diff --git a/README.md b/README.md
index 7622f26..0031827 100644
--- a/README.md
+++ b/README.md
@@ -34,6 +34,7 @@ npm i stat-methods
     -   [pStdev](#pStdev)
     -   [variance](#variance)
     -   [stdev](#stdev)
+    -   [medAbsdev](#medAbsdev)
     -   [range](#range)
 
 3.  [Descriptive statistics](#Descriptive-statistics)
@@ -332,6 +333,7 @@ These methods compute a measure of the variability in a sample or population, ho
 -   [pStdev](#pStdev): Population standard deviation
 -   [variance](#variance): Sample variance
 -   [stdev](#stdev): Sample standard deviation
+-   [medAbsdev](#medAbsdev): Median absolute deviation
 -   [range](#range): Range
 
 #### pVariance
@@ -430,6 +432,22 @@ stdev([1, 2, 3, 4, 5], xBar); // -> 1.5811388300841898
 
 Please refer to the [variance](#variance) method for further details.
 
+#### medAbsdev
+
+```js
+medAbsdev(arr);
+```
+
+Return the median absolute deviation of a numeric data array `arr`.
+
+The median absolute deviation is the median of the absolute deviations from a data sample's median.
+
+```js
+medAbsdev([1, 2, 3, 4, 5]); // -> 1
+```
+
+If the data array is empty or contains a non finite `Number`, the method returns `undefined`.
+
 #### range
 
 ```js
diff --git a/src/spread.js b/src/spread.js
index 65acbec..0fb7e7a 100644
--- a/src/spread.js
+++ b/src/spread.js
@@ -1,4 +1,8 @@
-import { mean } from './central';
+import {
+  mean,
+  median,
+} from './central';
+
 import {
   min,
   max,
@@ -81,6 +85,24 @@ export function stdev(arr, xBar) {
   return v === undefined ? v : Math.sqrt(v);
 }
 
+/**
+ * Return the median absolute deviation of a numeric data array.
+ * The median absolute deviation is the median of the absolute deviations
+ * from a data sample's median.
+ * @param {Number[]} arr the data array
+ * @returns {Number} the median absolute deviation of the data array
+ */
+export function medAbsdev(arr) {
+  const med = median(arr);
+  const absoluteDeviationArr = [];
+  if (med === undefined) return undefined;
+  for (let i = 0; i < arr.length; i += 1) {
+    const absdev = Math.abs(arr[i] - med);
+    absoluteDeviationArr.push(absdev);
+  }
+  return median(absoluteDeviationArr);
+}
+
 /**
  * Return the range of a numeric data array.
  * The range of a set of data is the difference between the largest and smallest values.
@@ -99,5 +121,6 @@ export default {
   pStdev,
   variance,
   stdev,
+  medAbsdev,
   range,
 };
diff --git a/test/spread.test.js b/test/spread.test.js
index 1e7ce78..f191ac4 100644
--- a/test/spread.test.js
+++ b/test/spread.test.js
@@ -4,6 +4,7 @@ import {
   pStdev,
   variance,
   stdev,
+  medAbsdev,
   range,
 } from '../src/spread';
 
@@ -53,6 +54,19 @@ describe('Measures of spread', () => {
     testUndefinedWithNullable(stdev);
   });
 
+  test('Median Absolute Deviation', () => {
+    expect(medAbsdev([1, 12, 3, 15, 6, 8, 9])).toBe(4);
+    expect(medAbsdev([1, -2, 3, 4, 8, 6, 5, 9])).toBe(2.5);
+    expect(medAbsdev([1, 2, 3, 4, 5])).toBe(1);
+    expect(medAbsdev([1, 2, 3, 4, 5, 6])).toBe(1.5);
+    expect(medAbsdev(['a', 2.5, 'b', 5.75])).toBeUndefined();
+    expect(medAbsdev([NaN, 2.5, 3, 5.75])).toBeUndefined();
+    expect(medAbsdev([])).toBeUndefined();
+    expect(medAbsdev(3)).toBeUndefined();
+    expect(medAbsdev([3])).toBe(0);
+    testUndefinedWithNullable(medAbsdev);
+  });
+
   test('Range', () => {
     expect(range([1.5, 2.5, 2.5, 2.75, 3.25, 4.75])).toBe(3.25);
     expect(range([89, 73, 84, 91, 87, 77, 94])).toBe(21);