diff --git a/concepts/randomness/.meta/config.json b/concepts/randomness/.meta/config.json
new file mode 100644
index 00000000..4f31b6dc
--- /dev/null
+++ b/concepts/randomness/.meta/config.json
@@ -0,0 +1,5 @@
+{
+  "authors": ["colinleach"],
+  "contributors": [],
+  "blurb": "R offers a rich variety of ways to generate random values, for many statistical distributions."
+}
\ No newline at end of file
diff --git a/concepts/randomness/about.md b/concepts/randomness/about.md
new file mode 100644
index 00000000..a520a556
--- /dev/null
+++ b/concepts/randomness/about.md
@@ -0,0 +1,39 @@
+# About
+
+R was derived from a statistics package and is often used for simulations, so it offers a rich variety of ways to generate random values.
+These are a few common ones.
+
+## Discrete values with `sample`
+
+To pick from a limited number of discrete values, `sample()` can be used with or without replacement (i.e. is it permitted to get repeated values?).
+This is useful for integers, strings, etc.
+
+```R
+> sample(1:10, 5) # no repeats
+[1] 8 3 4 2 6
+
+> sample(1:10, 5, replace = TRUE) # repeats are OK
+[1] 10 10  7 10  9
+
+> languages <- c("Fortran", "R", "Python", "Julia")
+> sample(languages, 1)
+[1] "Python"
+
+> sample(c(TRUE, FALSE), 5, replace = TRUE) # coin flips
+[1] FALSE  TRUE FALSE  TRUE  TRUE
+```
+
+## Floating-point numbers
+
+For a random-uniform distribution use `runif()`.
+Both `min` and `max` can be specified but default to 0 and 1.
+
+```R
+> runif(5)
+[1] 0.3038506 0.3527959 0.3319309 0.4846354 0.4386279
+
+> runif(5, max = 100)
+[1] 79.70762 51.62232 52.85281 71.08571 63.94380
+```
+
+Other common distributions include `rnorm()` for Gaussian, `rbinom()` for binomial, `rpois()` for Poisson, etc.
diff --git a/concepts/randomness/introduction.md b/concepts/randomness/introduction.md
new file mode 100644
index 00000000..6230d9d7
--- /dev/null
+++ b/concepts/randomness/introduction.md
@@ -0,0 +1,36 @@
+# Introduction
+
+There are many options for generating random values, and these are a few common ones.
+
+## Discrete values with `sample`
+
+To pick from a limited number of discrete values, `sample()` can be used with or without replacement (i.e. is it permitted to get repeated values?).
+This is useful for integers, strings, etc.
+
+```R
+> sample(1:10, 5) # no repeats
+[1] 8 3 4 2 6
+
+> sample(1:10, 5, replace = TRUE) # repeats are OK
+[1] 10 10  7 10  9
+
+> languages <- c("Fortran", "R", "Python", "Julia")
+> sample(languages, 1)
+[1] "Python"
+
+> sample(c(TRUE, FALSE), 5, replace = TRUE) # coin flips
+[1] FALSE  TRUE FALSE  TRUE  TRUE
+```
+
+## Floating-point numbers
+
+For a random-uniform distribution use `runif()`.
+Both `min` and `max` can be specified but default to 0 and 1.
+
+```R
+> runif(5)
+[1] 0.3038506 0.3527959 0.3319309 0.4846354 0.4386279
+
+> runif(5, max = 100)
+[1] 79.70762 51.62232 52.85281 71.08571 63.94380
+```
diff --git a/concepts/randomness/links.json b/concepts/randomness/links.json
new file mode 100644
index 00000000..013f4e6e
--- /dev/null
+++ b/concepts/randomness/links.json
@@ -0,0 +1,14 @@
+[
+  {
+    "url": "http://www.cookbook-r.com/Numbers/Generating_random_numbers/",
+    "description": "Cookbook for R"
+  },
+  {
+    "url": "https://www.educba.com/random-number-generator-in-r/",
+    "description": "EDUCBA"
+  },
+  {
+    "url": "https://www.statology.org/r-random-number/",
+    "description": "Statology"
+  }
+]
diff --git a/config.json b/config.json
index 01ec79ac..bd127020 100644
--- a/config.json
+++ b/config.json
@@ -569,6 +569,11 @@
       "uuid": "2751b6f2-7d71-4397-b063-9bf927a57756",
       "slug": "booleans",
       "name": "Booleans"
+    },
+    {
+      "uuid": "9de56486-6c39-4c08-9d5a-db78a524b0b1",
+      "slug": "randomness",
+      "name": "Randomness"
     }
   ],
   "key_features": [