diff --git a/README.md b/README.md
index 4cd866c..ee7b204 100644
--- a/README.md
+++ b/README.md
@@ -1,4 +1,6 @@
-# ``mcerp`` Real-time latin-hypercube sampling-based Monte Carlo ERror Propagation for Python
+# mcerp
+
+**Real-time latin-hypercube sampling-based Monte Carlo ERror Propagation for Python**
 
 [![Tests](https://github.com/eggzec/mcerp/actions/workflows/code_test.yml/badge.svg)](https://github.com/eggzec/mcerp/actions/workflows/code_test.yml)
 [![Documentation](https://github.com/eggzec/mcerp/actions/workflows/docs_build.yml/badge.svg)](https://github.com/eggzec/mcerp/actions/workflows/docs_build.yml)
diff --git a/docs/index.md b/docs/index.md
index 67c54af..85a2462 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -2,8 +2,8 @@
 
 ![MCERP](./_static/logo.png)
 
-Real-time latin-hypercube-sampling-based Monte Carlo error propagation for
-Python.
+**Real-time latin-hypercube-sampling-based Monte Carlo error propagation for
+Python.**
 
 `mcerp` is a stochastic calculator for uncertainty analysis. It represents
 inputs as probability distributions, samples them with Latin hypercube
diff --git a/docs/quickstart.md b/docs/quickstart.md
index 546e988..2ca6fc4 100644
--- a/docs/quickstart.md
+++ b/docs/quickstart.md
@@ -11,9 +11,9 @@ from mcerp import *
 Construct uncertain variables from probability distributions:
 
 ```python
-x1 = N(24, 1)   # normal distribution: mean 24, standard deviation 1
-x2 = N(37, 4)   # normal distribution: mean 37, standard deviation 4
-x3 = Exp(2)     # exponential distribution: lambda 2
+x1 = N(24, 1)  # normal distribution: mean 24, standard deviation 1
+x2 = N(37, 4)  # normal distribution: mean 37, standard deviation 4
+x3 = Exp(2)  # exponential distribution: lambda 2
 ```
 
 The first four moments are available as properties:
@@ -227,11 +227,7 @@ plotcorr([x1, x2, x3], labels=["x1", "x2", "x3"], show=True)
 Now impose a target correlation matrix:
 
 ```python
-c = np.array([
-    [1.0, -0.75, 0.0],
-    [-0.75, 1.0, 0.0],
-    [0.0, 0.0, 1.0],
-])
+c = np.array([[1.0, -0.75, 0.0], [-0.75, 1.0, 0.0], [0.0, 0.0, 1.0]])
 
 correlate([x1, x2, x3], c)
 correlation_matrix([x1, x2, x3])
diff --git a/docs/theory.md b/docs/theory.md
index 5189426..cb9e51b 100644
--- a/docs/theory.md
+++ b/docs/theory.md
@@ -387,11 +387,7 @@ x1 = N(24, 1)
 x2 = N(37, 4)
 x3 = Exp(2)
 
-R = np.array([
-    [1.0, -0.75, 0.0],
-    [-0.75, 1.0, 0.0],
-    [0.0, 0.0, 1.0],
-])
+R = np.array([[1.0, -0.75, 0.0], [-0.75, 1.0, 0.0], [0.0, 0.0, 1.0]])
 
 correlate([x1, x2, x3], R)