--- id: 6352fce75b2d3b2924930f1e title: Step 49 challengeType: 0 dashedName: step-49 --- # --description-- With two `.map()` calls and a `.reduce()` call, you're creating extra arrays and iterating more times than needed. You should move all of the logic into the `.reduce()` call to save time and memory. Remove the `differences`, `squaredDifferences`, and `sumSquaredDifferences` variables (and their values). Declare a `variance` variable, and assign it the value of `array.reduce()`. For the callback, pass in your standard `acc` and `el` parameters, but leave the function body empty for now. Don't forget to set the initial value to `0`. # --hints-- You should remove the `differences` variable. ```js assert.notMatch(getVariance.toString(), /differences\s*=/); ``` You should remove the `squaredDifferences` variable. ```js assert.notMatch(getVariance.toString(), /squaredDifferences\s*=/); ``` You should remove the `sumSquaredDifferences` variable. ```js assert.notMatch(getVariance.toString(), /sumSquaredDifferences\s*=/); ``` You should have a `variance` variable. ```js assert.match(getVariance.toString(), /variance\s*=/); ``` Your `variance` variable should use the `array.reduce()` method. ```js assert.match(getVariance.toString(), /variance\s*=\s*array\.reduce\(/); ``` Your `variance` variable should use the `acc` and `el` parameters in the callback function. ```js assert.match(getVariance.toString(), /variance\s*=\s*array\.reduce\(\s*function\s*\(\s*acc\s*,\s*el\s*\)/); ``` Your `reduce` callback should be an empty function. ```js assert.match(getVariance.toString(), /variance\s*=\s*array\.reduce\(\s*function\s*\(\s*acc\s*,\s*el\s*\)\s*\{\s*\}/); ``` Your `reduce` callback should have an initial value of `0`. ```js assert.match(getVariance.toString(), /variance\s*=\s*array\.reduce\(\s*function\s*\(\s*acc\s*,\s*el\s*\)\s*\{\s*\}\s*,\s*0\s*\)/); ``` # --seed-- ## --seed-contents-- ```html Statistics Calculator

Statistics Calculator

Enter a list of comma-separated numbers.

The mean of a list of numbers is the average, calculated by taking the sum of all numbers and dividing that by the count of numbers.

Mean:

The median of a list of numbers is the number that appears in the middle of the list, when sorted from least to greatest.

Median:

The mode of a list of numbers is the number that appears most often in the list.

Mode:

The range of a list of numbers is the difference between the largest and smallest numbers in the list.

Range:

The variance of a list of numbers measures how far the values are from the mean, on average.

Variance:

The standard deviation of a list of numbers is the square root of the variance.

Standard Deviation:

``` ```css 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; } ``` ```js 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 differences = array.map( el => el - mean ); const squaredDifferences = differences.map( el => el ** 2 ); const sumSquaredDifferences = squaredDifferences.reduce( (acc, el) => 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; } ```