diff --git a/README.md b/README.md
index 192d06a..d800382 100644
--- a/README.md
+++ b/README.md
@@ -10,8 +10,10 @@ A self-contained C99 library that provides a subset of [Squiggle](https://www.sq
 - Because it will last long
 - Because it can fit in my head
 - Because if you can implement something in C, you can implement it anywhere else
-- Because it can be made faster if need be, e.g., with a multi-threading library like OpenMP, or by adding more algorithmic complexity
-- **Because there are few abstractions between it and the bare metal: C -> assembly = CPU instructions**, leading to fewer errors beyond the programmer's control.
+- Because it can be made faster if need be
+  - e.g., with a multi-threading library like OpenMP, or by adding more algorithmic complexity
+  - or more simply, by inlining the sampling functions (adding an `inline` directive before their function declaration)
+- **Because there are few abstractions between it and machine code** (C => assembly => machine code with gcc, or C => machine code, with tcc), leading to fewer errors beyond the programmer's control.
 
 ## Getting started
 
@@ -79,8 +81,13 @@ Behaviour on error can be toggled by the `EXIT_ON_ERROR` variable. This library
 
 - [ ] Have some more complicated & realistic example
 - [ ] Add summarization functions: 90% ci (or all c.i.?) 
+- [ ] Systematize references
 - [ ] Publish online
 - [ ] Add efficient sampling from a beta distribution
+  - https://dl.acm.org/doi/10.1145/358407.358414
+  - https://link.springer.com/article/10.1007/bf02293108
+  - https://stats.stackexchange.com/questions/502146/how-does-numpy-generate-samples-from-a-beta-distribution
+  - https://github.com/numpy/numpy/blob/5cae51e794d69dd553104099305e9f92db237c53/numpy/random/src/distributions/distributions.c
 - [ ] Support all distribution functions in <https://www.squiggle-language.com/docs/Api/Dist>
 - [ ] Support all distribution functions in <https://www.squiggle-language.com/docs/Api/Dist>, and do so efficiently
 
@@ -107,3 +114,5 @@ Behaviour on error can be toggled by the `EXIT_ON_ERROR` variable. This library
   - [x] Explain individual examples
 - [x] Rename functions to something more self-explanatory, e.g,. `sample_unit_normal`.
 - [x] Add summarization functions: mean, std
+- [x] Add sampling from a gamma distribution
+  - https://dl.acm.org/doi/pdf/10.1145/358407.358414
diff --git a/examples/05_sample_from_cdf_beta/example b/examples/05_sample_from_cdf_beta/example
index b60681a..4bc0554 100755
Binary files a/examples/05_sample_from_cdf_beta/example and b/examples/05_sample_from_cdf_beta/example differ
diff --git a/examples/05_sample_from_cdf_beta/makefile b/examples/05_sample_from_cdf_beta/makefile
index 30cebab..2580b8c 100644
--- a/examples/05_sample_from_cdf_beta/makefile
+++ b/examples/05_sample_from_cdf_beta/makefile
@@ -18,12 +18,13 @@ DEPENDENCIES=$(MATH)
 # OPENMP=-fopenmp
 
 ## Flags
+VERBOSE=#-v
 DEBUG= #'-g'
 STANDARD=-std=c99 ## gnu99 allows for nested functions.
 EXTENSIONS= #-fnested-functions
 WARNINGS=-Wall
 OPTIMIZED=-O3#-Ofast
-CFLAGS=$(DEBUG) $(STANDARD) $(EXTENSIONS) $(WARNINGS) $(OPTIMIZED)
+CFLAGS=$(VERBOSE) $(DEBUG) $(STANDARD) $(EXTENSIONS) $(WARNINGS) $(OPTIMIZED)
 
 ## Formatter
 STYLE_BLUEPRINT=webkit
diff --git a/references/marsaglia-gamma.pdf b/references/marsaglia-gamma.pdf
new file mode 100644
index 0000000..d3a6982
Binary files /dev/null and b/references/marsaglia-gamma.pdf differ
diff --git a/squiggle.c b/squiggle.c
index 11b66f8..c8e30dd 100644
--- a/squiggle.c
+++ b/squiggle.c
@@ -73,6 +73,42 @@ float sample_to(float low, float high, uint32_t* seed)
     return sample_lognormal(logmean, logsigma, seed);
 }
 
+float sample_gamma(float alpha, uint32_t* seed){
+
+  // A Simple Method for Generating Gamma Variables, Marsaglia and Wan Tsang, 2001
+	// https://dl.acm.org/doi/pdf/10.1145/358407.358414
+	// see also the references/ folder
+	if(alpha >=1){
+		float d, c, x, v, u;
+		d = alpha - 1.0/3.0;
+		c = 1.0/sqrt(9.0 * d);
+		while(1){
+			
+			do {
+				x = sample_unit_normal(seed);
+				v = 1.0 + c * x;
+			} while(v <= 0.0);
+
+			v = pow(v, 3);
+			u = sample_unit_uniform(seed);
+			if( u < 1.0 - 0.0331 * pow(x, 4)){ // Condition 1
+					// the 0.0331 doesn't inspire much confidence
+					// however, this isn't the whole story
+					// by knowing that Condition 1 implies condition 2
+					// we realize that this is just a way of making the algorithm faster
+					// i.e., of not using the logarithms
+					return d*v;
+			}
+			if(log(u) < 0.5*pow(x,2) + d*(1.0 - v + log(v))){ // Condition 2
+				return d*v;
+			}
+		}
+	}else{
+		return sample_gamma(1 + alpha, seed) * pow(sample_unit_uniform(seed), 1/alpha);
+		// see note in p. 371 of https://dl.acm.org/doi/pdf/10.1145/358407.358414
+	}
+}
+
 // Array helpers
 float array_sum(float* array, int length)
 {