s*\(\s*acc\s*,\s*el\s*\)\s*\{\s*var\s+difference\s*=\s*el\s*-\s*mean\s*;/);
Your reduce callback should have a squared variable.
assert.match(getVariance.toString(), /variance\s*=\s*array\.reduce\(\s*function\s*\(\s*acc\s*,\s*el\s*\)\s*\{\s*var\s+difference\s*=\s*el\s*-\s*mean\s*;\s*var\s+squared\s*=/);
Your squared variable should be set to the value of difference to the power of 2.
assert.match(getVariance.toString(), /variance\s*=\s*array\.reduce\(\s*function\s*\(\s*acc\s*,\s*el\s*\)\s*\{\s*var\s+difference\s*=\s*el\s*-\s*mean\s*;\s*var\s+squared\s*=\s*Math\.pow\(\s*difference\s*,\s*2\s*\)\s*;?/);
Your reduce callback should return the value of acc plus squared.
assert.match(getVariance.toString(), /variance\s*=\s*array\.reduce\(\s*function\s*\(\s*acc\s*,\s*el\s*\)\s*\{\s*var\s+difference\s*=\s*el\s*-\s*mean\s*;\s*var\s+squared\s*=\s*Math\.pow\(\s*difference\s*,\s*2\s*\)\s*;?\s*return\s+acc\s*\+\s*squared\s*;/);
You should not remove the initial value of 0 from your .reduce() method.
assert.match(getVariance.toString(), /variance\s*=\s*array\.reduce\(\s*function\s*\(\s*acc\s*,\s*el\s*\)\s*\{\s*var\s+difference\s*=\s*el\s*-\s*mean\s*;\s*var\s+squared\s*=\s*Math\.pow\(\s*difference\s*,\s*2\s*\)\s*;?\s*return\s+acc\s*\+\s*squared\s*;\s*\}\s*,\s*0\s*\)/);
--seed--
--seed-contents--
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1" />
<link rel="stylesheet" href="./styles.css" />
<script src="./script.js"></script>
<title>Statistics Calculator</title>
</head>
<body>
<h1>Statistics Calculator</h1>
<p>Enter a list of comma-separated numbers.</p>
<form onsubmit="calculate(); return false;">
<label for="numbers">Numbers:</label>
<input type="text" name="numbers" id="numbers" />
<button type="submit">Calculate</button>
</form>
<div class="results">
<p>
The <dfn>mean</dfn> of a list of numbers is the average, calculated by
taking the sum of all numbers and dividing that by the count of numbers.
</p>
<p class="bold">Mean: <span id="mean"></span></p>
<p>
The <dfn>median</dfn> of a list of numbers is the number that appears in
the middle of the list, when sorted from least to greatest.
</p>
<p class="bold">Median: <span id="median"></span></p>
<p>
The <dfn>mode</dfn> of a list of numbers is the number that appears most
often in the list.
</p>
<p class="bold">Mode: <span id="mode"></span></p>
<p>
The <dfn>range</dfn> of a list of numbers is the difference between the
largest and smallest numbers in the list.
</p>
<p class="bold">Range: <span id="range"></span></p>
<p>
The <dfn>variance</dfn> of a list of numbers measures how far the values
are from the mean, on average.
</p>
<p class="bold">Variance: <span id="variance"></span></p>
<p>
The <dfn>standard deviation</dfn> of a list of numbers is the square
root of the variance.
</p>
<p class="bold">
Standard Deviation: <span id="standardDeviation"></span>
</p>
</div>
</body>
</html>
body {
margin: 0;
background-color: rgb(27, 27, 50);
text-align: center;
color: #fff;
}
button {
cursor: pointer;
background-color: rgb(59, 59, 79);
border: 3px solid white;
color: white;
}
input {
background-color: rgb(10, 10, 35);
color: white;
border: 1px solid rgb(59, 59, 79);
}
.bold {
font-weight: bold;
}
const getMean = (array) => array.reduce((acc, el) => acc + el, 0) / array.length;
const getMedian = (array) => {
const sorted = array.sort((a, b) => a - b);
const median =
array.length % 2 === 0
? getMean([sorted[array.length / 2], sorted[array.length / 2 - 1]])
: sorted[Math.floor(array.length / 2)];
return median;
}
const getMode = (array) => {
const counts = {};
array.forEach((el) => {
counts[el] = (counts[el] || 0) + 1;
})
if (new Set(Object.values(counts)).size === 1) {
return null;
}
const highest = Object.keys(counts).sort(
(a, b) => counts[b] - counts[a]
)[0];
const mode = Object.keys(counts).filter(
(el) => counts[el] === counts[highest]
);
return mode.join(", ");
}
const getRange = (array) => {
return Math.max(...array) - Math.min(...array);
}
--fcc-editable-region--
const getVariance = (array) => {
const mean = getMean(array);
const variance = array.reduce((acc, el) => {
}, 0);
}
--fcc-editable-region--
const calculate = () => {
const value = document.querySelector("#numbers").value;
const array = value.split(/,\s*/g);
const numbers = array.map(el => Number(el)).filter(el => !isNaN(el));
const mean = getMean(numbers);
const median = getMedian(numbers);
const mode = getMode(numbers);
const range = getRange(numbers);
document.querySelector("#mean").textContent = mean;
document.querySelector("#median").textContent = median;
document.querySelector("#mode").textContent = mode;
document.querySelector("#range").textContent = range;
}