diff --git a/inflammation-analysis.py b/inflammation-analysis.py
index 76a237ba..b8afab97 100644
--- a/inflammation-analysis.py
+++ b/inflammation-analysis.py
@@ -26,11 +26,13 @@ def main(args):
     for filename in in_files:
         inflammation_data = models.load_csv(filename)
 
-        view_data = {
-            "average": models.daily_mean(inflammation_data),
-            "max": models.daily_max(inflammation_data),
-            "min": models.daily_min(inflammation_data),
-        }
+        view_data = {'average': models.daily_mean(inflammation_data), 
+                     'max': models.daily_max(inflammation_data), 
+                     'min': models.daily_min(inflammation_data), 
+                     **(models.s_dev(inflammation_data))
+                    }
+
+
 
         views.visualize(view_data)
 
diff --git a/inflammation/models.py b/inflammation/models.py
index 4ff280c5..6b1318e4 100644
--- a/inflammation/models.py
+++ b/inflammation/models.py
@@ -70,6 +70,16 @@ def daily_min(data):
     return np.min(data, axis=0)
 
 
+def s_dev(data):
+    """Computes and returns standard deviation for data."""
+    mean_data = daily_mean(data)
+    devs = []
+    for entry in data:
+        devs.append((entry - mean_data) * (entry - mean_data))
+
+    s_dev2 = sum(devs) / len(data)
+    return {'standard deviation': s_dev2}
+
 def patient_normalise(data):
     """
     Normalise patient data from a 2D inflammation data array.
diff --git a/tests/test_models.py b/tests/test_models.py
index 6b884ad2..51b6e65c 100644
--- a/tests/test_models.py
+++ b/tests/test_models.py
@@ -3,6 +3,7 @@
 import os
 import numpy as np
 import numpy.testing as npt
+
 import pytest
 from inflammation.models import daily_mean
 from inflammation.models import daily_max
@@ -67,6 +68,16 @@ def test_load_from_json(tmpdir):
     npt.assert_array_equal(result, [[1, 2, 3], [4, 5, 6]])
 
 
+@pytest.mark.parametrize('data, expected_standard_deviation', [
+    ([0, 0, 0], 0.0),
+    ([1.0, 1.0, 1.0], 0),
+    ([0.0, 2.0], 1.0)
+])
+def test_daily_standard_deviation(data, expected_standard_deviation):
+    from inflammation.models import s_dev
+    result_data = s_dev(data)['standard deviation']
+    npt.assert_approx_equal(result_data, expected_standard_deviation)
+
 @pytest.mark.parametrize(
     "test, expected, expect_raises",
     [